Achieving supervisory control of systemic risk by Peter Bonisch

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

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Achieving supervisory control of systemic risk Are we building the right systemic risk information highway for Financial Services? A report commissioned by the Financial Services Knowledge Transfer Network Prepared by Paradigm Risk and JWG | October 2010

Achieving supervisory control of systemic risk Authors Peter Bonisch

Managing Director, Paradigm Risk

PJ Di Giammarino

CEO, JWG

Alaric Gibson

Principal Research Assistant, JWG

Niall Gibson

Research Analyst, JWG

Reviewers Dr Mustafa Cavus

Managing Director, Paradigm Risk

Dr Colin Johnston

Managing Director, Paradigm Risk

Dickie Whitaker

Director, FSKTN

Christopher Clack ScD Director Financial Computing, UCL; Director FSKTN Nigel Walker

Technology Strategy Board

Dr Chris Sier

Director, FSKTN

About the FS-KTN and the Technology Strategy Board The Financial Services Knowledge Transfer Network is sponsored by the Technology Strategy Board and by the Economic and Social Research Council. The Technology Strategy Board is a business-led executive non-departmental public body, established by the government. Its mission is to promote and support research into, and development and exploitation of, technology and innovation for the benefit of UK business. For more information on the Financial Services Knowledge Transfer Network, visit: https://ktn.innovateuk.org/web/financialservicesktn/overview About JWG JWG seeks to be recognised by regulators, financial institutions and technology firms as the independent analysts to help determine how the right regulations can be implemented in the right way. Its status as an independent think-tank focusing on financial services regulation permits collaboration across the industry without serving the interests of any constituent over another. For more information visit: www.jwg-it.eu. About Paradigm Risk Paradigm Risk is a London-based, multi-disciplinary risk consulting firm specialising in financial services. It brings together expert consultants and practitioners in the fields of governance, risk and assurance to offer experience-based and thought-led advisory services to financial institutions. Paradigm Risk focuses on leading insights into improving firm behaviour and effectiveness in governance and management of risk and assurance. www.paradigmrisk.com

Citation: Bonisch, P. and P.J. Di Giammarino, (2010), Achieving supervisory control of systemic risk, London: FS KTN, JWG and Paradigm Risk

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Contents

Foreword

vii

About this report

Executive summary

Signposting the systemic risk information highway

xiii

Introduction

1.1

Focus of the report

1.2

Acknowledgements

1.3

Framing the question

The rethink

2.1

Defining systemic risk

2.2

Systemic risk as an externality

2.3

A definition of systemically important firms (and other ‘things’)

2.4

What the financial crisis tells us about systemic risk

The redesign

3.1

Scoping the solution

3.2

Objectives for a systemic risk regime

3.3

The SR control paradox and illusion of control

3.4

Why systemic risk can’t be ‘Googled’

3.5

So, what now?

3.6

Regulatory framework

3.7

A framework for systemic risk control

3.8

The investment decision

The retooling

4.1

The response to the financial crisis and its effectiveness

4.2

The changing face of supervision

4.3

The future is ... big, bad and global

4.4

Uncertain landscape for regulatory control

4.5

What are the control gaps?

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

CONTENTS

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The answer

5.1

Todayâ&#x20AC;&#x2122;s regulatory information management landscape

5.2

Designing the platform

The roadmap

6.1

Setting the implementation path

6.2

The UK opportunity

6.3

The barriers to change

6.4

Getting started

6.5

Summary

6.6

Paradigm shifts

6.7

When is a solution possible?

Findings and conclusions

7.1

Collaboration: the key to success

7.2

Findings for politicians, regulators and supervisors

7.3

Findings for investment firms, their suppliers, trade bodies and technical associations

7.4

Findings for the research community, academics and funding agencies

7.5

Conclusions

List of attachments

Interviews conducted

Bibliography

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Figure contents

Figures Figure 1:

Key terms used in this report

Figure 2:

Framework for regulatory toolkit

Figure 3:

Classification of systemic risk models

Figure 4:

G20 action plan (excerpt)

Figure 5:

European System of Financial Supervisors

Figure 6:

Evolution of supervisory data requirements

Figure 7:

Potential risk performance objectives

Figure 8:

Expected value computations

Figure 9:

Platform options

Figure 10: Workable risk data?

Figure 11: What this means for standards

Figure 12: The principles for developing a new system

Figure 13: How comprehensive are the systemic data needs?

Figure 14: Example data anomalies

Figure 15: Systemic risk control engineering

Figure 16: FS operating model impact assessment â&#x20AC;&#x201C; Q2 2010

Figure 17: The systemic risk oversight implementation roadmap checklist

Figure 18: Future UK regulatory landscape

Figure 19: Examples of systemic risk oversight platform design committees

Figure 20: Systemic risk control barriers

Figure 21: Focus of immediate action

Figure 22: Issues for development roadmap

Figure 23: Key findings

Figure 24: Paradigm shifts

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

FIGURE CONTENTS

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FOREWORD

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Foreword

The challenge of finding new and effective approaches to dealing with systemic risk is huge and immediate. The landscape is changing quickly and, to date, the industry has been hard-pressed to keep up with the complexity and volume of issues. The practical challenges facing financial firms, regulators and legislators – both in a UK and international context – in the development and implementation of a systemic risk control framework are fundamental to establishing an effective foundation for financial stability. It is clear that critical issues like systemic risk reporting are vital to establishing effective oversight. To succeed, approaches must be inclusive of the views from central bankers, regulators, international agencies and the academic community. Equally, they must also be capable of being implemented in practice. Engagement by – and with – the financial services sector is vital for practical measures to be productive and sustainable. The Financial Services Knowledge Transfer Network is keen to assist in the development of solutions in this important, but so far relatively neglected, topic that has profound implications for the financial services industry and, indeed, for the entire global economy. A rigorous review focusing on the control requirements and practical impediments facing UK and European firms and regulators – the parties that will have to implement new approaches to systemic risk here – is timely and, we hope, welcome.

David Bennett Chairman Financial Services Knowledge Transfer Network

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ABOUT THIS REPORT

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

About this report

Background This report on systemic risk reporting has been commissioned by the Financial Services Knowledge Transfer Network (FS-KTN). The FS-KTN is one of a range of knowledge transfer networks, an over-arching national network designed to bring together people from business, universities, research, financial and technology organisations to stimulate innovation through knowledge sharing and exchange. The FS-KTN was launched in 2009 with the objective of promoting knowledge transfer and exchange to improve innovation and collaboration within sectors of the financial services industry, across sectors of the industry, between the industry and the research base and between the industry and related suppliers of products and services. More details about the FS-KTN and its activities can be found at www.innovateuk.org/ financialservicesktn.

About the research It is difficult to know what the ideal team to review practical issues in implementation in systemic risk would look like. It is necessary to balance experience with independence, interview skills with technical expertise, knowledge with practicality and curiosity with an action orientation. In the event, our team came together because we knew each other and covered knowledge of regulation, regulatory processes, economics, history, mathematics, financial services, systems and data management and academia. The team has conducted 30+ interviews with representatives of central banks, regulators, supervisors, major banks, broker dealers, hedge funds and asset managers, international agencies, suppliers to financial services and trade associations across Europe and the United States. A list of institutions with which we conducted interviews is appended. In parallel, the team has reviewed over 300 official documents containing more than 100,000 pages, academic contributions and industry research on the systemic risk debate. Many of these have been consistent but there has been a significant minority with opposing or contrary perspectives to understand and compare. Although there is a bibliography attached to this report, it is not comprehensive; for comprehensive tracking the multitude of global documents which constitute the regulatory tsunami, see www.jwg-it.eu. With systemic risk being such an â&#x20AC;&#x2DC;umbrella topicâ&#x20AC;&#x2122;, this report necessarily involved the findings of over 20 research efforts conducted by JWG into the G20â&#x20AC;&#x2122;s regulatory change programme. The team has pieced together a picture of an industry that is just getting to grips with the fact that it has to make some fundamental changes and faces a worrying spread in approaches that will bring both regulatory and commercial consequences.

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EXECUTIVE SUMMARY

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Executive summary

Controlling a system as complex as the global financial markets requires the linkage of disparate and disconnected pools of information. Engineering an effective control framework, therefore, requires a complete rethink, redesign and retooling of the way the supervisors and industry manage and share their risk information. Out-dated information structures are being expected to monitor a complex, technologically advanced and continually growing marketplace. Simply put, the old risk management tools are not equipped to manage today’s global, ‘system-level’ events, nor will they ever without material change. A ‘new solution’ to replace macro models that are disconnected from firm-level measures will be neither simple nor cheap. The problems are fundamental, long-standing and many of them currently unowned. Without a new global control framework, the potential cost could run into tens of billions. To be successful, an agile and adaptive monitoring system is required. Following over 30 interviews with representatives from central banks, regulators, supervisors, major investment firms and their trade bodies, standards organisations and technology suppliers, the report identifies sizable barriers and constraints to controlling systemic risk that have yet to be prioritised and resourced both by the regulatory community and the financial institutions that it oversees. Despite the thousands of data points collected by regulators across the globe today, there is no agreed regulatory data architecture in place. Financial and technological innovation continually shifts the goal posts on what information is required. As big market infrastructure changes and hundreds of new dataintensive rules are implemented, there is little time for the development of appropriate standards that allow information to be aggregated and compared. Not only will the current situation distract firms and their supervisors from controlling new risks, it will lead to the development of a control infrastructure that incurs the risk of Garbage In, Gospel Out’ (GIGO) – creating the illusion, but not the reality, of control. To avoid this problem, the design constraint of ‘the how’ needs to be taken into account by those who define ‘the what.’ We need to establish a blueprint for good systemic risk control comprising: !

The design principles required for a new information road system

A supervisory information inventory and gap assessment

An adaptable and future-proof target operating model

A clear migration path, timeline and governance models

A transparent assessment of costs, commercial models and tariff measures.

While national reform is certainly necessary, emphasis needs to be placed on the alignment of objectives, measures, tools and data collection efforts between national supervisors and supranational entities mandated to monitor systemic risk across the global system. All parts of industry – firms, regulators, supervisors, academics, central bankers, trade bodies, technology vendors and interested politicians – will need to focus their attention on the key barriers to achieving these goals and collaborate at levels not seen previously. Now is the time to ensure the central functions get the right people together to create a practical blueprint for the right systemic risk roadmap that gets us to the right place.

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SIGNPOSTING THE SYSTEMIC RISK INFORMATION HIGHWAY

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

xiii

Signposting the systemic risk information highway Chapter questions

CHAPTER 2: THE RETHINK

Key messages

Oversight is hard: vehicles move about the FS infrastructure on disconnected country lanes, toll roads and intercity road networks

There is no agency or ‘system’ for holistic regulatory control today – reports are filed by important firms to independent traffic authorities across the globe

The G20 mandate requires new control towers to track behaviours and spot fast-moving, innovative and potentially dangerous traffic patterns at firm, market and system level

We collect vast amounts of information today but our ability to link and access it is limited – a new shared infrastructure is required to analyse complex markets

More information is required than is collected today, but, paradoxically, this makes problems even harder to spot – new and multiple control models running in parallel are needed

This is a global problem involving hundreds of players that cannot be tackled without the appropriate, accountable governance to avoid spending billions

New capital and liquidity buffers have been built into the system and control points have been mandated (e.g., OTC derivatives clearing on exchange)

New reports from important firms have been defined by country without the definition of standards that are required to make the information intelligible

Significant disconnects in information management approaches and lack of discourse between jurisdictions exist

Key gaps in knowledge, information, motivation, governance and planning between relevant actors

To be successful, paradigms must shift for policy makers, supervisors, firms (and trade bodies), academics and suppliers

To control development risk, objectives and target operating models need to be defined and agreed

Further resourcing, research and collaboration is required to overcome significant barriers

Appropriate bodies need to be made accountable for delivering an implementation roadmap

What systemic risk information infrastructure exists today? What problem are we attempting to solve? Who needs to be part of the solution?

CHAPTER 3: THE REDESIGN What information do we need to spot systemic risks and how will we use it? Are the control towers and radars in the centre fit for purpose? What will it cost, is it of value and how will we pay for it?

CHAPTER 4: THE RETOOLING What new controls have been asked for? What new infrastructure has been mandated? How coordinated has the G20 approach been?

CHAPTER 5: THE ANSWER What gaps must be closed? What changes should be made?

CHAPTER 6: THE ROADMAP Who owns it? When is it needed? What needs to happen now?

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INTRODUCTION

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

1. Introduction

1.1 FOCUS OF THE REPORT This report and the review that has led to it occupy an unusual position between official reviews, academic contributions to the topic and the practical requirements of regulators, supervisors and firms to establish effective systemic risk control. Although much of the report covers ground that is treated elsewhere, we have attempted to approach the topic from the perspective of practical requirements which, thus far, have been distinctly lacking in the debate on systemic risk regulation. Our perspective is relatively simple: nothing can happen (i.e., be implemented) without the engagement of, and action by, investment firms. Because firms are a critical piece of any development puzzle, they must be able to connect with the topic. That implies attention, a focal point for engagement and an understanding of the grounds of the debate. While there is vast and growing academic literature on systemic risk, and a growing number of official contributions to the field, the practical issues of how to make a systemic risk control framework happen – and the barriers that may exist to doing so – have rarely been discussed or considered. We believe this is a serious and unsustainable omission. The capacity of firms to access data which is not currently available to regulators and the standards for, and comparability of, that data represent the major constraint in the development of the global, regional and national systemic risk control platforms. We began this exercise intent on focusing on the ‘pipes and plumbing’ aspects of systemic risk. However, over the course of our review, it became apparent that the underlying conditions for, and constraints to, creating a systemic risk supervisory capability were poorly (if at all) understood at official level. The basis for a discourse with firms on systemic risk simply was not present and, with academics, was ‘captured’ by orthodox economic principles that have been called seriously into question by the events of the financial crisis. This report is an attempt to lay out the conditions and constraints facing officials, firms and the academic and research communities and to make suggestions about how to satisfy or overcome them.

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

INTRODUCTION

1.2 ACKNOWLEDGEMENTS We are deeply gratified by and grateful for the generosity of people we have interviewed in all sectors – investment firms, regulators, central bankers and academics and economists – for the time they have been willing to contribute to assist us to complete this report. We have conducted many interviews in a short space of time and have sought, and received, comments widely from the official community, from practitioners and from academics. What has surprised us most is the willingness of people we have interviewed to acknowledge sectoral territorial limitations and to confess the limits of their knowledge. While a little scary in terms of pressing to a systemic risk control platform, that state of affairs is infinitely preferable to misplaced confidence. In this area, we all have a lot to learn. Any remaining errors and omissions remain the responsibility of the authors.

1.3 FRAMING THE QUESTION The policy challenge and the subsequent supervisory challenge of systemic risk are to prevent an excessive build-up of risk in the financial system. This entails, essentially, two different activities: !

Determining the level of “froth” (to use Alan Greenspan’s term) in asset values in financial markets and

Determining whether the level of interconnectedness between firms in the financial network represents a danger in terms of potential emergence of instability within that network

The first issue concerns (in the famous words of former Federal Reserve Board Chairman, William Martin) when to take away the punchbowl, or suppress economic activity in a market or markets. The second requires a deep understanding of the operation of all financial markets, especially interbank markets, commitments, claims and contingencies. Our work covers both of these activities. Note on terminology In this report, we use the term ‘systemic risk’ precisely. We explain systemic risk, its economic meaning and use in practice in sections 1 to 2.3 and delimit it relative to other, similar or related policy terms (microprudential, macroprudential, etc) in section 3.6. In relation to the ‘what’ of action to enhance supervision, we use a range of terms. For clarity, these are used as follows:

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

INTRODUCTION

Figure 1: Key terms used in this report Framework

Conceptual approach based on clearly expressed design principles

System

Information system used to extract, transmit, process, analyse, store or retrieve data. Also a synonym for ‘platform.’

Also refers to the ‘financial system’: the players and inter-relationships between players in the economy (including non-UK) and their network of transactions, payments, contracts, commitment, claims and contingencies.

Architecture

Design principles for systems, especially when multiple systems are linked within a firm or across firms and/or the supervisor; a ‘meta-layer’ of information

Model

A theoretical description of a complex process or (non-IT) system used to infer relationships between variables, or players, or both

Also used in the context of ‘operating model’ which describes the processes, people and technology requirements

Capability

Ability to select and apply relevant knowledge to a problem and to organise resources to address and resolve a problem

Capacity

Availability of resources and capability

Platform

The system, architecture, model, capability and capacity to achieve a stated (supervisory) objective

Toolkit

The policy response options and levers available to the supervisor to act at financial system, market and agent level.

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

THE RETHINK

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

2. The rethink

“Those who cannot remember the past are condemned to repeat it.” Jorge Agustín Nicolás Ruiz de Santayana y Borrás (1863 – 1952)

SUMMARY !"The financial crises of 2007 and 2008 have shown us that there needs to be a fundamental rethink in the way systemic risk is managed and financial stability maintained !"The previous approach to managing systemic risk was flawed in both its ability to spot risk within increasingly complex financial instruments and networks and the behavioural aspects that applied to them !"There were bodies charged with addressing systemic risk; however, they were not given the right tools to combat it. The orthodox ‘reduced-form’ macroeconomic models were disconnected from firm-level behaviour and offered only limited utility in understanding the risks of the financial system !"Systemic risk, by its nature, is a threat to the global system; however, despite the G20 objectives, there are no bodies yet mandated with a holistic approach to the global remediation of systemic risk !"The problems are well understood in silos but are difficult to reconcile without increased collaboration between academics, politicians, regulators, central banks and financial institutions !"While we understand what systemic risk is, we don’t know how to control it

2.1 DEFINING SYSTEMIC RISK There have been many definitions of ‘systemic risk’ offered, both before and after the financial crisis that began in 2007 and intensified in 2008. Standard definitions focus on impact, for example: “the probability that a series of correlated defaults among financial institutions, occurring over a short time span, will trigger a withdrawal of liquidity and widespread loss of confidence in the financial system as a whole”1, resulting in increases in the cost of capital (or credit) or decreases in its availability to non-financial firms (and households). This definition captures the range of issues usually discussed prior to ‘the event’. However, that definition paid no attention to either causes of crisis or transmission or amplification mechanisms between firms or between the financial services sector and the wider economy. By failing to identify the behavioural aspects of the formation and transmission of the crisis – and the frequently endogenous nature of financial crises generally – the definition may steer politicians, policy makers and regulators in the wrong direction. In short, a close examination of the financial crisis suggests we need a modified definition of systemic risk that reflects the reality ‘on the ground’. The nature of the risk may not have changed – as Kindleberger2 points out, “details proliferate, structure abides” – but our appreciation of it clearly has; as has our appreciation of the need to form a deeper understanding of the way speculative pressures emerge in an economy and to gauge ‘how much is too much’. An expanded definition of systemic risk would reflect the possibility of contagion of the financial system resulting from the failure of an institution or market function that is connected, via a network of financial 1

Monica Billio, Mila Getmansky, Andrew Lo and Loriana Pelizzon (2010), Econometric Measures of Systemic Risk in the Finance and Insurance Sectors (July 18). MIT Sloan Research Paper No. 4774-10; NBER Working Paper No. 16223, based on an earlier definition by Nicholas Chan, Getmansky, Lo and Shane Haas Charles Kindleberger and Robert Aliber, Manias, Panics and Crashes: A History of Financial Crises, 5. ed., Palgrave MacMillan, 2005

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

THE RETHINK

claims and commitments, with other financial and non-financial firms. The cause may be an event or series of events in the non-financial sector economy (exogenous) or the behaviour of financial firms or the interaction between them (endogenous). Because systemic risk relates to the interconnectedness of the firm with other firms (as well as its resilience to capital or other stress), rather than any aspect of the firm over which it can exercise management control, it is different from other risks – market, credit, operational, liquidity, maturity transformation, etc, faced by firms. As a result, there is no logical ‘control point’ or function responsible for systemic risk in the firm; it doesn’t live in any existing risk function. Short of increasing resilience through additional prudential capital or reducing interconnectedness with other financial firms, there are limited management actions a firm can take to reduce its systemic risk. However, reducing resilience and increasing interconnectedness raise the probability of the leveraged firm creating ‘externalities’ – probabilities of the firm’s failure resulting in contagion to other firms in the interconnected financial system. While there have been prominent analyses of financial crisis and the mechanisms through which the financial sector and the ‘real economy’ interact, few of the lessons appear to have been absorbed into standard macroeconomic models. Indebtedness, both at national and household levels, appears to be a common factor;3 or, as two authors put it: “when an accident is waiting to happen, it usually does”.4 They talk about the “debt-fuelled asset explosions”, but note that the timing of the bubble bursting “can be very difficult to guess and a crisis that seems imminent can sometimes take years to ignite.”5 The linkage between the financial sector, the payment system and the supply of working capital to the real economy makes financial crises, as opposed to other forms of economic crisis – inflation, external and internal debt crises, institutional financial distress, the ‘tech stock boom’ – particularly problematic.6 The recent crisis coincided with the collapse of a US housing bubble, as it did in many European countries and, with large current account deficits and ‘capital flow bonanzas’ as imported capital fuelled the credit and asset price booms (including US, UK, Spain, Iceland, Ireland, Bulgaria, Latvia and New Zealand).7 Some approaches treat financial instability as an inevitable part of the economic cycle: Hyman Minsky’s ‘financial instability hypothesis’8 is a prominent example. Minsky’s approach emphasised the role of confidence and optimism, especially around risk: firms’ ‘risk averseness’ changed through, and partially drove, the economic cycle9. While Minsky believed that crises begin with a ‘displacement’ or exogenous shock to the system10, others recognise that disturbances can arise within the system through feedback mechanisms around agents’ confidence, just as Minsky emphasised. Kindleberger and Aliber note that crises have both causa remota – background conditions such as expansion of credit and excessive speculation (or ‘over-trading’ in Adam Smith’s term) – and causa proxima – some potentially trivial event (a bankruptcy, a suicide, a revelation of fraud, a loan being declined) “which saps the confidence of the system”11 and causes investors to exit the assets they consider potentially over-valued and change their liquidity preferences.12 The effect: “prices fall; expectations are reversed; the downward price movements accelerate”.13 Here a ‘tipping point’ has been reached and ‘positive feedback’ takes over. These ‘feedback loops’ operate in all markets, as prices both increase and decrease, and are an essential characteristic of the financial system. Changes or adaptations in investors’ confidence levels and expectations 3 4 5 6 7 8 9 10 11 12 13

Carmen Reinhart and Kenneth Rogoff (2009), This Time is Different: Eight Centuries of Financial Folly, Princeton University Press ibid. ibid. Kindleberger & Aliber (2005) Reinhart & Rogoff (2009) Hyman P. Minsky (1992), The Financial Instability Hypothesis, The Jerome Levy Economics Institute of Bard College, Working Paper No. 74 (May) George A. Akerlof and Robert J. Shiller (2009) Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism, Princeton UP. Kindleberger & Aliber (2005) ibid. Reinhart & Rogoff (2009) Kindleberger & Aliber (2005)

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THE RETHINK

can – and do – impact the financial system’s momentum and direction. And they are unpredictable: “feedback loop dynamics can generate complex and even apparently random behaviour”14; crises can occur endogenously as well as being caused by external shocks. Analysing feedback loops necessitates incorporating human or ‘agent’ behaviour into models: ’decision heuristics and biases’ – anchoring, framing, overconfidence, reliance on intuition – that predominate in human decision-making and judgement under uncertain conditions, as well as relying on belief networks and analysis of adjustment of prior beliefs. Some commentators believe analytical methods that deal with behavioural feedback loops are essential additions to the armoury for fighting systemic risk.15 Whether the methods to fight it are related to observation of complex systems or modelling and simulation (such as agent-based modelling), our definition of systemic risk needs to incorporate complexity and feedback systems that give rise to it. At firm level, the implications of increasing efforts to control systemic risk are that, for the first time, firms are likely to face detailed examination by systemic risk supervisors of how their trading and operating behaviour – their resilience and interconnectedness – may create risk for the financial system that is not priced into their market activity. If, and when, it is priced in, through taxes or capital add-ons, this will necessitate firms’ understanding of how their business activities contribute to systemic risk. There is no comparable basis for such analysis today.

2.2 SYSTEMIC RISK AS AN EXTERNALITY A common justification for regulation is the presence of market failure, one class of which is an unpriced or uncorrected negative externality – the imposition of a cost on another party. Classically, externalities can be described as “any situation where some Paretian costs and benefits remain external to decentralised costrevenue calculations in terms of prices”.16 The interconnectedness of the leveraged financial firm and its risktaking creates an ‘ownership externality’17 which “arises from the way that financial intermediaries’ claims are interwoven”18, as well as their behaviour during periods of stress in the firm or the system. A recent paper on financial regulation outlines five ways in which externalities occur within the banking sector.19 Schwarcz (2008) 20 describes the problem in considerable detail: “Without regulation, the externalities caused by systemic risk would not be prevented or internalized because the motivation of market participants ‘is to protect themselves but not the system as a whole. ... No firm ... has an incentive to limit its risk taking in order to reduce the danger of contagion for other firms.’ The externalities caused by systemic risk also can go far beyond market participants, so even if market participants were able to collectively act to prevent systemic risk they might not choose to do so. This creates a type of tragedy of the commons, in which the benefits of exploiting finite capital resources accrue to individuals, each of which is motivated to maximize use of the resource, whereas the costs of exploitation are distributed among an even wider class of individuals [i.e., taxpayers]. Moreover, from a behavioural psychology perspective, market participants are likely to discount the impact of systemic risk since it is so rare relative to other market risks, making the net positive expected value of acting selfishly even higher.” 14 Akerlof, George and Robert Shiller, (2009), Animal Spirits: How Human Psychology Drives the Economy and Why it Matters for Global Capitalism, Princeton: Princeton UP 15 Doyne Farmer and Duncan Foley (2009), The economy needs agent-based modelling, Nature, vol 460, 6 August 16 Francis M. Bator (1958), The Anatomy of Market Failure, Quarterly Journal of Economics, Vol. 72, No. 3 17 ibid. 18 ibid. 19 Markus Brunnermeier, Andrew Crocket, Charles Goodhart, Avinash D. Persaud and Hyun Shin (2009), The Fundamental Principles of Financial Regulation, Geneva Reports on the World Economy 11 (July) 20 Steven L. Schwarcz (2008), Systemic Risk, Duke Law School Legal Studies Paper No. 163

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THE RETHINK

It is the combination of this externality and the expectation of government bailout that gives rise to moral hazard. One strand of proposed interventions to manage systemic risk is built around such externalities. Various measurement methodologies have been proposed: !

CoVaR – conditional value at risk, see Brunnermeier and Pedersen (2009), Adrian and Brunnermeier (2009)

Systemic expected shortfall (its propensity to be undercapitalised when the system as a whole is undercapitalised) / marginal expected shortfall, see Acharya et al. (2010)

Distress interdependence structures, see Segoviano and Goodhart (2009)

Use of game theory approaches to attribute overall systemic risk among firms, see Tarashev (2010)

These methods are all based on historic data and can only be used prospectively to the extent that the underlying variables can be forecasted accurately. In dealing with externalities, Goodhart (2010) advocates avoiding minimum ratios, whether for capital or liquidity on two bases: (i) the capital or liquidity below the minimum level becomes unusable and (ii) correct calibration of the minimum is difficult and “effort and time gets wasted in trying to do so.” Instead, he advocates a “preferably continuous ladder of penalties, whether pecuniary, e.g., in the form of a tax, or nonpecuniary in the form of prohibitions of increasing severity on the freedom of action of an intermediary as its capital, liquidity and margins decrease and its leverage increases.” 2.3 A DEFINITION OF SYSTEMICALLY IMPORTANT FIRMS (AND OTHER ‘THINGS’) Many of the proposed systemic risk control activities require consideration of what constitutes a ‘systemically important firm’; that is, what classes of firm produce externalities? The FSB, IMF and BIS have published a comprehensive working paper21 reviewing what central banks and other systemic risk supervisors consider to be suitable criteria for classification of systemically important firms, as well as systemically important instruments, markets and infrastructure. The key findings of the joint agencies’ paper are sound: that systemically important firms are those firms whose “failure would cause (sic) widespread distress, either as a direct impact or as a trigger for broader contagion.” The same definition was also considered to apply to markets and instruments. Criteria for firms’ systemic importance included: !

Interconnectedness

Leverage

Maturity mismatch

Size

Concentration risk

Correlation of exposures

Role of pension funds in fiscal policy as a potential risk.

Hedge funds were the exception, with interconnectedness, leverage and opacity/ complexity seen as more important factors.

21 Financial Stability Board, International Monetary Fund and Bank for International Settlements (2009), Guidance to Assess the Systemic Importance of Financial Institutions, Markets and Instruments: Initial Considerations — Background Paper Report to the G-20 Finance Ministers and Central bank Governors, October

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

THE RETHINK

And in relation to markets and instruments: !

Size

Interconnectedness

Opacity/complexity

Role in monetary policy

Concentration risk

Rate of change of activity

Robustness of the clearing and settlement process.

Unsurprisingly, systemic risk supervisors’ rankings were changed somewhat by the recent financial crisis. The difficulty with this type of approach is that it assumes that it is possible to determine what a “trigger for broader contagion”22 might be before the event. We consider there are two criteria for systemically important institutions which differ by use: !

Those firms from which accepted modelling approaches require data to track risk in the system or the level of the risk the firm poses to the system (with accepted criteria for modelling approaches defined below); i.e., those which may create an externality

Those firms in which the estimation of the level of the risk the firm poses to the system (based on size or inter-connectedness) exceeds a threshold and, thus, to which a systemic risk (SR) charge is applied (in the form of a capital add-on or other firm-specific capital or other charges).

The same criteria can, by extension, apply to markets, instruments and infrastructure. These very practical bases for assessment of ‘systemically important’ firms or markets, instruments or infrastructure avoid a pre-supposition of what might, under different modelling conditions and assumptions, ultimately be found to be systemically important. They also recognise that understanding the financial system as a complex network may require information on all material firms, including those outside the usual financial services regulatory perimeter.

2.4 WHAT THE FINANCIAL CRISIS TELLS US ABOUT SYSTEMIC RISK The first, clear lesson of the financial crisis was that we were looking for systemic risk in the wrong place. Despite warnings from leading ‘orthodox’ economists in both the US23, the UK and Europe24 that the Basel II framework may create unintended outcomes, there was little or no regulatory attention to firms’ regulatory arbitrages or exploitation of anomalies in the regulatory framework as potential sources of systemic risk. This was clearly a blind spot. Secondly, regulators and supervisors were focused on firm-level risks rather than on systemic risks, focusing on solvency of firms but ignoring the externalities of the firms to the financial system. As Lord Eatwell observed, the cost of externalities ... “... to the economy as a whole is greater than the cost to a firm whose actions are creating the risk. But if regulators focus on risks that are recognised by firms already, and neglect systemic risk, why do we need regulation at all, other than to enforce best practice? ...

22 Steven L. Schwarcz (2008), Systemic Risk, Duke Law School Legal Studies Paper No. 163 23 David Jones (2000), “Emerging Problems with the Basel Capital Accord: Regulatory Capital Arbitrage and Related Issues”, No. 24 , pp 35-58. 24 Jon Danielsson, Paul Embrechts, Charles Goodhart et al. (2001), An academic response to Basel II, LSE Financial Markets Group / ESRC Special Paper Series, May

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“The flaw is that in the face of systemic market failures the market is inefficient. Risk is mispriced, with consequences that are all too evident today.”25 Thirdly, the crisis shows the mainstream economics on which regulators and central bankers relied so heavily for macroeconomic management provided little or no capacity to incorporate perverse behaviour among economic agents or firm failure as a source of risk. Because it could not incorporate strategic behaviour by banks (or ‘gaming’ regulations), or reflect properly the risks emerging in the shadow banking system – off the balance sheets of the regulated banks – mainstream macroeconomics was of limited use in understanding the risk building up in the system. The shadow banking system was largely ignored by central bank analysts whose models could not, and did not, reflect its risks.26 Fourthly, standard macroeconomic modelling did not model feedback in the financial system nor allow for surprises to emerge endogenously from firms’ behaviour and reaction to other agents’ behaviour. The models did not reflect reality. More sophisticated and realistic models are needed. Prior to the emergence of the financial crisis, not only were several countries’ central banks routinely publishing reviews of financial stability, a number were working on the network exposures – interconnectedness of the financial system. Network analysis was underway at Oesterreichische Nationalbank (OeNB), National Bank of Belgium, Deutsche Bundesbank, Banco de México, De Nederlandsche Bank (DNB), Monetary Authority of Singapore and the Swiss National Bank.27 According to UK officials, the best developed of these (outside the UK itself) was at OeNB in Vienna. Beginning in 2002, a team at OeNB launched a series of projects to “develop modern tools for systemic financial stability analysis, off-site banking supervision and supervisory data analysis”.28 The Bank of England (BoE) developed a new model for analysis of financial stability just in time to have it put to the test: it was ‘unveiled’ in the BoE’s Financial Stability Review (FSR) in July 2006, nine months before the crisis began to unfold29. The work underway at the Bank of England30 appears to have been the most advanced supervisory work on systemic risk being undertaken globally. The point has been acknowledged elsewhere by the IMF, FSB and BIS in their joint report to the G20 finance ministers and central bank governors in October 200931. In that sense, the BoE work was considered to be the ‘supervisory state of the art’. The BoE’s July 2007 Financial Stability Review presented two (exogenous) crisis scenarios: a large supply-side shock and a generalised adjustment in asset prices. The BoE working paper introducing the revised modelling approach32 noted “a wide range of potential sources of error and uncertainty associated with these preliminary quantitative impact estimates” including:

25 John Eatwell, ‘Greater transparency’ is the mantra of the ignorant, The Guardian, Friday 19 September 2008 26 Gary Gorton (2009), Slapped in the Face by the Invisible Hand: Banking and the Panic of 2007, Federal Reserve Bank of Atlanta’s 2009 Financial Markets Conference: Financial Innovation and Crisis, May 11-13. 27 International Monetary Fund, Bank for International Settlements, Financial Stability Board (2009), Joint report to G20 finance ministers and central bank governors 28 Michael Boss et al., (2006), Systemic Risk Monitor: a model for systemic risk analysis and stress testing of banking systems, OeNB Financial Stability Report, 11. 29 We have chosen to time the onset of the financial crisis from the failure of New Century Financial Corp which filed for bankruptcy on 2 April 2007 30 Haldane, A., Hall, S., & Pezzini, S.,(2007), A new approach to assessing risks to financial stability, Bank of England Financial Stability Paper no. 2 31 Staff of the International Monetary Fund and the Bank for International Settlements, and the Secretariat of the Financial Stability Board (October 2009), Guidance to Assess the Systemic Importance of Financial Institutions, Markets and Instruments: Initial Considerations Report to the G20 finance ministers and central bank governors. The report states at para 32ff: ‘Countries are increasingly focusing on macro financial linkages in their analysis of systemic relevance, although work in this area remains in its early stages. One leading example is the BoE’s RAMSI, which is being developed to inform its assessment of institution-specific and system-wide vulnerabilities. The analytical foundations of RAMSI draw from the stress testing and the network literature. It takes into account interbank linkages and macro-banking linkages by analyzing three areas of interconnectedness: funding feedbacks, asset fire sales, and a real sector-financial sector feedback loop.’ 32 Haldane et al. (2007)

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Lack of data

Estimation uncertainty around reduced-form model-derived estimates

Behavioural modelling limited by few observations of behaviour at tails of the distribution

Behavioural assumptions that the financial sector would not take measures to adjust to the shocks.

Despite the impediments stated, the BoE paper outlines a framework for a “hybrid suite of models that allow the transmission channels for UK financial system stress to be mapped out more accurately and comprehensively”. Elements of the suite of models include: !

Shocks to the system, either macroeconomic or from liquidity or financial market ‘dislocation’, in turn impacting ... !"Credit and market risk, which impact banks’ balance sheets !"An asset pricing model !"Feedback systems through the asset side (market liquidity risk) or liability side (funding liquidity risk), all of which feed in to:

A network model of UK banks and LCFIs resulting in ...

Loss distributions which impact bank lending, which provides ...

Shock to the systems ... and so on.

The models described would, by 2009, form the BoE’s Risk Assessment Model for Systemic Institutions or ‘RAMSI’33. Unfortunately, a global financial crisis intervened. In 2007, it was not in use and certainly was useless in assessing, and not actually used to assess, the build-up of systemic risk that led to the financial crisis that was about to unfold. However, at the time of the emergence of the financial crisis in 2007, the organisation structures for oversight of stability were effectively in place: !

The tripartite authorities had in place an oversight committee for financial stability, chaired by an official of HM Treasury, which met monthly at ‘deputy’ level.

The BoE saw financial stability as one of its core purposes: “Financial stability entails detecting and reducing threats to the financial system as a whole. Such threats are detected through the bank’s surveillance and market intelligence functions.” (2006 Annual Report). In that same report, the bank claimed to have untaken “a major restructuring of the Financial Stability area coupled with a clarification of its primary purposes”.

The BoE had a deputy governor for financial stability, who chaired a dedicated executive committee, the Financial Stability Board.

The Financial Stability (Executive) Board, formed in 2004, was responsible for identifying key risks and activities to mitigate them, and fed into meetings of the Standing Committee on Financial Stability.

The BoE’s financial stability function was organised into four units focusing on risk assessment, risk reduction and planning for the effective management and resolution of financial crises. This work, and the collection of market intelligence to support it, was overseen by the Financial Stability Board.

33 David Aikman et al. (June 2009), Funding liquidity risk in a quantitative model of systemic stability, Bank of England Working Paper No. 372

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Their findings were being published six-monthly through the Financial Stability Report commencing in November 1996 (which included an article by then-Deputy Governor, Howard Davies).

There was a clear recognition of the difference between firm-level (microprudential) supervision and oversight of stability.

The BoE’s internal Financial Stability Board was addressing a wide range of stability issues and was identifying key drivers of systemic risk in the year preceding the crisis. However, despite having the infrastructure in place, the tripartite authorities collectively, and the BoE separately, failed to act to avert the looming financial crisis. Why? The BoE’s financial stability paper (Haldane et al., 2007) notes: “Unlike with monetary policy, non-supervisory central banks ... have few direct policy levers to achieve their financial stability objectives ... While the allocation of official sector responsibilities in the United Kingdom for maintaining financial stability is clearly set out in the tripartite Memorandum of Understanding between the Bank, FSA and HMT, there is no specific statement about how the stability of the system as a whole is defined and assessed. This issue of defining financial stability has been an active area of debate for some years.” That is, Haldane et al. argued before the event, that !

The BoE had limited policy levers available to it to address the build-up of systemic risk

There was no definition of systemic risk or systemic instability

There was no assessment process in place for systemic instability.

But the BoE personnel were also aware of other analytical limitations present at the time34. These were: 1.

Lack of definition of data requirements for analysis of systemic risk

Gaps in the data understood to be required, notably !

Lack of sectoral data on the composition of UK banks’ overseas exposures

Lack of detailed data on the trading book exposures of UK banks; and

Lack of data on the off-balance sheet exposures of UK banks

Failure to address systemic risk data requirements from first principles

Reliance on data gathered for other – data for monetary, fiscal or prudential policy – purposes

Understanding behaviour in a financial network35

Understanding the nature and extent of interconnectedness between financial firms

Amplification effects of financial instruments with embedded optionality.

34 Haldane et al. (2007) 35 Haldane et al., (2007): An area requiring further quantitative work is the effect of behavioural interactions among participants in a financial network. Defaults by important participants can set in train complex sequences of knock-on effects on other participants. And the optionality embedded in certain financial instruments, such as some derivatives, can amplify the impact of relatively small changes in underlying conditions. These effects can give rise to highly non-linear reactions within the system as a whole. Neither of these effects is adequately captured by the bank’s existing models ...

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Combined, these meant that BoE personnel were aware that the financial system could display “nonlinearity”36 – unexpected behaviour where “even minute changes in the triggering event could lead to large macro differences in the outcome, making it difficult to calculate long-term consequences.”37 If the BoE was the ‘state of the systemic risk supervisory art’, few, if any, other central bank functions were as sophisticated, let alone more so, in their approaches. Put simply, at the beginning of financial crisis, in relation to systemic risk, the relevant central bank personnel in the UK and elsewhere didn’t know what they were looking for, nor did they know how to recognise it when they saw it. They lacked sufficient understanding of the problem of interconnectedness or of how much interconnectedness was too much. The lacked an understanding of – and the modelling techniques for understanding – the behavioural microstructure of financial markets; and they lacked robust data across the markets they needed to analyse. They were facing a global, and globally interconnected, problem of increasingly ‘exuberant’ or ‘over-traded’ markets with data that was, at best, national and was not capable of being used internationally to form a consolidated picture of systemically important firms’ exposures or interconnectedness. To use an aviation metaphor, they were flying in a thunderstorm without the correct instruments38... and the plane crashed.

36 Haldane et al., (2007) 37 Steven L. Schwarcz (2007), Systemic Risk, Duke Law School Faculty Scholarship Series 38 Farmer and Foley (2009) state that the failure of standard econometric and dynamic stochastic general equilibrium models, in addressing the financial crisis, “economic policy makers are basing their decisions on common sense, and on anecdotal analogies to previous crises ... the leaders of the world are flying the economy by the seat of their pants.”

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3. The redesign

“… It is not what we know, but what we do not know, which we must always address, to avoid major failures, catastrophes, and panics.” Richard Feynman

SUMMARY !"For a systemic risk reporting regime to be effective, there needs to be a complete redesign in the way regulators collect and analyse systemic information !"Regulators currently collect vast quantities of information, on a variety of subjects, from thousands of firms, for a variety of purposes, incorporating many elements that will form essential parts of a systemic risk control regime. However, regulators are limited by the methods by which they collect, store and access the data !"There is no ‘one’ solution: multiple models are required. Models capable of representing agents’ diverse behaviours in different market conditions are necessary to be able to correctly view the financial system as complex and chaotic !"Control of systemic risk will require additional information sources to feed multiple and new analytical approaches. Paradoxically, however, the more information applicable to systemic risk collected, the greater the difficulty in interpreting it !"Supplementing these sources with macroprudential elements will require approaches to analysis of connectedness in the financial network that are either not available or not operating today !"Tariff models must be developed that apportion the cost of any solution according to an estimation of each firm’s contribution to systemic risk !"Though many actions can be taken, we won’t know whether they will work against all future forms of financial market instability. This creates problems in calculating the value of these actions when we cannot know their effectiveness !"This is a global problem involving hundreds of players and it cannot be solved without the appropriate accountable governance, mandate and objectives !"Whatever the solution, there needs to be a collaborative approach in establishing global inputs to avoid costs escalating into the billions !"New approaches in governance, frameworks, analysis and data management are needed to incorporate a paradigm shift in the way that the systemic risk problem is viewed and solved for.

3.1 SCOPING THE SOLUTION Policing systemic risk is a matter of creating measures to identify its build-up and prevent it exceeding some threshold level. If it is seen as a more dynamic problem, then the question of controlling systemic risk becomes ‘how to prevent a trigger event from occurring?’ Its control becomes spotting asset bubbles within markets, identifying potentially systemic shocks or ‘trigger events’ and designing measures to deal with them. Rather than improving or understanding the system itself, it becomes a question of defending

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the system against contagion from the excessive risk-taking of interconnected firms (with negative external consequences or ‘externalities’). In establishing systemic risk supervisors, we face decisions about how to allocate resources between the choices in our operating model: the people, the process and governance or the technology and data. Our discussions highlighted the need to make a choice between having an operating model based on ‘computers’ versus ‘eyes and ears’. Of course, given the amount of information required about systemic risk, there is no real possibility of it being tracked informally, with response by the ‘governor’s eyebrows’ alone. Likewise, however, there is also little chance of the subtleties and nuances in the environment being observable by computers without human intervention, and successful intervention without human judgement appears impracticable. For the systemic risk supervisory platform to be successful, we must start with fundamental questions of scope, for example: !

How many systemic risk supervisors will require access to the information?

To what extent is the solution commonly used by different systemic risk supervisors?

How integrated will the systemic risk data be with the existing industry data sources?

Will the platform operate in a centralised or decentralised manner?

How will the performance of the operating model be evaluated against its objectives?

The answers to these scope questions will establish the ‘first principles’ for the operating model objectives and subsequent platform design.

3.2 OBJECTIVES FOR A SYSTEMIC RISK REGIME Effective management of systemic risk contains an epistemological dilemma: you can never know that it is effective; only that it is ineffective. Furthermore, rather like a nuclear deterrent, you build it in the hope that you don’t have to use it in anger. As with MAD and Nuclear Winter, another failure of systemic risk control on the scale of the recent crisis would be beyond the means of governments to bail out, resulting in catastrophic bank failures; it could bankrupt the entire world. Despite that, it is possible to define some key objectives and aspects of a systemic risk control approach that will be essential to its effectiveness. It should: !

Draw on microprudential and macroprudential policy tools to provide information on firm and market systemic risk levels

Provide enough confidence to use to justify actions to take away the punchbowl or charge firms for – or require additional capital provisions relating to – systemic risk (the ‘evidential’ requirement)

Provide data on firm exposures and interconnections that is internationally comparable – international is overly-ambitious in the short term (Danielsson, 2009) – requiring internationally recognised and applied standards for reference (static) data for counterparties, instruments and markets

Represent the interconnectedness of the firm and its impact on the interconnectedness of the market

Provide an indicator, or measure, of whether interconnectedness of firms in the financial network is approaching a tipping point at which interconnectedness becomes a shock amplifier

Reference agents’ actual observed behaviour

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Provide a data set (or the means to establish a data set) to support research into competing, viable approaches to understanding systemic risk

Be sensitive enough to changes in systemic risk levels and the marginal systemic risk impact of firms’ investment decisions to apply within firms’ allocation systems; for example, identify the marginal systemic risk impact of changes in a firm’s maturity transformation profile.

The overall objective of systemic risk control can be viewed as “reducing (sic) the amplitude of financial booms and busts, particularly the externalities that are generated in the boom and bust dynamics.”39 Ultimately, a framework can only be judged to be effective if the systemic risk supervisor has deemed it necessary to intervene to reduce systemic risk and is shown afterwards, through detailed and independent analysis, to have been justified – a ‘true positive’ judgement afterwards to have been true. A false positive will result in suppressing economic activity unnecessarily with a resulting cost in terms of productive economic activity and growth forgone. A false negative will result in a systemic crisis that was not averted where it is, subsequently, considered that effective intervention would have been possible. It is this epistemological problem that makes use of multiple, competing (and possibly contradictory) approaches to judge systemic risk so critical. The relative importance of these cannot easily be determined ex ante. To take the current example: if the financial crisis has cost 5% of GDP in one year (see section 4), suppressing growth by 1% of GDP per annum over five years represents a greater total cost to the economy. There is a real possibility of a false positive costing more than a false negative.

3.3 THE SR CONTROL PARADOX AND ILLUSION OF CONTROL Malcolm Gladwell40 distinguishes between a ‘puzzle’ (complexity) and a ‘mystery’ (uncertainty or ambiguity) and the need for differences in approaches to solving them.41 Evidence of this concept was provided in July, 2010 when, in response to the Financial Crisis Inquiry Commission’s (FCIC) request for information on their mortgage derivatives business, Goldman Sachs provided 2.5 billion pages worth of documentation.42 If printed, it would have required over a thousand lorries to transport the pages. Consequently, the FCIC charged them with wilfully obstructing their work. That their work was obstructed is definitely true, but it also means that anything the FCIC reads about Goldman Sachs’ mortgages derivatives business will necessarily be the summary ... of a summary ... of a summary ... of those 2.5 billion pages. As the quantity of data and the complexity of computing systems to deal with it increase, the view of how they work becomes more opaque; it becomes increasingly difficult for anyone to have an end-to-end view. This creates knowledge gaps between those who create the data infrastructure, create the computing systems, use the computing systems and those who make decisions based on the above.

39 Stephen Morris and Hyun Song Shin (2008), Financial Regulation in a System Context, Brookings Papers on Economic Activity, Fall (Conference Draft). 40 Gladwell, Malcolm, Open Secrets: Enron, intelligence and the perils of too much information, (2007), The New Yorker: http://www.newyorker. com/reporting/2007/01/08/070108fa_fact 41 Gladwell describes the difference thus: “Osama bin Laden’s whereabouts are a puzzle. We can’t find him because we don’t have enough information. The key to the puzzle will probably come from someone close to bin Laden, and until we can find that source bin Laden will remain at large… The problem of what would happen in Iraq after the toppling of Saddam Hussein was, by contrast, a mystery. It wasn’t a question that had a simple, factual answer. Mysteries require judgements and the assessment of uncertainty, and the hard part is not that we have too little information but that we have too much.” 42 Foley, Stephen, Grovelling Goldman says sorry for documents foul-up, (2010), The Independent: http://www.independent.co.uk/news/business/ news/grovelling-goldman-says-sorry-for-documents-foulup-2015109.html

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As the financial system has grown in size and complexity, the number and types of risk within it have grown also. When attempting to maintain financial stability within the system, therefore, it is important to recognise the appearance of new forms of risk as endogenous. It is this adaptive nature of the financial system that forces systemic risk to be considered complex and emergent from the interactions of elements of the complex system. The more information that becomes available, the greater the ‘processing’ challenge is to understand it. Analysing all of the data all of the time is impracticable. Therefore, one has to treat the analysis of systemic risk as a ‘mystery’ (per Gladwell). To extract meaning, the right questions have to be asked in the right way. In more concrete terms, a supervisor has to be mindful in its collection of data that it knows its objectives, what information is required to meet them and that it has the right standards in place to able to analyse correctly the information it collects. Reliance on any single model to provide ‘an answer’ is dangerous but, compounded with poor or incorrect data, the risk of creating ‘Garbage In, Gospel Out’ increases. When so much of today’s information is computer-generated, it becomes increasingly difficult for those who use the information to understand exactly where it comes from and what processes have been applied to ensure its accuracy and quality.43 The problem this creates can be termed the ‘illusion of control’44: the “perception that control is effective whether or not that is really the case.”45 Because the numbers are there, and there are complex models behind them, people believe the numbers. If 2008 can be remembered as “the year stress-testing failed,” as Haldane asserts, there is a real risk that the next crisis will be remembered subsequently as the year the systemic risk models failed. In discussion of the issues with the regulatory community, we noted the existence of a ‘guilty knowledge’ dilemma. The dilemma is this: if, long after a piece of information was missed, it can be proven that the regulator was negligent in its interpretation of that information, it could be found to be at fault. Therefore, the regulator is incentivised to collect information only for purposes that are clearly specified and for which it can establish controls. This dilemma is a strong inhibitor to open discussion about what information is truly required. Without the right standards on data quality in place, there is the real risk that any conclusion reached on the result of the analysis of this data will be fundamentally and unobservably flawed; the ‘control’ achieved by using the results of the model will be an illusion. The adage that “all models are wrong, but some are useful”46 is apposite, just as the stakes in relying on a faulty or misunderstood ‘riskometer’47 are enormous.

3.4 WHY SYSTEMIC RISK CAN’T BE ‘GOOGLED’ The platform for controlling systemic risk will not be anything like the Google search engine. The solution will neither be quick nor easy, but there is a process that can be followed to build it. The industry will need to evaluate a number of potential approaches to solving the systemic risk control paradox. In order to come to consensus on a global approach (or series of global approaches), the objectives will need to be carefully examined and a number of choices made.

43 We are increasingly facing the same situations presented to Charles Babbage, the ‘father of the computer’ when he created his difference engine: “On two occasions I have been asked: “Pray, Mr Babbage, if you put into the machine wrong Figures, will the right answers come out?” ... I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.” 44 Michael Power (2007), Organized Uncertainty: Designing a world of risk management, OUP 45 Richard Anderson, Peter Bonisch and Michael Power, Thinking beyond Turnbull: A guidance paper, forthcoming 46 George Box, (1980), Sampling and Bayes’ Inference in scientific modelling and robustness, Journal of the Royal Statistical Society of Australia, 143, Part 4. 47 Jon Dannielsson (2009), The Myth of the Riskometer, Vox. http://www.voxeu.org/index.php?q=node/2753

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Our review of potential platform types has identified three logical steps which should form the basis of discussion for decision makers in 2011, varying according to the institutional demands of firms and regulators/supervisors respectively: we call these (i) firm heavy; (ii) regulator (or supervisor) heavy; and (ii) regulator light (see section 5.2). Our research highlights significant barriers for any of these platforms which will require a well-thought-through engineering approach that deploys the right people on the right problems at the right time. The financial system, unlike the real economy, has no tangible products that live in warehouses. Its assets, however, do live in a myriad of complex and interconnected information silos across value chains that span the globe. Monitoring systemic risk effectively requires an appreciation of the connections from buy-side to sellside to execution venue to clearing and settlement locations. The information that flows through the value chain is generated for different purposes and in the context of the player in that supply chain. For example, the information collected to protect the financial system from terrorism (commonly referred to as Anti Money Laundering) is collected, validated, stored and indexed differently from the information used to assess the exposures that the same company has across its supply chain (referred to as large exposure management). Access to this data is controlled for good reason. There is a duty of care that investment firms are obligated to fulfil. For example, it is against the law for a bank to advise its potential customer that they are being investigated as a terrorist. In a similar way, it is not possible to acquire information on a company or position in the market without signalling that there may be an issue in the market. In asking market participants for more information on their position with a bank, the systemic risk overseer may create a run on the bank stock and, thus, cause the risk that they were investigating to actually materialise. The good news for systemic risk overseers (SROs) is that much of the information they seek is aggregated today by either supervisors or market participants. Supervisors collect a significant amount of information today. From a commercial perspective, there are hundreds of information providers that do the same. Simply put, a lot more work will be required to collect and analyse the information about the financial system than is implied by those that consider the challenge to be equivalent to typing a few words into a web browser. In a speech in 2009, Haldane spelled out the problem in relation to the information requirements of the failure in September 2008 of investment firm, Lehman Brothers: “understanding the full consequences of Lehman’s failure would have required information on the entire topology of the financial network. This is unrealistic even for the authorities, much less an individual firm. Absent that knowledge, the financial system was seized by network uncertainty. If this informational failure is not easily rectified by the actions of individual firms, there is a case for the authorities attempting to provide that missing informational public good, however difficult that might be in practice”.48 3.5 SO, WHAT NOW? Organisationally, addressing the knowledge problems emerging from the financial crisis will not be achieved simply by reconstituting existing committee structures or by adding to them appointees from outside existing official ranks, who are within existing professional paradigms or from within the existing ‘coherent traditions of economic research’49 (see section 6.6 for a discussion of the paradigm shifts or changes to mind-set that we have identified as necessary). Responding effectively to the crisis will require systemic risk supervisors nationally and globally to develop, implement and maintain a range of new solutions which incorporate the information and analytic insight missing prior to the crisis. This will necessitate: 48 Andrew Haldane, (2009), Why banks failed the stress test, Bank of England, speech to a commercial conference, 13 February 49 to paraphrase Thomas Kuhn (1996), The Structure of Scientific Revolutions, 3 ed., Chicago University Press

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New approaches to governance of global supervisors and to global supervision of internationally systemically important financial institutions

Developing new frameworks to plug some or all of the gaps identified in understanding systemic risk

Different analytic approaches which incorporate feedback systems, agent behaviour and irrationality

Additional data to support analysis of interconnectedness – networks in the financial system and ‘networks of networks’ across particular subsets of banks and asset classes, in addition to interbank borrowing and lending. As Lord May and N. Arinaminpathy50 point out, this means “we need to know more both about interconnections among real banks and about the properties of non-random interactions among big banks and little banks”.

Improved reliability of existing data (i) to increase confidence in analysis and (ii) to allow for internationally standardised data which can, if and when required, be brought together meaningfully for analytical purposes

Clear and clearly accessible data architectures at firm and regulator level to define data for systemic risk analysis and to support audit trails for systemic risk data.

The will to develop these will require a paradigm shift among politicians, central bankers, academic economists, regulators and executives in financial institutions about their roles in the ‘systemic risk knowledge chain’. These will affect the costs of doing business for systemically important firms and require a detailed definition of which firms are, or could be, systemically important. Part of the systemic risk regime is likely to require that systemically important firms be charged directly, or through marginal capital requirements, for their potential spill-overs of risk in to the financial system, i.e., the externalities their leverage creates. These charge-backs or attribution structures are already under development and will result in a relatively increased cost of business for highly interconnected firms.

3.6 REGULATORY FRAMEWORK The following table shows the high-level classification of intervention options. It shows the building blocks of our proposed framework for systemic risk control requirement including both microprudential (firm-level) and macroprudential elements.

50 Robert M. May and Nimalan Arinaminpathy(2009), Systemic risk: the dynamics of model banking systems, Journal of the Royal Society Interface vol 7, October

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Figure 2: Framework for regulatory toolkit Focus

Terminology

Additional coverage required

Firm-level aspects

Microprudential

! !

Micro & macroprudential

! ! !

Macroprudential

! !

Resolution measures

Network aspects

Systemic

! !

! ! !

Economy aspects

Macroeconomic

Development state

Adding to existing firm-level prudential and control rules Enhancements to governance of risk â&#x20AC;&#x201C; per Walker (2009) Liquidity enhancement Prudential capital requirements

Under development or implemented at local and BIS level

Stress testing Reverse stress testing Firm and sector liquidity exercises

Under development or implemented at local and ECB level

Counter-cyclical buffers Instrument or counterparty class risk weights for capital requirements Collateral requirements Prospective cyclical loss provisioning Lending limits / credit controls Reserve policy

Under development or development under consideration

Living wills and data requirements of the special resolution regime Contingent capital measures

Under development

Interconnectedness Capital adjustments for highly interconnected firms Transmission mechanisms Amplification mechanisms Emergence mechanisms

Under discussion at academic level

Linkage of macroeconomic variables to financial system risk !" Fiscal policy !" Monetary policy settings

Extensive commentary emerging academically and at policy level

Source: Interviews, literature review and JWG and Paradigm Risk analysis

3.7 A FRAMEWORK FOR SYSTEMIC RISK CONTROL Systemic risk control will necessitate a better and more aligned understanding of the regulatory models, the criteria for the modelsâ&#x20AC;&#x2122; success and the regulatory data requirement. Types of models The key implication of reviewing model types is that different models (even of the same type) will require different source data (some of which will currently be available, some not) and produce different insights; therefore, different models will solve (or suggest solutions to) different parts of the systemic risk puzzle. All parties we

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spoke to, whether supervisors or academics, expressed profound doubts about the utility of some or all of the approaches currently identified to support systemic risk analysis to the standard necessary for supervisory intervention. Assuming such intervention is to be attempted, it is likely that it will need to be informed by multiple models, the results and insights of which are compared and assessed on an ongoing basis. We refer to this as ‘model pluralism’ or ‘using a plurality of models’ to justify systemic risk supervisory intervention. For the purposes of understanding information requirements of models, we have defined the following types of models:

Figure 3: Classification of systemic risk models Model class

Model groups

Historical approach

Data aggregation models

Models describing networks

Complex systems

Description

Utility

Focus on achieving control of systemic risk through control of firmlevel risk [1] Econometric solutions

Specification of long-form or short-form econometric models for forecasting; can be adapted to examine sector stress

Basis of most current models; usually compiled from publicly available data sets

[2] Failure-based conditional default probabilities

Analyses how the risk of one institution reacts to changes in the risk of other institutions after controlling for common risk factors

Uses market and/or proprietary data to produce correlations in value or default probabilities

[3] Dynamic network interconnectedness models

Interconnectedness with multi-period feedback loops to market (asset side) and funding (liability) behaviour, leverage and liquidity requirements

e.g., BoE RAMSI approach; uses a variety of sources of data including regulatory returns; supports analysis of default probability and domino effects over multiple runs of the models

[4] Complex statistical observation

Identification of patterns and discontinuities within large datasets using advanced statistical techniques

Various types / sources of information; common factors are use of market data to identify and observe ‘hidden’ patterns in the data Emergent behaviour visible

[5] Observation of complex systems

Understanding structural vulnerabilities of the financial system to identify system characteristics such as variation, interaction and selection and the behaviour of system agents

Focuses on observing relationships between players and player behaviour from patterns in existing market data Emergent behaviour observable and describable

[6] Modelling and simulation of complex systems

Definition of behavioural assumptions for economic agents (firms) and building in decision rules to multi-period simulation models

Models assumptions of agents’ behaviour under stress and how agents adapt their behaviour (‘learning rules’) over multiple time periods. Identifies boundary conditions and outcomes Emergent behaviour can be modelled and replicated

Source: Interviews, literature review and JWG and Paradigm Risk analysis

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Criteria for models At the heart of any systemic risk control approach will be the models used to analyse interconnectedness or “monitoring measures for systemic stress” (IMF, 2009). Performance criteria Performance criteria will differ by model and are best defined in each of the proposed approaches in consultation with the systemic risk supervisor. As a starting point, a reasonable approach would be to challenge a model on: !

A standard back-testing basis

Its utility ex post in describing or foretelling or predicting the financial crisis of 2007 and thereafter

Its ability to shed light on concentrations of risk or dynamic patterns of risk assumption, risk shedding or dynamic network characteristics

Its ability to monitor changes in the level of risk in the system

Its ability to explain behaviour emerging endogenously from the system

If a model is unable to demonstrate its utility on one of these criteria, there would need to be an extenuating circumstance for investing in its development. The fundamental purposes of a systemic risk model are to explain crises after the fact, to capture the decision approaches that led to the crisis and to model them under different and subsequent conditions. Evidence Noting that systemic risk involves real costs (as we have recently had emphatically illustrated), reducing it and/or improving its management will impose real costs at three levels: 1.

By reducing the growth and innovation in the economy as ‘the punch-bowl’ is taken away during growth phases of the economic cycle

By reducing the profitability of financial firms by requiring them to hold additional capital to reflect their contribution to SR or by prohibiting them from profitable business opportunities

By allocating the costs of operating the SR supervision system (per the US OFR funding model, for example)

Justifying the imposition of these costs, especially (1) and (2), will require a level of evidence of build-up of systemic risk that is not currently available, given the state of current knowledge and modelling efforts. The confidence levels predictive models achieve with historic data will, therefore, be crucial to their utility and evidential value for decision-making.

3.8 THE INVESTMENT DECISION It is at this point that the discussion has to become the ‘ten pound question’: where do you allocate your money to create the greatest value? This is more complicated than it might appear. Investing or prioritising the entirety of your £10 in creating complex and expensive modelling techniques and computational methods neglects data requirements and standards to fuel those models. We need minimum data requirements and standards to assure the quality of input to the complex models. But we cannot know the data requirements before settling on the analytical models the data will be required to feed; we must anticipate these as well as we can. It is then necessary to decide whether the minimum standards are enough. It might be that a low cost platform with expensive, but high quality, data standards works better and, therefore, has more value than an expensive platform with poor data standards.

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THE RETOOLING

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THE RETOOLING

4. The retooling

“The problems that exist in the world today cannot be solved by the level of thinking that created them.” Attributed to Albert Einstein

SUMMARY !"New and multiple tools are required to create an effective, agile and adaptive monitoring system !"Since the financial crisis, regulators have imposed significant additional information and data requirements on firms – in the UK alone, firms must now provide over 10,000 data items; firms receive no comparative analysis from the regulator in return for all the data they provide !"The additional liquidity, capital and resolution requirements imposed on firms have created considerable additional costs for firms but have made individual firms more resilient to crisis with more control points, e.g., OTC derivatives clearing on exchange. However, conforming to additional regulatory data requirements distracts firms (and supervisors) from paying attention to the risks they are meant to be controlling !"Little has been done to address the control gaps that exist in systemic risk around interconnectedness, transmission and amplification of shocks to the financial system !"Regulators have not developed a regulatory data model which would define their own information requirements for the use of the data that they need. This adds to the difficulty firms face in complying with the requirements and imposes costs throughout the system that could more efficiently be borne at the centre !"Each additional information requirement – of which there are likely to be many more – compounds the problem !"Already, different jurisdictions and regions are adopting different remedies to these problems. This is leading to a disconnected approach and misaligned radars emerging across the EU, the US and AsiaPacific regions !"A critical challenge for supervisors will be to marshal the standards of evidence required to justify costly interventions whether for market-wide action – taking away the punchbowl – or defending firm-level capital add-ons !"As yet, central policymakers have not engaged with the providers of information within firms and commercial data providers to determine what it is feasible to source and the cost of doing so.

4.1 THE RESPONSE TO THE FINANCIAL CRISIS AND ITS EFFECTIVENESS In the wake of the collapse of Lehman Brothers on Monday, 15 September 2008 and the bailout of AIG on the Wednesday, the US Secretary of the Treasury, Hank Paulson, FRB Chairman, Ben Bernanke, SEC Chairman, Christopher Cox and congressional leaders held a dramatic meeting on the Thursday in House Speaker Pelosi’s office. Speaking after the meeting, Paulson described the proposal that emerged as “an approach to deal with

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THE RETOOLING

systemic risk and the stresses in our capital markets.”51 Paulson’s proposal was accepted and, on the Friday, the rescue plan was announced by President George W. Bush at a press conference on the White House lawn. The reaction of financial markets to the announcement was swift. The Dow Jones Industrial index, which had fallen 4.4% on Monday and 4.0% on Wednesday, recovered by 3.9% and 3.3% on Thursday and Friday respectively. A revised form of the Paulson bailout plan was enacted as the Emergency Economic Stabilization Act on October 3, 2008. The original proposal, in expanded form, was put to the House as HR 3997 for a vote on 29 September 2008. In a surprise outcome, it was defeated. On the day, the DJI index lost 6.9%. An amended bill of 451 pages (versus Paulson’s original three-page proposal), which extended the proposal, passed the Senate on 1 October and was sent back to the House for a vote on 3 October. Chastened by both market and public reaction, the House vote passed comfortably. President Bush signed the law within hours of its passage. The USD 700 billion Troubled Asset Relief Program was born. Leaders of the G20 countries met for the first time in Washington on 15 November 2008. These leaders (previously confined to ministers and central bank governors) prepared a plan that, by the time of the London summit, a year later, had become a 92-point action plan. Action on financial stability – including addressing systemic risk – forms an integral part of that plan.

Figure 4: G20 action plan (excerpt) 61. Amend our regulatory systems to ensure authorities are able to identify and take account of macroprudential risks across the financial system including in the case of regulated banks, shadow banks and private pools of capital to limit the build up of systemic risk. 62. Large and complex financial institutions require particularly careful oversight given their systemic importance. 63. We call on the FSB to work with the BIS and international standard setters to develop macroprudential tools and provide a report by autumn 2009. 64. Ensure that national regulators possess the powers for gathering relevant information on all material financial institutions, markets and instruments in order to assess the potential for failure or severe stress to contribute to systemic risk. This will be done in close coordination at international level in order to achieve as much consistency as possible across jurisdictions. Source: G20 action plan

The Troubled Asset Relief Program (TARP), a programme to provide a market for sales by firms of securitised loans held on their balance sheets, forms only part of the US bailout and stimulus programme. So far just over half of that programme’s provision of USD 700 billion has been invested. Similarly, USD 1.5 trillion of the direct rescue provision of the Federal Reserve system has been invested against a commitment of USD 6.4 trillion, and less than half of the stimulus provisions of USD 1.2 trillion committed has been invested (USD 578 billion). In total, USD 3.0 trillion, against a commitment of USD 11.0 trillion, has been invested.52 A recent Bank of England paper put the ‘narrow’ cost in the US, i.e., “the wealth transfer from the government to the banks as a result of the bailout” at USD 100 billion.53 The total cost of bailouts and stimulus in the UK is contested. The same BoE paper estimates the ‘direct’ cost at less than £20 billion or little more than 1% of GDP. If the loss of output is considered, the cost calculated is far higher. If world output is 6.5% lower than in the absence of the crisis, as BoE has estimated, the global loss is equivalent to USD 4 trillion, of which the loss to the UK is £140 billion. As Haldane (2010) notes, some 51 Video of statements following the congressional meeting of 19 September 2010 available at MSNBC, accessed 11 August 2010 52 Data from CNN Money’s bailout tracker at http://money.cnn.com/news/storysupplement/economy/bailouttracker/ 53 Andrew Haldane (2010), The $100 billion question, Bank of England, speech to Institute of Regulation & Risk, Hong Kong, 30 March

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of these losses will persist raising the total cost to between £1.8 trillion and £7.4 trillion. IMF data from April 2010 suggest a global cost of the crisis of $2.3 trillion, revised down from $2.8 trillion in October 2009.54 The same IMF review concludes that risks to global financial stability have eased, but concerns about advanced economy sovereign debts crises “could undermine stability gains and prolong the collapse of credit”. The IMF advocates that economies: 1.

Reduce sovereign vulnerabilities, including through communicating credible medium- term fiscal consolidation plans;

Ensure that the ongoing deleveraging process unfolds smoothly; and

Decisively move forward to complete the regulatory agenda so as to move to a safer, more resilient and dynamic global financial system

Meanwhile, among professional economists, there is debate about the effectiveness of the response and economic stimulus.55 Two economists go so far as to claim that the US government’s response “probably averted what could have been described as The Great Depression 2.0.”56 This view is shared by officials to whom we have spoken in the UK and from other jurisdictions. The view is also widespread among officials that, of the regulatory policy changes and financial market policy changes, additional liquidity, capital and resolution requirements imposed on firms have created considerable additional costs for firms but have made individual firms more resilient to crisis. Initiatives to require risk retention in securitisation and to bring on-market over-the-counter derivatives contracts through central counterparties for clearing derivatives trades have also reduced risk in the system (but have introduced new ones, especially in relation to concentration of trade flow in central counterparties (CCPs).

4.2 THE CHANGING FACE OF SUPERVISION Throughout the world, the regulatory structures of G20 countries were found to be wanting. Many economists and authors claim to have spotted the crisis before the storm broke, suggesting there may have been indicators of the build-up of risk in the financial system that could have been spotted, if the right people had been looking. Unfortunately, either the mandate to look for these indicators, or the power to interpret and act upon them (or both), seems to have been lacking. In an attempt to prevent such ‘underlaps’57 in future, many regions are rearranging the way they supervise the financial system at the highest level: creating and demolishing various regulatory bodies. United Kingdom In the UK, the Government has announced its intention to disband the Financial Services Authority (FSA), bringing an end to the so-called ‘tripartite’ system of governance. Supervisory authority will be split between HM Treasury and the Bank of England, the former being in charge of economic and financial policy and contingency planning, while the latter takes on the roles of setting monetary policy, monitoring risks and vulnerabilities and the normal prudential regulation of financial firms.

54 IMF Global Financial Stability Review, April 2010, International Monetary Fund. 55 See, for example, Bloomberg online, Economists Spar on Effectiveness of U.S. Stimulus Response, August 3, 2010 and Alan S. Blinder and Mark Zandi, (2010), How the Great Recession Was Brought to an End, Moody Analytics, July 28. 56 Blinder and Zandi (2010) 57 Haldane et al (2007)

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In order for the Bank of England to successfully achieve its new mandate, several new committees and authorities have been or will be set up58: !

Financial Policy Committee (FPC). The FPC will have “the tools and the responsibility to look across the economy at the macro issues that may threaten economic and financial stability and take effective action in response”.

Consumer Protection and Markets Authority (CPMA). The CPMA will “regulate the conduct of every authorised financial firm providing services to consumers. It will also be responsible for ensuring the good conduct of business in the UK’s retail and wholesale financial services.”

Prudential Regulation Authority (PRA). The PRA will “carry out the prudential regulation of financial firms, including banks, investment banks, building societies and insurance companies.”

European Union In May 2009, the European Commission (EC) released a communication document, proposing a new supervisory architecture. Following this, in late September, it released the proposal known as the ‘Omnibus’ directive; a collection of amendments to effect the suggested changes. The directive calls for greater powers to lie with European regulators, noting that “national supervisory models have lagged behind the integrated and interconnected reality of European financial markets”. Henceforth, the bodies formerly known as CEBS, CEIOPS and CESR will become the EBA, EIOPA and ESMA, respectively, as defined below. Collectively, these three authorities will make up the European System of Financial Supervisors (ESFS), which will handle the microprudential supervision of the financial system.

Figure 5: European System of Financial Supervisors Committee of European Securities Regulations (CESR)

European Securities and Markets Authorities (ESMA)

Committee of European Banking Supervisors (CEBS)

European Banking Authority (EBA)

Committee of European Insurance and Occupational Pensions Supervisors (CEIOPS)

European Insurance and Occupational Pensions Authority (EIOPA)

Source: European Commission Omnibus Directive

The task of macroprudential oversight, meanwhile, will be handed to the newly-spawned ESRB: !

European Systemic Risk Board (ESRB) “The ESRB’s task should be to monitor and assess systemic risk in normal times for the purpose of mitigating the exposure of the system to the risk of failure of systemic components and enhancing the financial system’s resilience to shocks...in order to accomplish its objectives the ESRB should analyse all the relevant information.”

58 HM Treasury, (2010), A new approach to financial regulation: judgement, focus and stability: http://www.hm-treasury.gov.uk/d/consult_financial_regulation_condoc.pdf

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United States The Dodd-Frank Wall Street Reform and Consumer Protection Act also heavily restructures the way financial regulation will work in the US. The Act encompasses any number of minor adjustments, subtly shifting authority from one federal agency to another, but there are several major changes: three weddings and a funeral, if you will. The Office of Thrift Supervision (OFS) has been abolished and three new agencies have been created: !

Financial Stability Oversight Council (FSOC). The purposes of the Council are: !"To identify risks to the financial stability of the United States that could arise from the material financial distress or failure, or ongoing activities, of large, interconnected bank holding companies or nonbank financial companies, or that could arise outside the financial services marketplace !"To promote market discipline, by eliminating expectations on the part of shareholders, creditors, and counterparties of such companies that the Government will shield them from losses in the event of failure !"To respond to emerging threats to the stability of the United States financial markets system.

Office of Financial Research (OFR). The purpose of the Office is to support the Council in fulfilling the purposes and duties of the Council and to support member agencies, by: !"Collecting data on behalf of the Council, and providing data to the Council and member agencies !"Standardising the types and formats of data reported and collected !"Performing applied research and essential long-term research !"Developing tools for risk measurement and monitoring !"Performing other related services !"Making the results of the activities of the office available to financial regulatory agencies !"Assisting member agencies to determine the types and formats of data authorised by the Act to be collected by member agencies.

Bureau of Consumer Financial Protection. â&#x20AC;&#x153;The Bureau shall seek to implement and, where applicable, enforce federal consumer financial law consistently for the purpose of ensuring that all consumers have access to markets for consumer financial products and services and that markets for consumer financial products and services are fair, transparent, and competitive.â&#x20AC;?59

The post-crisis explosion in regulation has had a definite impact on firms, both in the intended way and also through the huge administrative costs associated with it. The new regulation has totalled almost 100,000 pages of material that compliant firms were, and are still, forced to read. The cost in human hours to digest this is huge and to understand and comply with it, even higher. The strain new regulation puts on firms and on supervisors should not be underestimated. The level of activity and executive focus required to comply with requirements and integrate new systems with existing risk management systems is considerable. This activity has both a direct cost and an opportunity cost: the effort of adapting to changing requirements cannot help but distract from deeper understanding of existing systems and the risk-related information they produce. Certainly, employing the staff required to establish compliance at firm level will limit the resources available to address the underlying issues of risk data structures and architectures, and data quality.

59 Dodd-Frank Act: Wall Street Reform and Consumer Protection Act, (US Pub.L. 111-203)

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4.3 THE FUTURE IS ... BIG, BAD AND GLOBAL With the increasingly global financial system and the pervasive presence of international financial institutions, systemic risk is not something that can be fully dealt with or understood properly at a national or sectoral level. We can see from the recent crisis that sub-prime retail mortgages, originating in US regional markets, had real implications for the rest of the world. Austria, despite a comprehensive supervisory programme with more advanced modelling techniques, was just as affected by the crisis as places without such a programme. While they could account for, and accurately monitor, the firms within their borders, the connections with subsidiaries in Eastern Europe and elsewhere were unmonitored and allowed contagion to spread to Austria as easily as anywhere else. From this we can see that systemic risk is a truly global problem. However, systemic risk is not owned globally. The creation of entities such as the international Financial Stability Board (FSB) and the European Systemic Risk Board (ESRB) is recognition of this problem. These institutions are not yet fully mandated to remediate systemic risk, and may never be. Yet they raise the question of how national supervisors can align themselves under these entities to allow them to be effective both nationally and globally (or regionally). This creates another layer of complexity in designing a national platform: will it be able to communicate its findings accurately to a supranational entity in a way that they can build a picture of the systemâ&#x20AC;&#x2122;s health from a global, or at least, supranational perspective? The brief review of responses in different jurisdictions shows there are differing, and potentially conflicting, approaches emerging, from the US OFR approach at one end to the â&#x20AC;&#x2DC;wait-and-seeâ&#x20AC;&#x2122; approach in Asian markets at the other. The UK which, before the crisis, enjoyed a lead in addressing systemic risk (at least theoretically), will emerge in the middle of the pack. However, for systemic risk control to match the potential market impact of globally operating firms, it must be organised, or at least capable of coordinating (a more realistic objective), globally. Certainly, in their announcements after their meetings in Washington and London, the G20 leaders envisaged greater global coordination. Can it become a reality? If, as seems likely, pressure grows for international regulatory authorities to define approaches for control of systemic risk, firms may face a new capital add-on relating to their interconnectedness and the negative externality it implies for the financial system and to the ultimate risk-holder, the home-juristriction taxpayer. The potential cost of this to firms deemed to be systemically important has, as far as we are aware, yet to be quantified, but it is likely to increase greater than proportionally to balance sheet size, and to represent a material cost to the most interconnected firms. There is a pressing need for further research to define the structure of, and to calibrate, a potential interconnectedness capital charge.

4.4 UNCERTAIN LANDSCAPE FOR REGULATORY CONTROL The global financial markets will have many new sources of risk after the regulatory reform package has been implemented. If supervisors are to spot the next crisis coming, they will have to understand not just the market as-was, but how the market has changed since the regulators restricted the market. Examples of new risks that may appear include: !

New capital rules catalyse instrument concentrations. The changes to the Basel rules should make leaps and bounds toward increasing the resilience of the financial system, but firms will always gravitate towards the greatest return on investment

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THE RETOOLING

Liquidity regime drives up risk from sovereign default. The liquid asset buffers (LAB) being assembled in various parts of the world60 should help to lessen the impact of liquidity shocks but, as with new capital rules, firms may flock towards eligible securities without distinguishing between quality of sovereign instruments.

Concentration of risk at CCPs. Clearing trillions of dollars worth of OTC derivatives contracts centrally means that CCPs will likely become a key systemic risk over the coming years and their capital reserves, liquidity buffers and risk management systems will need to be good enough to withstand the worst of market turbulence.

Regulatory arbitrage drives risk abroad. Many new regulations are localised in the areas hit worst by the crisis. Thus, we may end up with an imbalance of the severity of financial rules across different geographies, giving rise to regulatory arbitrage.

“I’m sorry Dave, I’m afraid I can’t do that.”61 The interplay between the increasing number of algorithms active in the market may produce unexpected effects, all of which could take place in a very short timescale, as demonstrated by the ‘flash crash’.

Regulatory expectations and funds transfer pricing (FTP). The approach of the regulator has been to expect firms to establish internal pricing structures which reflect to desk-level decision-makers appropriate microeconomic incentives. Funds transfer pricing structures that price risk correctly to personnel making marginal business and investment or allocation decisions within the firm are ‘where the rubber hits the road’. In a letter to firms’ treasurers in 2009 relating to liquidity risk, the FSA spelled out the challenge. It seems likely that regulators will adopt a similar approach to systemic risk and the attribution at firm level of the cost of firms’ externalities. Such an approach requires: calculating the total cost of the externality; reflecting the cost in a suitable capital charge; determining a suitable attribution basis for systemic risk between firms to reflect the potential negative externality as a source of contagion. The BIS has already begun to define such an attribution basis.62

Although supervisors must also consider how to prioritise the risks they look at, and thus decide which parts of the system have become less risky, problems with securitisation may have been ‘fixed’ by forcing firms to retain ‘skin-in-the-game’ for structured products. Similarly, credit rating agencies (CRAs) may now have been almost eliminated from the systemic risk equation by new regulation enforcing their transparency and reduce dependence upon them63.

4.5 WHAT ARE THE CONTROL GAPS? In a sense, it is unlikely that supervisors will ever be able to exert ‘control’ over systemic risk in this new landscape, as with the last. A more realistic objective is to be able to observe and monitor a build-up of systemic risk and to direct or incentivise firms to reduce their exposure to the drivers of systemic risk. Our current understanding suggests that principal among these are:

60 FSA PS0916 or CEBS CP28 61 HAL 9000, the sentient supercomputer in 2001: A Space Odyssey, refuses human command 62 Use of game theory approaches to attribute overall systemic risk among firms, see Nikola Tarashev, Claudio Borio and Kostas Tsatsaronis (2010), Attributing systemic risk to individual institutions BIS Working Papers No 308, BIS Monetary and Economic Department 63 CESR’s Guidelines for the implementation of the Central Repository (CEREP): http://www.cesr-eu.org/data/document/10_331.pdf

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A firm’s size makes its failure unsustainable through losses of counterparties resulting in a contagion of failure among those counterparties in a ‘domino effect’

The extent of a firm’s interconnectedness in a highly interconnected financial network is believed to approach a level at which transmission and amplification of even minor shocks is conceivable

The extent of a firm’s participation in common strategies (herding) that may produce the same effect.

Because of those drivers, knowledge requirements for the systemic risk supervisor are: !

The extent and nature of interconnectedness between firms in the financial system

The resilience (and potential decline in resilience beyond some ‘tipping point’) of the financial network or system given the interconnectedness observed

The resilience of individual firms in the interconnected network to shocks to their capital from counterparty or market losses or other external (exogenous) events including their need for funding through interconnected markets

The structure of negative feedback mechanisms, conditions under which feedback can ‘tip’ to positive and the (potentially very rapid) pathways for decay of stability under positive feedback conditions

The plausible transmission paths for shocks from inside (endogenous) or outside (exogenous) firms in the interconnected network, such as through short-term funding markets

Amplification drivers in the firms’ positions over time, such as the impact of asset fire-sales on portfolio valuation relative to capital position.

As if that were not enough, we also need to understand how firms may react over time to the events as they unfold through several ‘iterations’ of responses to the emerging systemic event. The key challenge is to understand how and why firms are connected in the financial network. One major driver is the nesting of counterparty risk in “lengthy and complex intermediation chains”64 as contingent financial instruments are bought, sold and used as collateral along the intermediation chains. Understanding counterparty exposures requires the firm (in the first instance) to be able to form a clear view of its direct or ‘first-order’ counterparty risk and to be able to communicate that to systemic risk supervisors. To be comparable by the SR supervisors between firms and across jurisdictions, the data supporting each firm’s view must, itself, be standardised. This requires, as an essential building block, standardised reference (or ‘static’) data on counterparties, instruments and markets. Without this building block, subsequent analysis will be ‘built on sand’. All these problems require attention to developing and disseminating knowledge on analytical methods and approaches which differ from and, in some cases, contradict many years of ‘received wisdom’ in economics. The control challenge is to ensure the SR supervisor has, or has access to, the relevant knowledge to frame the problem and data requirements and to build, maintain and operate the analytical models required. There may simply not presently be enough of this expertise available.

64 Randall Kroszner (2010) Statement to the FCIC, Washington DC, February 26-27

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Equally critically, moving to the new SR regime, in which interconnectedness and behavioural modelling have an essential role, will require a recognition by firms of potential spill-over effects of their risk assumptions and risk-holding decision-making and risk management performance. Because the impacts of the spill-over are external to the firm, driving this change – this ‘paradigm shift’ – will require regulatory action for firms to price the cost of risk into their capital provisions, through (i) calculation of the total cost to the system of systemic risk and (ii) allocation methodologies relating to their contribution, and marginal contribution, to that systemic risk. Approaches to these challenges are in the very early stages of formalisation. Regulators may wish to consider incentives for firms to collaborate in defining approaches, such as minimal reductions in capital add-ons associated with interconnectedness. Given that the decision infrastructure and authority for intervening in systemic risk were, at least in the UK’s case, present before the financial crisis and the Bank of England was registering its concern over build-up of risks with potential systemic consequences, ultimately this ‘control gap’ may prove the most difficult to bridge.

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THE ANSWER

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

5. The answer

“Faced with the choice between changing one’s mind and proving that there is no need to do so, almost everyone gets busy on the proof.” John Kenneth Galbraith

SUMMARY !"There is no ‘one’ answer. Key knowledge and information gaps must be recognised and bridged if an effective systemic risk supervisory regime is to be implemented !"Changes to the data requirements, data standards and analytic approaches – including incorporating behavioural analysis and feedback systems and analysis of interconnectedness in the financial system – will be central to establishing effective systemic risk control !"Also, because control of systemic risk will require a global discussion, standardised data will need to be available to supervisors to support a global, consolidated view !"Regulators and supervisors should develop and publish for the industry regulatory data models that provide for changes to data requirements, as well as invest in data extraction technologies (e.g., XBRL) using agreed and accepted data standards !"To be successful there must be a paradigm shift in the way policy makers, supervisors, firms (and trade bodies), academics and suppliers interact and view the problem !"Regulators face a ‘guilty knowledge’ dilemma – if they have relevant information, they will be expected to have used it to avert crises. This problem must not hamper development of a significantly re-tooled information solution using 21st century information and analytic technologies !"The supranational bodies must establish and agree design criteria for jurisdictions’ systemic risk control systems and their data requirements.

In this section, we define the following platform design elements: SR performance objectives

JWG & Paradigm Risk

5.2.1

Design options

JWG & Paradigm Risk

5.3.1

Development capabilities

JWG & Paradigm Risk

5.3.2

Standards requirements

Gerald Corrigan (Goldman Sachs) testimony to Senate

5.3.3

Design principles

Dan Tarullo (FRB Governor) testimony to Senate

5.3.4

False assumptions about data

JWG & Paradigm Risk

5.3.5

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5.1 TODAY’S REGULATORY INFORMATION MANAGEMENT LANDSCAPE Under the UK’s tripartite regulatory system, firm level data collection was split between the Financial Services Authority and the Bank of England by mandate as stated under the memorandum of understanding. The FSA’s data requirements are fed into their online regulatory reporting collector GABRIEL65 which is used to collect, validate and store the 50+ data reports from financial institutions. The BoE’s 23 reports66 are collected in a similar manner. Both sets vary in their frequency from monthly to ‘on notification’. In total these reports contain over 1,000 questions with over 10,000 individual data points on the workings of a firm. The data collected encompasses: !

Balance sheets

Sectoral information

Capital adequacy

Securitisation

Compliance with regulation

Systems and controls

Concentration

Techniques questionnaires

Currency information

Pricing data

Funding

Capital expenditure

Interest rate gaps

Profit and loss

Large exposures

Interest rates return

Liquidity

Eligible liabilities

Mismatch

Operational risk

Their level of granularity can vary from ‘yes/no’ answers through to vast tables of daily flows. The post-crisis ‘tsunami’ of new regulatory provisions required the entirety of these reports to be updated and amended in the number of their data requirements and questions. A total of nine extra FSA reports were created in 2009/10, with approximately 900 additional data points needed on a firm’s liquidity information. Six BoE forms were updated for 2010/11, increasing data requirements on profit and loss, interest, liabilities and income. None of this information has been encoded into a widely accepted, non-proprietary, searchable, computerreadable data format. There is no oversight in the tripartite authorities charged with making this information consistent with the appropriate international standards and demonstrated best practices. Although data quality is a top concern, and prominent in recent fines issued to the industry, no systematic supervisory data quality programme exists in the UK. This situation is typical across the current regulatory landscape in other jurisdictions. However, the role of standards authority and the desire to create a ‘common rulebook’ have been delegated to the European Supervisory Agencies. A similar power has been granted to the newly-created US Office of Financial Research which has been tasked with creating data standards.

65 GAthering Better Regulatory Information Electronically: http://www.fsa.gov.uk/pages/Doing/Regulated/Returns/IRR/gabriel/system/drg/index. shtml 66 BoE data requirements: http://www.bankofengland.co.uk/statistics/reporters/defs/defs.htm

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Figure 6: Evolution of supervisory data requirements

Regulatory access to raw data and behavioural assumptions

Dynamic aggregation and linkage

Forecasting, peer comparability

Static stress testing

Existence of a control, static valuation

Source: Interviews and JWG and Paradigm Risk analysis of UK FSA and Bank of England reporting requirements

This is welcome news to the information supply chain as they struggle with mixed message formats, protocols, identifiers and regulatory data requirements. The question for systemic risk oversight is: how much of this data can be reused for the systemic risk platform? Setting the systemic risk operating model objectives From our interviews and a comprehensive review of the literature on systemic risk, the discussion about the potential operating models for control of systemic risk has been limited. However, from our review, we have been able to identify two sets of concurrent conversations that are required to articulate what the systemic risk regime will do and the value that is attributed to it: setting performance targets and cost allocation. Setting performance targets In our discussions with the risk community, we have distilled five key criteria that help define the perimeter of the systemic risk operating model: !

The monitoring objective. What is it that we are attempting to observe at both market-wide and firm level? How much of present activity do we want to be able to observe and what do we aspire to forecast in the future?

The analysis objective. How specific are the events that we are attempting to spot? How many different models are we maintaining? How much data is required? How much history is required?

The reporting objective. What are we attempting to aggregate and how much do we need to disaggregate the numbers? What level of analysis is required? How are we looking to present the information, to whom and where are they located?

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The action objective. How do we expect senior decision makers to use the information and how much will they be responsible for adding to the process?

The proof objective. How long do we expect to be able to ‘reconstitute’ the information that was used to oversee risk at a particular point in time? Should we be able to pass judgements on those that made the decisions?

There is a sliding scale of answers for each of these objectives that range from highly aggregated to very granular. It is probably not the case that all objectives are at the same point in the scale. Setting these objectives needs to be done as a ‘package deal’. It is insufficient to address some and not all.

Figure 7: Potential risk performance objectives

Monitoring

Market prudence

Firm prudence

Forecast

Spot

Spot/requests

High-level trends

Near time event monitoring

Real time

Aggregate

Manipulate

Dashboard

Drill down

Action

Inform

Recommend

Create instrument

Drill down

Proof

Decision tracking

Decision documentation

Linked history

System reconstitution

Analysis

Reporting/MI

Source: Interviews and JWG and Paradigm Risk analysis of micro and macroprudential risk management requirements

Allocating the budget The good news is that there are big efficiency gains to be realised if the objectives are thought through at the start of the initiative. By setting the objectives for a G20 SR control framework up front, the industry will: !

Avoid uncoordinated and splintered decision-making by regulators in each major juristriction and EU Member State

Get better thinking from academics, who will be able to put more ‘wood behind the arrow head’ and develop interdisciplinary approaches

Recoup the cost of scores of investment firm analysts working in an isolated and uncoordinated fashion across regulatory boundaries

Benefit from better and more affordable solutions from infrastructure vendors.

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Key issues include, however: !

Funding approach and transfer of costs of development and operation to participant firms in the financial services industry

The cost-allocation approach adopted (which should, ideally, reflect some measure of firms’ contribution to systemic risk)

Justifying the investment on research feasibility and performance grounds

Practicality of developing data feeds from firms, as well as storage and access rights to the data.

The bad news is that any platform for systemic risk oversight will not come cheaply. The Data Center, which the US is in the process of setting up as a foundation for the OFR’s analysis, has been estimated to cost in excess of $500 million.67 Of course, looked at in the optic of global IT spending, these numbers are small. According to Gartner, worldwide IT spending is likely to reach around $3.4 trillion in 2010, representing a 4.6% increase over 20091. Forrester agrees that global IT spending is likely to increase by more than 8% in 2010 to $1.6 trillion, mainly on the strength of improved hardware and software sales68. There is also a real cost associated with poor quality information as well-intentioned policies, once implemented, may have unintended (and often costly) results. However, this cost frequently escapes the cost/ benefit analysis for the new policies. Additionally, as with any investment in IT – financial services or otherwise – the investment in a systemic risk oversight (SRO) platform will not be a single occurrence. To realise a return, the investment will need to be sustained over a long period of time. Of course, as highlighted in section 3.3, if we do not set objectives, we risk creating ‘Garbage In, Gospel Out’ as computers generate numbers that give decision makers only a partial and/or misleading view of a highly complex landscape. The consequence would be an economy impoverished by higher banking fees and illinformed monetary policy. In its extreme, collection of data and analysis of the financial system could cost tens of billions. This leaves the decision makers with a value proposition to create. The expected value from the investment will need to overcome the costs. As Schwarcz69 has found in his research on systemic risk, the expected value computations can be described as in Figure 8, overleaf. Although perhaps overly simplistic, we do need to come to an understanding of the ‘ballpark costs’ for the SRO platform in order to complete the equation. A key insight of this equation is the need to consider the cost of a ‘false positive’ – restricting economic activity when no ‘systemic meltdown’ would have occurred. Though beyond the scope of this paper to come up with such a number, we believe that this estimate should be generated from a combination of ‘top down’ and ‘bottom up’ approaches. Ultimately, the models will rely upon information that is local to a jurisdiction, so the estimates will be most accurate if they take into account the current state of play in each jurisdiction, rather than sample the players involved. At a regional level, certain costs will be borne for the integration of information. 67 Wall Street Journal, (2010), How a Street Watchdog Got its Bite: http://online.wsj.com/article/SB10001424052748704285104575492182195 397138.html?mod=WSJEUROPE_newsreel_business “It ultimately could have an annual budget of $500 million, and cost $500 million to get up and running, according to a person familiar with the office, and could take as long as a decade to fully establish.” 68 Gartner, ITC Spending to Grow 4.6 Percent, http://www.ictmag.info/politics/it-spending-in-2010-to-grow-4-6-percent-gartner/ 69 Stanley A. Star Professor of Law & Business, Duke University School of Law; Founding/Co-Academic Director, Duke Global Capital Markets Center. The author testified before the U.S. House of Representatives Committee on Financial Services on October 2, 2007 regarding this article’s research and recommendations

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Figure 8: Expected value computations Expected value (without regulation)

likelihood of systemic meltdown without regulation

cost of systemic meltdown

Expected value (with regulation)

likelihood of avoiding systemic meltdown without regulation

cost of having avoided systemic meltdown

likelihood of systemic meltdown with regulation

cost of systemic meltdown

cost of having avoided systemic meltdown

+ %

likelihood of avoiding systemic meltdown with regulation +

cost of regulation

Source: adapted from Schwarcz (2008)

Near misses In the same way, ‘near misses’ or events that could have transformed into a crisis (but didn’t) should not necessarily be interpreted as signs that the controls are working. As lessons from other high-risk industries indicate,70 detailed analysis of near misses is an invaluable source of knowledge about the behaviour of the system being examined. For this reason, any financial data repository or repositories to support systemic risk analysis should allow for deep-drill analyses of near misses. Examples71 of near misses include: !

Hedges that did not work as intended

Significant losses in single product lines that did not result in firm failure

A default that may have occurred had external measures (including drawing on a parent company’s capital reserves) not been taken.

Signalling and security Other possible risks involved in a supervisory platform are around the security with which it holds the data it collects. In this age of increasing sophistication of internet crime and identity theft, with threats such as botnets72 and the ever-increasing complexity and number of viruses, any system collecting firm-level proprietary, or potentially sensitive, data on a large scale is a target for criminal, corporate or even national espionage or sabotage. An even more dangerous effect of considering the implementation of a systemic risk regime is the question of what you can do when you spot a crisis forming. If there is a potential crisis in the making, how do you tell people that it is so without alarming them? The risk is that ‘signalling’ supervisory concerns about an asset bubble ends up triggering the very event you were hoping to avoid. ‘Bank runs’ or ‘funding runs’ are obvious concerns. The question then becomes, not just ‘which tool to use?’, but rather ‘how do I use it?’

70 World Economic Forum / Boston Consulting Group (2010), Rethinking Risk Management in Financial Services: Practices from other domains, April, WEF 71 Internal Briefing note from World Economic Forum, provided to the authors 72 Fildes, Jonathan, Bank Scam targets 100,000 people, (2010), BBC: http://www.bbc.co.uk/news/technology-10865568

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5.2 DESIGNING THE PLATFORM During our review, important design assumptions have been made in the US. The depth of thinking about the platform is limited globally, but opinions are starting to emerge. In large part, these opinions are fuelled by the gap analyses that systemically important firms are performing as they look at the capabilities they require to clear the new risk management hurdles set by the G20. This section examines the three platform design options and the capabilities required across them before turning to the need for comprehensive specifications. Platform design options As we have described above, the performance and cost requirements will, in large part, determine the type of platform that is required. But from an engineering perspective, we have choices to make about how we meet the objective. In their systemic risk information study, Deloitte and SIFMA have identified eight approaches to obtaining information.73 These approaches differ in the way that they assign accountability for the management of the information.

Figure 9: Platform options

Current data requirements

SRO platform options

Valuation

Earnings

Market liquidity

Model complexity Examine sector stress

Bilateral reactions to changes in risk in firms

Funding liquidity

Operations

Systems & controls

Supervisory data dashboard e.g. Gabriel

Market data

CRA info?

Mapping behaviours between agents

Regulatory light Spot patterns and discontinuities between firms

Sensitivities

Data elements ! Linkage between counterparties ! Linkage between leverage/liquidity ratios

Systemic risk spreadsheet Firm heavy

Data gap

! Transactions by firms or market ! Interconnectedness of supply chain ! Aggregate leverage by sector ! Liquidity by asset class/firm type ! Behavioural assumptions ! Transaction volumes by instruments/ underlying

Systemic risk data hub Regulatory heavy

Understanding structural vulnerabilities

Source: Interviews and JWG and Paradigm Risk analysis of systemic risk information requirements and infrastructure options

73 Deloitte & Securities Industry and Financial Markets Association (SIFMA), (2010), Systemic Risk Information Study, July

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The analysis of these options shows important distinctions in the way information is managed: !

Firm heavy. It would be possible to create a very light core of high-level information at the centre and leave the detailed data in the context that it was created. Systemic risks would be spotted by regulators asking firms to stress their models and respond to the regulator who would attempt to aggregate the results.

Regulatory light. A regulator generates templates for reporting on key products, counterparties and markets, and analyses the aggregated data.

Regulatory heavy. Through either industry run or regulator-owned repositories, firms, market participants, regulators and service providers have their information stored in a place that gives the SRO access to granular data.

As these options show, the key questions are “who owns the data?” and “how much do they own?” The answers will determine the type of solution that the SRO requires. Figure 9 illustrates the differences in these platform options. However, before deciding what operating model is required, it would be prudent to specify the capabilities that SROs need to work with the systemic risk data. We examine these capabilities in the next section. Risk management capabilities The control platform has to manage the transformation of data across five big steps.

Figure 10: Workable risk data?

Governance & control

Quality & proof Apply & observe

Analyse & interpret

Aquire & aggredate

Record & classify

Source: Interviews and JWG and Paradigm Risk analysis of micro and macro regulatory risk management objectives

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Record and classify. Whatever risk data is collected, the platform has to be able to maintain the provenance of the information (e.g., Firm A’s reported view of its funding concentration in wholesale securities to Firm B)

Acquire and aggregate. The SRO will need to manipulate the data it acquires (e.g., the report by Firm A of its open positions to Firm B and the same report by Firm C, etc.) to bring the information together (and pull it apart) in different ways (e.g., the total market exposure to Firm B)

Analyse and interpret. Decisions will need to be made based on the information at a point in time and the data used for those judgements will need to be accessible (e.g., Firm B is holding an unacceptable level of risk in a particular market or instrument)

Apply and observe. The judgements will need to be recorded and tracked for their efficacy and accuracy (e.g., Firm B was asked to wind down its exposure and the resulting market impact is judged to be ‘good’)

Governance, control and quality. Across all four above, define the management objectives for the information, monitor the quality with which those objectives are being fulfilled and be able to prove that the data is being managed according to agreed standards. (e.g., did the systemic risk supervisor’s management get the right information in the right time and make the appropriate judgement?)

Our research has identified a mix of technical, data and process issues for each of these capabilities. Record and classify There are many challenges in obtaining the data. The first is existence: behavioural data required by systemic risk models may not normally be collated in electronic form (e.g., behavioural data for depositors or non-marketable assets). Other retrieval issues include information or data being buried in contracts or stored in spreadsheets. But what source data is required for systemic risk? There are many different types of information required for different purposes in the financial system. For example, in the case of customers, their information may be required for the purposes of anti money laundering, protecting their rights (conduct of business), guaranteeing their deposits or controlling the interconnectedness risk of the supply chain. The information required for these purposes is different and the identifiers used to construct a holistic view are often not present in datasets that cross silos. As discussed in section 3.3, our analysis of the UK’s supervisory data requirements revealed thousands of data items in scores of different files that are currently being collected by the supervisors. The information required historically was for the purpose of supervising a firm’s view of its own position. Hence, valuations, earnings and systems and controls were paramount. Looking at the more recently added data feeds, it struck us that there has been an important shift in the types of information that the regulator is asking for. Compare, for example, the 900 items74 required for liquidity risk with the two dozen items required for single customer view reporting75. The data required by regulators is becoming more granular and it relies on understanding interconnections in the firms’ value chain. Another jump can be observed when looking at the requirements for ‘evergreen’ business information packs76 or the documentation for ‘reverse’ stress77 tests that push the investment firm to the point of failure and beyond. There is a worrying assumption that a ‘Googleable’ information set can be maintained and worked 74 JWG Research: ‘Liquidity Risk: A dummies guide’ http://www.jwg-it.eu/library.php?typeId=6 75 JWG Research: ‘Getting value from a single customer view’ http://www.jwg-it.eu/library.php?typeId=10 76 HM Treasury, (2009), Special Resolution regime: http://www.hm-treasury.gov.uk/d/consult_srr_fsma_regs2009_pu820.pdf 77 FSA, (2009), PS09/20: Stress and Scenario Testing: http://www.fsa.gov.uk/pubs/policy/ps09_20.pdf

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with for new and obscure purposes. Perhaps this is what Gerald Corrigan, Chairman of Goldman Sachs Bank USA, the bank’s holding company, was referring to in his identical testimony to US and UK lawmakers when he discussed the need for standards78, as illustrated in Figure 11. The further we get from the original source of the information, the greater the care we need to take in how it is recorded, classified and used. Figure 11: What this means for standards The official community must work with institutions to ensure they have systems and procedures to provide: !" Comprehensive !" Complete !" Accurate

and consistent valuations

and comprehensive liquidity information

!" Fully-integrated !" Legal

data on all counterparty exposures

risk management frameworks

agreements and transaction documents in organised, accessible forms

!" Comprehensive

information on positions with exchanges, clearers, custodian and others

Source: Excerpt from the testimony of E. Gerald Corrigan (2010) before the United States Senate Committee on Banking, Housing, and Urban Affairs

Acquire and aggregate There is a phenomenal number of ‘moving parts’ involved in the generation of the data required by systemic risk supervisors. With thousands of applications and spreadsheets, hundreds of thousands of databases and exabytes of storage, the chances that a change to an identifier in the production environment on Saturday morning will result in emergency phone calls being made on Monday are considerable. With every change in requirement, the integrity, accuracy and timeliness of the data must be tested and reconciled if the regulatory systems and controls are to comply. Once these challenges are surmounted, the next set – to normalise, validate, enrich and derive any information which might be missing – need tackling. The larger the jurisdiction, the more painful the headaches can be. For starters, the sheer data quantities can be massive with the number of cash movements in complex businesses easily reaching millions each day. Throwing more boxes, chips and wires at the problem can help, but batch windows are already crowded and, in most large institutions, they are difficult to extend. Finally, more technical issues must be overcome, like the batch window timing for obtaining ‘daily’ data which follows the sun or the sheer volume of millions of cash flows and their associated processing issues. Even with the processing issues under control, there remains a very large set of problems around validation. If a four-hour job fails three hours into the batch window, there are some important decisions to be made. What is the materiality of the missing 25% of the processing? How long will it take to rerun? Can the partial data processed so far be used in the morning? How will the users know if it is reliable? Whatever the scope of the platform, systemic risk supervisors need to have a data repository capable of handling significant volumes and with extensive connectivity to the source systems. The extent and diversity of connectivity requirements present a significant control and reconciliation challenge. Perhaps more importantly, the newer data required are being used for the purpose of comparing firms’ strategies and, in the case of stress testing, starting to examine the mapping of behaviours between agents. In summary, the data collection requirement is moving up a sharp slope as illustrated in Figure 6, on page 37.

78 Testimony of E. Gerald Corrigan Before the United States Senate Committee on Banking, Housing, and Urban Affairs, (2010)

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The future of systemic risk could give rise to a need for understanding the reactions of agents to particular events. This would require dynamic interconnectedness modelling. Where will this need for more systemic information end? To address these types of challenges, Federal Reserve Board Governor Tarullo has suggested principles for the collection of the new information relating to systemic risk. Figure 12: The principles for developing a new system !" Priorities !" Data

should be driven by the regulatory mission

collection is user-driven

!" Greater

standardisation is required

!" Data

should enable better firm risk management and foster market discipline

!" Data

collection should be nimble, flexible and statistically coherent

!" Results !" The

should be shared with regulators and the market

efforts must be international

Source: Daniel Tarullo (2010), Member of the Board of Governors of the Federal Reserve System, testimony before US Senate Subcommittee, 12 February 2010

Analyse and interpret The systemic risk supervisors, like firms’ chief risk officers, treasury and, sometimes, finance functions in large banks will be responsible for a Herculean aggregation in and across legal jurisdictions and markets. Doing this well requires having the resources to deliver correct and accurate information in consolidated formats in a controlled manner. In order to oversee systemic risk, we need to assemble the appropriate ‘data assets’, ensure they are of high quality and monitor them on a regular basis in order to have a transparent financial system. The data should account for multiple levels of identification of the same ‘physical thing’ in our financial system. JWG’s previous work on identifiers revealed ten regulatory identification requirements for customers alone79. Instruments have a similar level of complexity, depending on the regulatory lens used to observe them. In summary, the industry is beginning to recognise that, for a variety of reasons, it requires unique and meaningful (or ‘rich’) customer identifiers; put simply, ‘customer A’ needs to be recognised as ‘customer A’ and ‘instrument B’ needs to be identified as ‘instrument B’, regardless of firm-specific nomenclatures or the role of that legal entity in the financial services transaction. However, our research has revealed five fundamental misunderstandings inherent in many regulatory data strategies that prevent data from being aggregated. These false assumptions are that: !

Firms can consistently link information about counterparties across business lines, products, geographies, time periods

The context of the interaction is readily identifiable

Data is accurate and readily available to both firms and their regulators

Standards exist for the information used by the regulators

There are no conflicts of law, banking secrecy or issues of data protection.

These are serious hurdles to be overcome across the infrastructure if we are to analyse the rivers of financial information. 79 JWG research: http://www.jwg-it.eu/pressRelease.php?idnum=79

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Apply and observe The requirements for market-wide and institution-specific risk analyses are challenging. Data must be able to allow market positions to be understood at a moment in time, forecasted based on a set of assumptions, stress tested, reported to management and, ultimately, discussed with politicians. If the analysis is required at an atomic, detailed level, then the risk owner should be able to drill back through that data at the behest of the supervisor with the click of a button. The further up in the organisation the query goes, the more distilled the information needs to be. However, for every request that is made, a different viewpoint will exist depending on the individual exposures, market, counterparty or instrument being questioned. Simply put, large volumes of information need to be put in context and analysed across multiple dimensions in the timeframe in which they are required. It is extremely difficult to imagine a systemic risk supervisor gluing information together from spreadsheets, emails and architectures built for static and slow-moving accounting questions. As they continue to get serious about building capabilities to meet all oversight requirements, supervisors will need to rethink how their infrastructures tag the transactional data in their core processing systems and display it in an appropriate manner. One can conclude that supervisors are at a crossroads where they need to assess whether their current infrastructures are fit for purpose or whether they need to implement new approaches to controlling their enterprise information. The key would appear to be getting the right balance of resources to meet an aligned set of objectives for the control framework. Figure 13 summarises the impact on the data requirement for systemic risk.

Figure 13: How comprehensive are the systemic data needs?

Observation of complex systems

Complex statistical observation

Understanding of structural vulnerabilities to the system

Identification of patterns and discontinuities between firm behaviours

Mapping behaviours between agents Dynamic network interconnectedness models

Failure-based conditional default probabilities

Bilateral reactions to changes in risk in firms

Operating model requirements? Size of data gap?

Examine sector stress Econometric solutions

Source: Interviews and JWG and Paradigm Risk analysis of analytical capabilities required by systemic risk modelling requirements

It appears likely that the greater the analytical sophistication, the greater the utility of centralising data capture and storage; however, this is by no means certain. But we can identify trade-offs, between: !

Ease of implementation â&#x20AC;&#x201C; firm heavy will be simplest to implement for the supervisor

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Cost to the firm – which is not predictable; greater reliance on firm reporting is likely to be more expensive for firms than reporting data centrally, but this depends on the nature and periodicity of requirements. The greater trade-off is likely to be inter-temporal: greater investment required now versus on-going cost of data manipulation and submission over time

Flexibility for the supervisor to apply data sourced from firms across new modelling requirements

Requirement for the supervisor to invest in defining a regulatory data architecture and data extraction and reporting technologies (such as XBRL)

Clearly, these are important decisions to get right. To make these trade-offs, and to establish the requirements for the four capabilities listed above (record and classify, etc), we need a formal blueprint and specification that establishes ‘what a good systemic risk platform looks like’. Governance, control and quality The strategic risk supervisory platform requirements will be far from static. As we discover the ‘unknown unknowns’ of systemic risk management, the industry will need to evaluate the performance of the platform and improve it. As JWG’s – and other – research into data quality has shown80, there are significant gaps in the industry’s data quality levels within the systemically important institutions and their supervisors. In many instances, reference data used internally within firms follows different formats with limited commonality in fields between vendor, regulator and firm. To support comparability between firms, we need standardised reference data. To illustrate the problem: if firm A refers to its counterparties with acronyms and the firm B refers to theirs with full company names, the counterparty exposure cannot be consolidated or compared without considerable manual intervention or ‘scrubbing’. Figure 14: Example data anomalies Qantas Airways Ltd. ID

Trading address Active

Address 1

Open F

Address 3

203 Coward Mascot, Street NSW 2020

Appointed Quantas representative house

Address 2

City

State

Mascot

401–403 King Street

Country Australia

London

Level 9, Building A, Qantas Centre, 203 Coward Street

Post code 2020

Entity type UP ID Other corporate

UP name Qantas Airways Ltd.

UP reg country Australia

W6 9NJ

Mascot

2020

ING Bank N.V. ID

Trading address

Address 1

Address 2

Address 3

City

Active

Amstel1081 KL veenseweg Amsterdam 500

Amsterdam

EEA authorised

60 London Wall

London

Open

Amstelveenseweg 500

Amsterdam

■ Same

■ Different

■ Blank

V=vendor

R= regulator

State

F=firm

Source: JWG analysis of customer data management data quality survey 2010 80 JWG research: http://www.jwg-it.eu/pressRelease.php?idnum=75

Country

Post code

Netherlands 1081

EC2M 5TQ NL

1081

Entity type UP ID Commercial & Investment Banks

UP name ING Group NV

UP reg country Netherlands

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To take an example from recent research by JWG comparing reference data across a range of investment firms and vendors against regulatory data, Figure 14 illustrates reference data for two entities (Qantas Airways and ING Bank NV) across three anonymised entities – a vendor, a regulator and an investment firm. The differences in data in each field illustrate the problem of comparability. This, in conjunction other issues covered in this section, necessitates that the systemic risk supervisory platform have a strong quality control programme with clear indicators for performance, gaps and improvement targets. As systemically important firms have learnt in managing the latest crisis, the systemic risk supervisory platform objectives, measures and targets will evolve as we learn what works, and what doesn’t. Linkage between senior decision makers and the detailed information management targets must be closely supervised. There is a chain of dependencies between definition of the systemic risk problem and specification of solutions; this is illustrated in Figure 15. The objectives set by policy makers may be the ideal way of solving the problem in theory; however, the practical limitations – the constraints – are not always apparent at the highest level. Without a clear understanding of the constraints at all levels of implementation, ‘policy’ will not be implemented as designed and constraints (such as comparability of counterparty reference data) will define what is possible. Although somewhat simplified in the figure below, this underlines the need for an end-to-end view of the problem and emphasises the utility of a regulatory data architecture. If investment firms’ data architects are not brought into the discussion at objectives level, ‘the horse will have bolted’ on developing and implementing reference data standards; this will limit inter-firm comparability and inhibit formation of an accurate picture of network interconnectedness. Figure 15 illustrates the cascade of elements necessary for engineering an effective systemic risk control solution.

Figure 15: Systemic risk control engineering

! For what purpose should a SRR regime be put in place?

Objectives

! Who will be in control and accountable?

Governance

! What tools will be available to a Systemic Risk Supervisor?

Toolkit/models

! What do you measure? When is it necessary to use those tools?

Measures

The examination of the part requires an understanding of the whole

Data requirements

Operating model

! What quantity of information is necessary? ! What standards need to be in place? Are they implementable?

Source: JWG analysis of the dependencies for systemic risk data control

Those that are responsible for the maintenance of the platform will want to have a firm control of the ‘design authority’ that governs how the platform works.

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The regulatory data architecture The huge number of additional data points required by regulators since the financial crisis highlight a significant problem: that the regulator has not established any regulatory data architecture and cannot, therefore, articulate efficiently its data requirements from regulated firms. What is a regulatory data architecture? A regulatory data architecture is (or would be) a model of the data structures required to support regulatory and supervisory analysis at firm and sector level. In the words of one interviewee from our study, it would be a “meta layer of information about the financial system”. The regulatory data architecture would define the types of information and data that regulators and supervisors need to know about regulated firms. An example from JWG is the ‘KNOW YOUR ...’ framework which defines high-level data structures for regulatory data management ! ! ! ! ! !

Know your products (KYP) Know your customer (KYC) Know your deals (KYD) Know your reports (KYR) Know your firm (KYF) Know your exposure (KYE)81

Figure 16 shows an example of the regulatory mapping required to create the data architecture.

Figure 16: FS operating model impact assessment – Q2 2010

2010

Capital requirements directive (CRD) MiFID Review IASB Exposure Draft on Financial FSA PS09/20 Stress and scenario Instruments: Classification and testing Measurement AIFMD CEBS CP28 Liquidity Buffers and Survival Periods Wall street reform and consumer protection Act FSA Strengthening liquidity CESRPS09/16 CP 09-618 Classification and standards Identification of OTC Derivative Instruments for Transaction Reporting EMIL and OTC Derivatives

2008

2009

CEBS CP27 Hybrid Capital Instruments

MAD Restoring American financial stability Act

FSA PS09/18 FS Compensation Scheme: SCV

PS 09/13 Changes to the Rules for Approved Persons

CEBS CP28 Liquidity Buffers and Survival Proposed Interagency Guidance – Periods Funding and Liquidity Risk Management JCFC 09-10 Financial Conglomerates Directive CP09/15 Extension of the Short Selling Disclosure Obligation IOSCO Principles for Periodic Disclosure FSA CP09/30 Capital by Listed Entities planning buffers CEBS CP27 Hybrid Capital Instruments

CESR OTC Derivatives IDs and CP 09/13 Liquidity Reporting FSA CP09/29 Strengthening capitalClassification standards 3 CP09/08 Distribution CP09/08 Distribution of Retail IASB Expected Cash Flow Approach of Retail Investments: Investments: Delivering the RDR Delivering the RDR PS 09/11 FS Compensation BIS Stock Taking on the Scheme Reform Use of Credit Ratings Carbon Reduction CEBS CP26 Large Exposures Commitment IOSCO Disclosure Principles for IOSCO Disclosure Principles for Public Public Offerings and Listings Offerings and Listings of ABSs CESR C3 Proposal for a Pan-European Short of ABSs Selling Disclosure RegimeFSF Principles for Sound CEBS CP26 Large Exposures FSF Addressing Procyclicality Compensation Practice BIS Revisions to Basel II in the Financial System Market Risk Framework CP09/03 Compensation CP09/02 Judgements Scheme Reform CP09/03 Compensation on Judgements BIS Due Diligence and BIS Guidelines for ComputingScheme Reform Transparency Regarding Capital for Incremental Risk in IASB Exposure Drafts, DP Carbon Reduction Cover Payment Messages... the Trading Book Commitment

Know your products Know your customer Know your deals

Know your reports

Know your firm

Source: JWG analysis of approximately 75,000 pages of regulatory requirement documents between Q108 and Q210 81 For a current picture incorporating KYE, contact JWG or access at www.jwg-it.eu

New linkages !"Accounting !"Reporting !"Trading !"Clearing !"Settlement !"Customers !"Products

UK EU US

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THE ANSWER

Key elements of the regulatory data architecture would include: !

Data management standards

Data quality standards

Reference data standards

Strategic data mining functionality

Online analytical processing requirements for data

Standards for data governance and change control over the regulatory data architecture

Approaches to data architectures are increasingly standardised around warehouse meta-models, common object facilities and meta-data interchange specifications. Many of these can be standardised to support the hundreds of firms that supply data to the regulator. Already, in Europe, there has been considerable progress on defining standardised reporting data from firms to comply with Basel II requirements: the Common Reporting Framework (or COREP) is an example of this. The Federal Deposit and Insurance Corporation (FDIC) also uses XBRL-based reporting. In the UK, HMRC has defined an XBRL taxonomy for filing tax returns that will come into effect in 2011. XBRL permits tagging of reported data to enable it to be exchanged efficiently between systems. The data architecture phase of system planning would force the regulator/supervisor to specify and delineate both incoming information flows and uses of data; that is, it would link the data supplied to its analytical purpose and eliminate (or substantially reduce) duplication. It would enable the regulator/supervisor to comprehensively identify their information and analytical requirements as well as to define information requirements and data standards for new asset and liability classes, and products and contingent assets and liabilities, across all classes of risk. Equally importantly, it would offer predictability for firms developing and implementing information systems and new products to understand and anticipate the regulatory expectations for reporting and data quality. By improving the discipline of regulatory reporting and eliminating duplication design protocols across the sector, it would free up IT and general management time and resources to focus on improving the firmâ&#x20AC;&#x2122;s internal reporting for and management of risk. By establishing a process for consultation with the industry around changes to the data architecture, it would also support firmsâ&#x20AC;&#x2122; chief information officers to anticipate information requirements and improve the discipline of their development and implementation within firms, reducing error and improving the quality of data internally and supplied externally. Why is it necessary now? The financial crisis has highlighted the need for high-quality data on stocks, flows and contingent claims in the financial sector. Failing to respond to this need, or responding ineffectively, risks a recurrence of the system-level events of 2007 and 2008. Responding without a clear information meta-structure will be almost impossible. The more efficiently and accurately data requirements can be communicated to firms, and data can be extracted from firms and applied to diverse analytical models within the regulator, supervisor and modelling agents (such as relevant research centres and academic institutions), the more likely it is that we can in the future avoid a repeat of the financial crisis and anticipate and avoid similar events with other, as-yet-unknown causes. If there is to be a plurality of modelling approaches encouraged (as we strongly advocate), researchers and analysts need to be able to understand both current information availability and the process (and therefore cost) for generating new source data from the sector. This will only be possible with a greatly improved data meta-structure.

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THE ANSWER

What would it cost? A lot! But the total cost of ownership of industry data should reduce dramatically as a result. There would be material benefits to the regulator and the costs are already borne (many times over) by the sector through lack of planning and the cost of responses to ad hoc requests for information from the regulator. Perhaps the largest cost is due to the poor organisation and utility of data currently supplied for systemic and firm-level supervision. What would be the first step? Defining what is there now â&#x20AC;&#x201C; comprising (i) a comprehensive, sector-wide data inventory and (ii) a classification system for the data that is compatible with existing regulatory structures (without limiting new structures). This should be addressed as a matter of considerable priority. The regulator/supervisor needs to make a substantial, and very long overdue, investment in the discipline of its data governance and data management. Without such investment, defence against subsequent system-level events will be considerably more difficult to conceive, specify and implement.

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THE ROADMAP

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

6. The roadmap

SUMMARY !"To manage the risks of development of a platform for systemic risk supervision, objectives and target operating models need to be defined and agreed !"We have developed a 10-point roadmap checklist for implementation of systemic risk oversight !"Effective implementation of a systemic risk solution offers material opportunity for efficiency gains in regulatory data management but faces inevitable development risks !"Justifying investment and analysing benefits and costs will require a ‘ballpark’ budget. But estimation of a benefit is problematic !"Supranational organisations will need to specify objectives for each jurisdiction’s supervisors for monitoring, analysis, reporting, decision-making and action and standards of evidence or proof for intervention !"Appropriate bodies need to be made accountable for delivering an implementation roadmap !"We have identified three design options with differing levels of regulatory and firm-level commitment required and identified four technical/data capabilities required !"We have identified seven-plus ‘Blueprint’ design committees that will be required to specify the operating model for systemic risk supervision !"Governance and control structures will need to reflect the international coordination of responses required to avert or respond to build-ups of interconnectedness and other forms of systemic risk and to crises !"Supervisors must specify information requirements in a form that supports international comparison of data at entity level and that minimises the long-term costs of compliance for firms !"Any solution will require greatly increased resourcing, research and collaboration between regulators/supervisors, firms and academics who have little history of working together effectively to overcome significant barriers.

6.1 SETTING THE IMPLEMENTATION PATH It is fair to say that the majority of conversations we had about the platform in the course of our study got stuck well before considering how the change was going to occur. Thus, we have focused on the first three platform management capabilities and conclude this section with a ‘strawman’ for discussion about how we move forwards. Figure 17 shows the key questions to consider when designing a systemic risk control and oversight platform.

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THE ROADMAP

Figure 17: The systemic risk oversight implementation roadmap checklist 1.

Do we understand the problem we are trying to solve?

Do we know the platform requirements at Member State, region and global level?

Have the performance objectives been agreed?

How much are we willing to spend to build and maintain through 2020?

Are we agreed on a regulator-centric or firm-centric approach?

Have we understood the risks of working with systemic risk data?

Do we have a target operating model and do we understand the gaps?

Are we resourcing with the right people and are their incentives aligned?

Has accountability been assigned and appropriate governance established?

10. Are the method, plan and milestones and success criteria clearly articulated? Source: Interviews and JWG and Paradigm Risk analysis of regulatory implementation success factors between 2005 and 2010

The ‘who’ and the ‘how’ will be just as important as the ‘what’.

6.2 THE UK OPPORTUNITY Two-thirds of the way to completing our research, the UK released two consultations on the future of financial services supervision.82 As illustrated in Figure 18, there are important discussions about the way that responsibilities are defined. It is beyond the scope of our research to investigate the policy objectives of the new bodies that are under consideration. However, this is a great opportunity to take the future operating model for the platform into account when assigning responsibilities and goals. Figure 18: Future UK regulatory landscape Financial Policy Committee (FPC) “[It has] the tools and the responsibility to look across the economy at the macro issues that may threaten economic and financial stability and take effective action in response.”

Parliment

BoE

HMT

Consumer Protection and Markets Authority (CPMA) “It will regulate the conduct of every authorised financial firm providing services to consumers. It will also be responsible for ensuring the good conduct of business in the UK’s retail and wholesale financial services,”

MPC

PRA

FPC

CPMA

FSB

ESRB

ESMA

Prudential Regulation Authority (PRA) “Will carry out the prudential regulation of financial firms, including banks, investment banks, building societies and insurance companies.” George Osborne, Mansion House, 16 June 2010

Source: JWG and Paradigm Risk analysis of HM Treasury July 2010 consultation paper 82 HM Treasury, (2010), A new approach to financial regulation: judgement, focus and stability: http://www.hm-treasury.gov.uk/d/consult_financial_regulation_condoc.pdf

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THE ROADMAP

Creating a global blueprint Many of the people we have interviewed for this review have noted that fora for collaboration on the ‘blueprint’ for systemic risk do not exist. While it is beyond the scope of this analysis to suggest the governance structures for these committees, it is clear that there will need to be focused, but linked, conversations running in parallel. Whatever form these take, the right people with the right capabilities need to be ‘at the table’ to identify constraints and to resolve practical implementation challenges as they arise. Figure 19 highlights several of the practical fora that will need to be convened to identify and resolve implementation challenges.

Figure 19: Examples of systemic risk oversight platform design committees Level

Group

Focus

Participants

UK SRO operating model (SROM)

Future state operating model requirements

Supervisor, firm, academic

Platform design

Operating model design and planning

Supervisor, firm

Standards

Information standards

Supervisor, firm, ISO, IOSCO

European SROM

Regional operating model alignment

ESAs, BOE, ESRB?, firms, academic

European standards

Information standards

ESAs, firms, ISO, IOSCO

Global SROM

International operating model and standards alignment

ISO, IOSCO, CGFS, FSB, BCBS, academic

Platform design

Operating model design and planning

Supervisor, firm

Europe

International

Source: Interviews, JWG and Paradigm Risk analysis

6.3 THE BARRIERS TO CHANGE In the course of our research, we identified a number of barriers to putting in place effective supervisory control of systemic risk. It would be premature to suggest how these barriers can best be overcome in advance of the selection of the platform. However, as illustrated in this paper, and in Figure 20, there is much that we can start working on.

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THE ROADMAP

Figure 20: Systemic risk control barriers Operating model objectives

Disclosure

Harmonisation

Governance & commercials

Model structures

Missing regulatory data standards

Adoption of standards

No total cost of ownership, value statement or business case

No formal blueprints

5 false data assumptions

Significant data quality gaps

No consolidated impact assessment

Cross-functional collaboration

Signalling

Divergent legal frameworks

Lack of regional and international discussions

Interdisciplinary collaboration

Feedback

Divergent tax regimes

No design authority

Firm/regulator collaboration incentives

Guilty knowledge

Limited history of collaborative development; cost

Technical resources not assigned

Historical data requirement

Divergent procurement models

Technical performance characteristics

Forum for industry consultation and collaboration

Lack of aligned implementation plans

Source: Interviews, JWG and Paradigm Risk analysis

6.4 GETTING STARTED In looking at the barriers, it is evident that collaboration at many levels will be required to define the right approaches to breaching them. In the short term, we suggest that the relevant parties meet to scope the constraints and implementation challenges and define a terms of reference for each group to work towards solutions. While some of these barriers can be overcome quickly, many of them have existed since the financial services industry came into existence; knocking them down will require time, effort and determination, through: !

A UK approach agreed between legislators, policy makers, regulators, firms and systemic and firmlevel supervisors

Existence of and active participation in regional and international discussions.

Figure 21: Focus of immediate action Group

Operating model objectives

Disclosure

Harmonisation

Governance & commercials

SRO operating model (SROM)

Model requirements

Policy guidance

Regional and international commonality

Data procurement policy

Platform design

Capabilities specification

Operating procedures

Measures and metrics

Procedure design

Standards

Reference libraries

Transmission protocols

ISO standards

Minimum requirements

Source: Interviews, JWG and Paradigm Risk analysis

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THE ROADMAP

6.5 SUMMARY Clearly, these components are linked and interdependent. However, in summary, developing a viable systemic risk supervision platform will require politicians, policy-makers, regulators, firms and supervisors to address the following issues:

Figure 22: Issues for development roadmap

What operating model objective?

What platform design?

What path?

! Performance objectives

! Capabilities

! Governance

! Budget

! Specification

! People

! Options

! Controls ! Roadmap

Source: Interviews, JWG and Paradigm Risk analysis

Within these issues, we have identified the following design attributes and tools to assist with development of the systemic risk supervision and control platform:

Figure 23: Key findings Question

Finding

What operating model objective?

! ! !

Refer to ...

page

Opportunity for efficiency gains

section 5.1

37 – 38

Significant risks

section 6.3

‘Ballpark’ budget required for ROI

figure 8

3 operating model choices

38 – 40

section 5.2

41 – 42

figure 9 What platform design?

What path?

section 5.1

4 technical / data capabilities required

figure 10

42 – 47

Governance and control need

figure 10

47 – 48

A formal blueprint and specification that establishes ‘what a good systemic risk platform looks like’ is required

section 6.2

10-point checklist

figure 17

Well timed opportunity to put on the UK agenda

section 6.2

54 – 55

5 behaviour shifts

section 7.1

7+ ‘blueprint’ design committees

figure 19

Source: Interviews, JWG and Paradigm Risk analysis

55 54

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THE ROADMAP

6.6 PARADIGM SHIFTS There is no doubt that the recent financial crisis represents an “anomaly”83 to established regulatory, supervisory and academic methods in financial services and economics. Kuhn (1996) describes the stages of a paradigm shift: !

Previous awareness of an anomaly

The gradual and simultaneous emergence of both observational and conceptual recognition of the anomaly

Consequent change of paradigm categories

Resistance to change.

As early efforts fail to solve the problem, additional effort is focused on it to solve the challenges represented by the anomalies that have become apparent. Kuhn warns that transition from a paradigm in crisis – as economics surely is presently – is not a “cumulative” process; “it is a reconstruction of the field from new fundamentals ... that changes some of the field’s most elementary theoretical generalisations as well as many of its paradigm methods and applications ... When the transition is complete, the profession will have changed its view of the field, its methods, its goals.” Nothing less is necessary from the disciplines of economics confronted by the financial crisis of 2007. Of course, economics, as Karl Popper84 pointed out, is not a physical science and is not falsifiable. But the urgency for its change is no less than if it were. And paradigm shifts are also indicated in all areas touched by economics and its assumptions. Briefly, these are: FS regulatory data Data has been treated as the ‘poor orphan’ of financial management and regulation. At firm level, despite (or perhaps as a result of) the plethora of regulatory information requirements, there has been systematic under-investment in both data architecture relating to regulation and data quality. As a result of neglect at the regulatory level, there has been very limited pressure on firms to collaborate in the creation of industrywide standards or solutions to reference (or ‘static’) data. Regulators generally have made limited use of data collected and have under-invested in regulatory data architectures and architecture design. To achieve international comparability of data between national supervisors, data standards are essential and their development and implementation an urgent priority. This effort must be supported by regulators but ultimately will be driven by firms collaborating through international standards bodies, notably ISO. Recognition of the externality problem Firms have operated without cognisance of the spill-over effects of their risk-taking (externality problem). For regulatory initiatives to be accepted, regulators and supervisors must improve firms’ executives’ knowledge and understanding of the externality problem. They will need a level of understanding of the problem and capital add-ons so they can, if they consider it economically justified, adjust their business models to reduce the impost. Contribution of academics To solve the problems – resolve the anomalies – of the recent financial crisis, will require academics to adapt to new requirements and realities. Recognition structures and funding priorities must change to reflect the value of practical, problem-focused research. Also, inter-disciplinary collaboration must become less of an aberration. Far greater engagement by regulators, central bankers and politicians with the academic community is an urgent 83 Thomas Kuhn (1996) 84 Karl R. Popper (1963), Science as falsification in Conjectures and Refutations: The Growth of Scientific Knowledge, Routledge

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THE ROADMAP

necessity so that (a) they are better informed of options for technical solutions in systemic risk and (b) to provide the necessary grounding for academics in practical problems to focus academic research efforts. The single number approach Regulators and politicians will need to accept that there is no single-number solution to systemic risk; it will require a range of approaches which will, in all likelihood, produce ambiguous and even contradictory results. A range – a ‘plurality’ – of techniques, which are not necessarily comparable or compatible, should be encouraged and judged on their practical utility in informing decision-making at both the level of risk in the system and the ‘unsafe’ or trigger level of risk as well as its nature and dispersion (and the ‘safe’ level of dispersion or tipping point to ‘positive feedback’). Research funding and collaboration between sectors While academic independence must be preserved, the level of interaction between academics and supervisors, regulators and firms may need to increase radically to encourage greater awareness of the practical implications of theoretical problems in regulation and supervision and techniques to overcome them. The traditional mutual suspicion between academic and ‘practical’ sectors is counter-productive but is sustained by current approaches to funding academic research. Industry (and regulatory) input to focus the academic research agenda in finance and risk is desperately needed. Given that firms will inevitably seek narrowly defined benefits which they can capture, a material increase in attention from regulators (even if funded by the sector via industry levies) is needed. New approaches to funding of research on behaviour of interconnected financial networks and systems are required. Irrespective of the source of funding, research activity in this area will need to rise dramatically. Cost attribution Attribution methodologies for the cost of systemic risk to be reflected in adjusting capital add-ons for systemically important firms are indicated. These will require a new approach to communicating with firms against which the attributions are made about the logic and level of the requirements. Understanding from other disciplines Recent research for the World Economic Forum on lessons from other, high-risk, industries suggests that analysis of systemic risk may be enhanced by collection of ‘near miss’ data – those incidents that came close to precipitating crisis at firm or system level but did not. Global approaches to information management We have identified a number of issues which will require resolution in new data access arrangements !

Privacy of information must be secured

Global registry standards and service levels need to be established

Data security will need to be ensured for new data collected

Intellectual property rights must be obtained

Firms’ transfer pricing systems Rather than focusing on enforcing standardisation of organisational and structural arrangements, supervisors should increase their focus on the approaches firms use to create microeconomic incentives within the firm – their funds and risk transfer pricing mechanisms. Our experience, interviews and the FSA’s own research indicate that supervisory focus in this area is underemphasised and few supervisors have the skills required to interpret or judge firms’ FTP systems effectively.

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THE ROADMAP

Classification of ‘paradigm shifts’ or changes of mindset that are required By classifying the changes of mind-set identified by actor, we have identified the following 35 changes required: Figure 24: Paradigm shifts Conceptual framework

Politicians, regulators and supervisors

Investment firms

Academics

Research funding agencies

Integration with other approaches

Expectation of a single-point solution Assumptions around data Presumptions around compliance costs

Data as a firmlevel problem Data as a systemlevel problem Commitment to greatly improved allocation of risk cost through FTP systems

Overhauling DGSE modelling Agent-based modelling Data first versus model first Publication as principal measure of performance

Action

International collaboration essential to solving SR problems Greater engagement with firms over ! Data architecture ! Data standards ! Greater engagement with research sector

Development of a regulatory data architecture

Increase commitment to work with regulators, academics and trade bodies

Linking firm-level data architecture to regulatory data architecture Development of reference data standards Allocation of SR supraordinator roles

Regulatory affairs CIO/ architects Chief Administrative Officers/ COOs Compliance Risk management Strategy

Inter-disciplinary work essential

Improve greatly the practical applicability of economic research in finance and markets

Active engagement with ‘practical’ sectors

Need to encourage inter-disciplinary research Encourage nonorthodox and/ or innovative research areas in finance and markets

Need to encourage collaboration with the supervisory sector and investment firms

Review of funding models/ opportunities

! !

! ! !

Source: Interviews and Paradigm Risk analysis

Development of a platform design and review capability

Collaboration with other players / sectors

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THE ROADMAP

6.7 WHEN IS A SOLUTION POSSIBLE? It is valid to ask if a modelled solution to systemic risk, in its entirety, will ever be possible. While there is substantial academic debate about the efficacy of econometric approaches, for example, they are reasonably easily developed given existing or slightly amended data sets. More sophisticated approaches will require both considerable time and investment to develop and, in some cases, greatly increase access to firm-level or transaction-level data. The nature of requirements differs by the type of modelling proposed. Therefore, it seems realistic to recast the question as: over what timeframe is it reasonable to expect it will be possible to specify models and data requirements, then to collect, collate and analyse the data specified to define possible solutions? This revised question argues for a staged approach to developing modelling capability and data requirements. Again, the time requirement will differ by the type of modelling proposed, its sophistication and the feasibility of data access at firm and market level.

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

FINDINGS AND CONCLUSIONS

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

7. Findings and conclusions

7.1 COLLABORATION: THE KEY TO SUCCESS Of course, whatever the organisational structure, the systemic risk supervisor is entirely dependent on one critical resource: the right people. In the course of our discussions with the industry, a number of behavioural shifts were postulated as necessary to develop an effective systemic risk oversight platform: !

Supervisor/firm interaction. The need for an adjustment in philosophy, or perhaps, at times, attitude, will be required with the systemically important firms. While the mantra of “be afraid” applies to certain supervisory responsibilities, it does not work well in creating the collaborative environment needed for successful design of a systemic risk platform

Shared standards development. Given the complexity of the industry’s value chain, it is unreasonable to expect supervisors to define the precise data that they need. A number of interviewees in firms suggested that there must be a better way to share accountability for definition of the information set required by the supervisor. A few noted the absence of International Standards Organisation in the design of regulatory information needs (e.g., MiFID review)

Multidisciplinary skill sets. Lawyers, operations, finance, accounting and audit skills will be required to make it happen

Academic: industry engagement. This paradigm shift will require the inclusion of multiple disciplines in the discussion of the new platform requirements and new research funding models in the FS sector

Academic: academic engagement. In the course of our conversations, we were dismayed by the breadth of research disciplines involved in this conversation: psychology, oceanography, biology, economics, engineering, maths and physics were all noted85. The only ones not at the party thus far would appear to be the historians and the artists. There is a clear need to cross-pollinate and align research efforts in the field of systemic risk.86

7.2 FINDINGS FOR POLITICIANS, REGULATORS AND SUPERVISORS Key problems: !

Understanding systemic risk is a complex, multi-faceted problem. There are no single-point solutions

There is presently considerable political will to address the problem, but objectives of the national and supranational control organisations are not sufficiently aligned

Given the volume of market, technology and regulatory innovation, the requirements for a control infrastructure are getting more difficult quickly and will continue to change

The practical implications of the quantum of regulatory change is impossible for any one body to interpret for the whole industry

SR control is not a problem solved by edict from the ‘centre’. A collaborative approach inclusive of all facets of the industry is required

There is a ‘guilty knowledge’ dilemma that disincentivises supervisors from collecting data that they are not able to process and draw conclusions from

!"An efficient systemic risk supervisory structure requires global supraordination but approaches have already begun fragmenting in 2010 85 World Economic Forum (WEF), (2010), Everybody’s Business: Strengthening International Cooperation in a More Interdependent World: http:// www.weforum.org/pdf/grs2010/report/5-Global-Risks.pdf 86 WEF GRI article

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FINDINGS AND CONCLUSIONS

Incentives for collaboration with the firms who have the expertise, and the resources to help, have not been established

Vendor profit incentives are leading to the generation of multiple fragmented ‘quick fixes’ that will not address the holistic problem – which is yet to be understood

Costs can be in tens of billions without certainty of benefit

Milestones which are currently in the G20’s action plan are unlikely to be met.

What they mean to you: !

The problem will continue to distract supervisors from attending to the risks they are meant to be controlling

Consequences of moving too slowly, or in the wrong direction, are high as an incorrect analytical approach may do more damage than good

Whatever solutions do get developed are likely to be costly, late and inefficient as mandates for decision-making are not clearly articulated

More resources will be required at supranational, regional and EU Member State levels

A clear roadmap of ‘what good SR oversight looks like’ as described in Chapter 6 is required now

If you want to return to ‘crisis as usual’ stop reading now.

Your action check list: !

Articulate clear mandates at international, regional and national levels

Increase resourcing levels to do the job properly

Set a date by which a roadmap is required in order to catalyse new, ongoing requirements, design and standards discussions

Understand control requirements though practical, multidisciplinary and focused research

Make a realistic statement about the information capabilities that are truly required

Establish the incentives for the appropriate participation of the firms and their suppliers

Mandate the development of standard regulatory data taxonomy in each jurisdiction now, or accept the risks, costs and consequences of building a regulatory tower of Babel.

7.3 FINDINGS FOR INVESTMENT FIRMS, THEIR SUPPLIERS, TRADE BODIES AND TECHNICAL ASSOCIATIONS Key problems: !

‘Good policy’ requires understanding of a complex, innovative and fast market which is difficult for ‘outsiders’ to comprehend

Firms have not yet assigned responsibility for systemic risk across organisational silos and thus make consensus across front, middle and back-offices difficult

Cost/income ratios will increase due to technology and data spend demand

The current structure and resourcing of trade bodies makes it difficult to have discussions across firms

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

FINDINGS AND CONCLUSIONS

Lack of external support will put stress on strategy, policy, control, operations and technology functions within the firms

There is currently no incentive for collaboration outside the firm

There is currently no formal mechanism to engage technical standards bodies (e.g., ISO, XBRL, ISITC US), data vendors and technology suppliers should standards be mandated.

What they mean to you: !

If you are a systemically important firm, this is your problem

Policy makers won’t stop – you ought to help shape their answer into a good one

Waiting for someone else to solve the problem will only make it worse as you won’t be sure your issues are reflected in either the debate or the solution

You need to explain the problems in clear, well-articulated ways

You will need to collaborate with regulators to define requirements and scope solutions.

Your action check list: !

Assign a point person to create federated responses across front, middle and back-office functions

Ensure that you have the architectural team required to develop and control your firm’s regulatory data architecture

Define new methods of discussing issues and recommending global solutions across firms

Accept the need for, and contribute to, the roadmap described in Chapter 6

Find a way to engage the research community

Establish proofs of concept and tangible examples of the outputs.

7.4 FOR THE RESEARCH COMMUNITY, ACADEMICS AND FUNDING AGENCIES: Key problems: !

Relevance and utility of modelling approaches have proven limited

Regulatory, market and technology innovation are constantly shifting the goal posts

Research is not generally conducted on real problems using market-based data sets

The economics community funding model does not incentivise practical and collaborative approaches which model market behaviour

Limited feedback mechanism from the FS sector on the practical usefulness of the research is produced

Funding for research focused on the challenges for SR supervision needs to increase dramatically.

What they mean to you: !

You will need to make new friends in other disciplines and develop multi-disciplinary and crossdisciplinary approaches

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

FINDINGS AND CONCLUSIONS

You will need to increase engagement levels with the back-office and corporate functions to better understand how the industry works

More effort will be required to define and promote the practical utility of your research

Funding models and prioritisation mechanisms need to change.

Your action check list: !

Establish research agendas focused both on theory and on finding solutions to practical problems in systemic risk

Your research will need to start with data first, rather than model first

Research funders to promote sector (especially regulator and supervisor) engagement and define and postulate solutions to practical problems

Engage with regulators and supervisors to define new industry research funding models.

7.5 CONCLUSIONS This report has taken a snapshot of a fast changing landscape. From this picture, it is clear that the industry has started to digest the lessons of the crisis and put in place the new nuts and bolts required for control. While the problem is understood by some, the very nature of the paradox is complex and few have thought through the roadmap to solve it. At the time of this report, there were encouraging signs that resources were being mobilised to address the issues. Diverse arrays of measures are in various stages of implementation across the globe. However, the level of harmony between these approaches is low. Expectations are high and deadlines for results are tight. Given the scale, complexity and cost of the challenge, establishing a new platform for systemic risk oversight will not be quick, easy or cheap. The total cost of effective implementation could cost many billions, whilst poor implementation could have severe consequences on the economy through higher taxes, fees and ill-informed monetary policy or unecessarily suppressed economic growth. Equally, a regime based on a system of ‘Garbage In, Gospel Out’ would not only unduly burden the economy but also create a situation where it would be even more susceptible to the next crisis. The fact that the recent crisis has left our central banks and economies impoverished has highlighted the need for a better system. However, if it is not implemented effectively, sooner rather than later, then, when the next crisis arrives, we will not be able to afford it. Systemic risk, therefore, is a problem that cannot be left to chance. Without a global change programme the industry will revert to ‘crisis as usual’. If we genuinely want to effect the change championed by politicians, implementing an effective systemic risk regime is a high priority. If the next crisis is of the same magnitude as the most recent one, it is unlikely we will survive. We are in a situation now where real change can, and must, be effected. To overcome this challenge, a degree of collaboration, not previously envisioned, is required. Only with the right skills in the right place, focusing on the right problems, will a solution be achieved. In order to succeed collectively in addressing the problems of systemic risk, all sections of industry – firms, regulators, supervisors, academics, central bankers, trade bodies and interested politicians – will need to contribute to enhancing and building upon the findings in this report and other studies to define desired outcomes and put in place the foundations for an information highway that is fit for the financial services industry.

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

List of attachments

Interviews conducted Bibliography

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Interviews conducted

TYPE

INSTITUTION

ACADEMIC

University of Essex Centre for Computational Finance and Economic Agents (CCFEA) London School of Economics (LSE) Cass Business School University College London (UCL) University of Keale Paul CĂŠzanne University (Aix-Marseille III)

REGULATORS

Financial Services Authority (FSA)

CENTRAL BANKS

Bank of England (BoE) European Central Bank (ECB)

FIRMS

Citigroup Man Group HSBC Barclays Capital

OTHER

Association for Financial Markets in Europe (AFME) British Bankers Association (BBA) International Organisation for Standardisation (ISO) Society for Worldwide Interbank Financial Telecommunication (SWIFT) XBRL US Enterprise Data Management Council (EDM) International Organisation of Securities Commissions (IOSCO Financial Stability Board (FSB) World Economic Forum (WEF)

ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK

Bibliography

Note: a comprehensive bibliography with relevant URLs is available online to accompany this report. Visit www.jwg-it.eu or www.paradigmrisk.com

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ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK |

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ACHIEVING SUPERVISORY CONTROL OF SYSTEMIC RISK