Credit Risk Modelling by Informa Middle East

Credit Risk Modelling Highlighting Best Practice And Current Developments

Updated for 2013 17 â&#x20AC;&#x201C; 20 November 2013 Jumeirah Emirates Towers Hotel, Dubai, UAE

Top 5 Learning Objectives 1. Explore latest qualitative and quantitative credit measurement and modelling techniques related to individual credit facilities, corporate credits, distressed corporate debt, corporate lending, sovereign lending, distressed sovereign debt, sovereign and credit rating process, securitised credit exposures and portfolios of credits 2. Learn current credit risk modelling best practice for the assessment, measuring and modelling of credit risk factors including potential credit exposures, credit loss distributions, default frequencies, times to default, recovery rates, credit migrations, credit spreads and dependent default frequencies 3. Understand best practice and applicability of qualitative financial scoring models, regression-based financial distress and failure prediction models, structural and reduced-form credit risk models 4. Implement qualitative and quantitative credit modelling techniques, including Credit-Value-at-Risk (CVaR), using practical Excel-based Monte Carlo simulation exercises 5. Acquire knowledge of best practice for credit loss protection techniques and various procedures for hedging different aspects of credit risk and the evolution of a global regulatory Basel capital standard, i.e. Basel I, II, and III

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Please bring your laptop Loaded with Excel

Credit Risk Modelling

17 – 20 November 2013 Jumeirah Emirates Towers Hotel, Dubai, UAE

Course Methodology

Course Overview Since the early 1990s, credit risk measurement, modelling, and management has advanced, evolved with and beyond the traditional methods using credit agency ratings, credit scoring, assessing credit risk and assigning collateral based on the outstanding principal of the credit exposure. Currently, to effectively use these traditional and recently developed methods requires a practical knowledge of their limitations and downsides. The main focus of the course is towards developing a solid understanding of both the upsides and downsides of the procedures required for assessing, evaluating and modelling the creditworthiness of those positions exposed to the wide range of credit exposures, including distressed corporate and sovereign debt issues that affect the performance of the various credit providers and lenders. The course also presents a comprehensive discussion of the current and best practice in qualitative and quantitative credit risk modelling and measurement techniques, which have become required skill sets for today’s credit risk managers and analysts. This course continues with discussions of both qualitative and quantitative credit risk assessment techniques; including regressionbased ratings procedures using financial ratios and the scorecard approach of the CAMEL credit assessment system. Systemic risk issues including: rating sovereign debt issues, assessing sovereign default risk using market premiums from sovereign Credit Default Swaps (CDSs) and the reasons underlying the current sovereign debt issues. The course also discusses best practice for the modelling and measuring of credit loss distributions, individual and dependent default probabilities and intensities, credit migration transition matrices, recovery rates, and credit spreads. Extensions of Valueat-Risk (VaR) forecasts for assessing credit risks, i.e. CVaR, are also presented for standalone and portfolio credit risk assessment. Discussions of structural and reduced-form credit risk models are also presented, and various comparisons of common commercial/vendor credit portfolio risk models are also presented. Basel II, as detailed in the latest June 2006 version of Basel II, presented in terms of general principles of Basel II is a set of three mutually reinforcing pillars, i.e. Pillar I – Minimum capital requirements, Pillar II – Supervisory review, and Pillar III – Market discipline. Also, Basel III, which is the latest extension of the Basel Accords, is discussed in terms of the new Basel rules included in the December 2010 Basel initiative and the June 2011 update for reforming global regulatory framework.

The lecturing and course context are developed and presented through a systematic approach, starting from fundamentals of credit exposures to qualitative scoring methods, quantitative standalone and portfolio credit risk modelling techniques and advanced credit risk modelling using structures and securitised credit products. The modelling procedures are supplemented with the analysis of various case studies of systemic credit crisis examples since the 1980s including the LDC crisis of the 1980s, the Collateralised Mortgage Obligations (CMOs) crisis of the mid-1990s, the subprime crisis mid to late 2000s, the subsequent credit market freeze up of late 2008 and early 2009, and the European sovereign debt of 2011. An extensive set of practical worked exhibits and examples, discussions and case studies, computer simulations and various other exhibits are used throughout this course. You should be familiar with Microsoft Excel.

Course Introduction Issues, implications and consequences of the excessive credit risk exposures in mortgage lending, faulty credit ratings, credit concentration risks, significant counterparty risk exposure and subsequent defaults, sovereign debt risk exposures, country defaults, etc. have nearly become everyday events and headline news. The common prominence of these issues in the news has been due to the global contagious effects of the systemic sovereign debt crises in the European Union starting in 2009 and into August 2011 and beyond, the August 5, 2011 downgrade of US sovereign debt by Standard and Poor’s, the contagious global implications of US subprime lending and securitisation crises of the middle 2007 into 4th quarter of 2008, and the spillover to a global market recession in 2009 and beyond. These issues have led to a greater need by credit lenders, analysts and risk managers to understand the criteria used in determining and assigning credit ratings, the methods for assessing standalone and portfolio risk exposures, and dealing with the corresponding model misspecification and estimation risks faced when using these approaches that underlie these issues just mentioned. This course is designed to meet these needs and present delegates with knowledge of best practice and update them with current developments in the credit markets.

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Notes – Prerequisites An understanding of the workings of the credit markets, basic knowledge of standard risk measurement models and intermediatelevel courses in statistics and probability are prerequisites. Proficiency with Excel is also suggested. Delegates should bring their own laptop with Excel preloaded.

+971 4 335 2437

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The in-house training division of IIR Middle East Tel: +971 4 407 2624 • Email: CTS@iirme.com www.iirme.com/cts

www.iirme.com/creditrisk

Credit Risk Modelling

17 – 20 November 2013 Jumeirah Emirates Towers Hotel, Dubai, UAE

Course Timings: Registration will be at 07:30 on Day One. The course will commence at 08:00 and conclude at 14:30. There will be refreshment breaks at approximately 10:30 and 12:30 and lunch will be served at approximately 14:30, at the end of each day’s session.

Day One Credit Risks, Exposures, And Events; Corporate Credits, Distressed Corporate Debt Credit Rating Process And Distressed Sovereign Debt And Sovereign Credit Ratings Module 1.1 – Credit Risks, Exposures And Events • Credit, credit analysis, and credit decisions – a historical perspective • Common factors affecting industry sectors – market, strategic and financial variables • Credit risk definitions, categories, sources, and exposures for creditsensitive products - Exposures for credit-sensitive instruments and other credit products - Exposures for corporate loans - Exposures from credit given to retail customers - Exposures inherent to a bank’s trading operations - Exposures from derivatives positions • Credit events arising in credit risk modelling – Default, trigger and termination events

Excel Exercise – Simulation of default events and the times to default Module 1.2 – Corporate Credits And Distressed Corporate Debt • What is corporate credit - fundamental characteristics of corporate debt • Corporate credit types and corporate capital structure • Defining/labeling the unsuccessful business enterprise • Distressed securities and distressed debt – overview • Business failure, insolvency, default and bankrupt – definitions • Financial distress, debt restructuring and costs of bankruptcy – issues • Red flags for financial distress and/or elevated credit risk exposures • Red flags indicating a potentially distressed/insolvent debtor Comment – High yield bond market: risks and returns for investors Module 1.3 – Corporate, Bank And Other Credit Ratings – Foundations • Establishing good credit and credit lending decision – basic issues • Credit ratings process – guidelines, criteria, information and perceptions • Rating definitions for various credit market segments - Individual bank, corporate, and insurance company ratings - Issuer default ratings - Domestic short and long-term debt ratings - International short and long-term debt ratings - Recovery ratings • Point-in-time and through the cycles ratings – a comparison

Exhibit – Fitch’s, S&P’s and Moody’s ratings criteria, definitions and symbols Module 1.4 – Sovereign Debt, Sovereign Ratings, And Sovereign Credit Default Swaps (CDS) • Fundamental characteristics of sovereign debt issues • How sovereign public debt differs from private debt • Sovereign credit ratings – definitions, uses, and types • Credit quality factors and indicators for rating sovereigns • Sovereign debt defaults and restructuring – determinants and key elements

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• Assessing and managing sovereign debt exposures using sovereign CDS

Exhibit – Various sovereign credit ratings by agency and country Discussion – Systemic effects of the August 5, 2011 downgrade of US sovereign debt by the S&P credit rating agency from AAA to AA+ Discussion – Global and local spillover implications and contagious consequences of US subprime crisis of the 2000s, subsequent global market recession of 2009 and beyond and global markets recovery to a “New Normal” Discussion – Systemic sovereign debt crises in the European Union of 2009 and the implications of the Euro and the European Monetary Systems (EMS)

Day Two Practical Issues With Credit Ratings, Credit Assessment Using Financial Ratios, Credit Quality Assessment, Credit Scores, Credit Scorecards, Credit Scoring Methods, And Qualitative Credit Scoring Models Module 2.1 – Corporate, Bank And Other Credit Ratings – Practical Issues • Limitations and practical issues for credit ratings - Credit ratings migrations and backward looking ratings forecasts - Conflicts of interest between rating agencies and their clients - Granularity issues for credit rating scales - Counterparties, concentration risks and collateral management Module 2.2 – Credit Assessment Using Financial Ratios • Financial statements analysis and financial ratios – overviews - Credit ratios and financial stability measure - Short and long-term solvency ratios or liquidity ratios - Asset management ratios or turnover measures - Profitability measures and value ratios - Cash flow and operating measures - Growth, stability, size, and payout ratios • Forecasting credit worthiness using financial ratios – introduction

Discussion – Chinese reverse mergers shortcut to Wall Street listings and financial statements fraud during 2010-2011 Exhibit – Comparison of credit agency ratings versus comparative financial ratios Module 2.3 – Classic Credit Evaluation And Analysis Using Credit Scores And Scorecards And Consumer Credit Scoring Factors • Credit evaluation using credit-scoring techniques • Comparing credit scoring and credit rating • Different types of credit scores and credit scorecards • Scorecard development and the selection of scorecard characteristics • Characteristics used in accounts receivables and collection scoring

Exhibit – Scoring criteria – characteristics and attributed used in consumer scoring models Exhibit – FICO and Vantage credit scores – a comparison

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Credit Risk Modelling

17 – 20 November 2013 Jumeirah Emirates Towers Hotel, Dubai, UAE

Module 2.4 - Credit Scoring Methods – Characteristics, Attributes And Scores • Common statistical and judgmental indicators of credit worthiness • Common predictors of credit quality for individuals/consumers • Distinguishing between risk classes in score-based rating systems • Extracting a credit rating system from credit scoring models • Judgmental and Quantitative risk characteristics for consumer credit scoring

Exhibit – Credit scoring examples for credit approval, accounts receivables, fraud, recovery, and collections scoring Module 2.5 – Qualitative Credit Scoring/Grading – Factors And Models • Common credit quality indicators and predictors and technical adjustments • Credit quality scoring models and scorecards – overview

Exhibit – Using scoring models to distinguish between various credit rating grades Exhibit – Example of consumer scorecards: FICO credit scores and Vantage scores Exhibit – KPIs and KRIs for assessing credit quality Exhibit – Key Risk Indicators (KRIs) and a credit risk rating framework for individual banks and Japanese banking industry structure Exhibit – Five or six Cs of credit: factors affecting the credit ratings Exhibit – CAMEL creditworthiness assessment system Exhibit – Argenti’s A-scores for assessing creditworthiness

Module 3.2 – Credit Risk Modelling: Credit Loss Distributions, Loss Exposure Modelling, Default Likelihoods/Probabilities, And Dependent Defaults • Modelling credit exposures – current and potential exposures • Credit loss structures – expected, unexpected and extreme losses • Common loss distribution models used in credit risk modelling • Default predictors, default frequency, times to default and default term structure • Commonly used approaches to modelling dependent/conditional defaults

Exhibit – Relationship between default probabilities and credit ratings Exhibit – McKinsey’s Logit default prediction model Excel Exercise – Simulation modelling of potential credit loss distributions Excel Exercise – Simulation modelling of conditional and dependent default events Module 3.3 – Recovery Rates, Credit Rating Migrations, And Credit Spreads • Factors affecting recovery rates modelling recovery rates • Credit ratings migration process – credit quality downgrades and upgrades • Limitations of historical estimation of credit migration probabilities • Economic factors affecting credit spreads and ratings-based credit spread models

Excel Exercise – Simulation modelling of loss-given-default with random recoveries Excel Exercise – Simulating rating transitions using Markov chains with multiple credit ratings categories and a default absorbing state Excel Exercise – Simulation modelling of credit spreads

Exhibit – Piotroski F-Score for assessing financial strength

Day Three Regression-Based Credit Quality Prediction Models, Credit Exposure Factor Modelling, Reduced-Form And Structural Credit Risk Models Module 3.1 – Regression-Based Credit Quality Prediction Models Using Financial Rations And Other Credit Quality Indicators • Financial attributes affecting retail and corporate credit quality worthiness • Corporate/retail business failure prediction – overview and summary comments • Regression-based credit ratings models using financial ratios – examples - Beaver’s financial distress model and failure prediction using financial ratios - Altman’s Z-score and Zeta score models for failure prediction using financial ratios - Ohlson’s Logit regression model for bankruptcy prediction using financial ratios - Horrigan’s Multivariate discriminant model for bond rating predictions using financial ratios

Exhibit – International survey of credit scoring models and associated explanatory variables

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Module 3.4 – Default And Time To Default Forecasting Using Reduced-Form And Structural Credit Risk Models • Structural and reduced-form credit risk models – fundamentals and applications • Merton (1974) structural model – option-theoretic default forecasting model • Forecasting default spreads and recovery rates using structural models • Credit spreads and exogenous factors underlying times to default for reduced-form models • Structural and reduced-form credit risk models – strengths and limitations

Excel Exercise – Simulation modelling of KMV’s Distant-to-Default (DtD) and corresponding default probabilities using the Merton (1974) asset value model Excel Exercise – Simulation modelling of reduced-form models using credit spreads

Day Four Standalone And Portfolio Credit Risk Assessment Using Cvar, Commercial Credit Portfolio Risk Models, Managing And Mitigating Credit Exposures And Basel I, II And III Module 4.1 – Standalone And Portfolio Credit Risk Assessment Using CVaR Forecasts • Key risk factors affecting parameter specifications for credit portfolio risk

www.iirme.com/creditrisk

Credit Risk Modelling

17 – 20 November 2013 Jumeirah Emirates Towers Hotel, Dubai, UAE

• Credit Value-at Risk (CVaR) model types – overview and characteristics - Default Mode models (DM) - Mark-to-Market (MTM) models • Standalone CVaR – Assessing expected and unexpected losses for credit exposures • Portfolio CVaR – Assessing expected and unexpected losses for portfolio credit exposures

Short overview discussions related to systemic credit crises since and during the 1980s, which will be discussed during the course • Lesser Developed Country (LDC) crisis of early 1980s and Brady bond restructuring innovation for distressed sovereign debt • Banking crisis and fraud in the US savings and loan industry during the early 1980s

Excel Exercise – Simulation modelling of portfolio credit risk losses with random default arrivals, recovery rates, and credit exposures

• Leveraged Collateralised Mortgage Obligations (CMOs) crisis, US bond market sell-off of 1994 and mutual funds losses

Excel Exercise – Putting it all together – developing Monte Carlo simulation models for standalone and portfolio credit VaR forecasts

• Global and national implications and consequences of the US subprime crisis of the late 2000s – implications of prolonged US recovery and the “New Normal” for global markets

Excel Exercise – Simulation modelling of dependent default events and credit VaR forecasts

• Resilience of Islamic financial institutions when compared to conventional western banks during 2007-2009 financial crisis

Module 4.2 – Commercial/Vendor Credit Portfolio Risk Models • Key risk factors affecting parameter specifications for credit portfolio risk • Best practice and modelling methodologies underlying commercial credit portfolio risk systems, including: - RiskMetrics CreditMetrics® portfolio credit risk model - Credit Suisse Financial Products (CSFP) CreditRisk+ - KMV/Moody’s Credit Portfolio Manager™ - McKinsey’s Credit Portfolio View

Exhibit – Comparison of commercial credit portfolio models strengths and limitations Module 4.3 – Credit Loss Protection Techniques, Hedging Counterparty Credit Risk, Assessing Credit Concentration Risk, Hedging Credit Risk Using Credit Derivatives And Credit Derivatives Indices And Credit Fraud Prevention • Common credit loss protection techniques – bills discounting, factoring of accounts receivables, financial guaranties, Letters of Credit (LoCs), credit insurance, securitisation, collateral and margining and the use of covenants • Credit concentration risk – sector and single-name concentration risk and the Herfindahl-Hirschman index of concentration • Assessing Counterparty Credit Risk (CCR) using Credit Valuation Adjustment (CVA) • Credit Default Swaps (CDS), credit derivatives indices and other credit derivatives - Default protection and hedging credit risk • Customer identity verification and preventing fraud in a credit scoring and rating Module 4.4 – Basel I, II And III – Evolution Of Global Regulatory Capital Standard • Regulatory capital and the Basel I and II accords – overview • Basel II - Pillar I – minimum capital requirements - Basel II - Pillar I modelling approaches – I: standardised approach - Basel II modelling approaches – II: foundation internal rating based approach - Basel II modelling approaches – III: advanced internal ratingbased approach • Basel II Pillar II: supervisory review – overview • Basel II Pillar III: market discipline – overview • Basel III – December 2010 initiative proposal and June 2011 update for reforming global regulatory framework

Exhibit – Comparing expected and unexpected credit losses, economic risk capital, and regulatory capital

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• Systemic sovereign debt crises in European Union arising in the aftermath of the credit crunch and liquidity freeze of late 2008

Meet Your Expert Course Director Dr. John W. Dalle Molle is an independent financial markets consultant and trainer specialising in quantitative credit, energy, market and operational risk management, analytics and modelling. Recently, he has been involved in model validation consulting projects with major Singaporean and Malaysian banks. He has presented executive educational and professional training programs in Africa, the Americas, Asia-Pacific Region, South Asia, the Middle East, the GCC and various European countries. His clients include several large financial institutions and central banks. In the past, he has also taught at a number of renowned universities in Asia, Europe, and the Americas. Dr. Dalle Molle has also made several professional presentations at international conferences and exhibitions.

Who Should Attend? Organisations and individuals seeking commercial and personal credit and credit lines, those making commercial and personal credit-granting decisions, lending and credit policy makers, commercial and in-house credit scorecard developers and users, credit risk managers and regulators; and specifically: • Asset/liability managers • Back and middle office personnel involved in credit risk management • Accounts receivables, billing and collection managers • Central bankers, market regulators and bank supervisors involved in credit markets • Credit portfolio risk managers, chief risk officers and enterprise risk managers • Corporate financial analysts involved in credit risk assessment • Credit department personnel, loan origination officers and underwriters • External and internal auditors and compliance personnel • Quantitative credit analysts • Retail, commercial and consumer lending managers • Treasury and capital markets analysts and managers

www.iirme.com/creditrisk

Credit Risk Modelling 17 – 20 November 2013 • Jumeirah Emirates Towers Hotel, Dubai, UAE

FIVE WAYS TO REGISTER IIR Holdings Ltd. P.O Box 9428 Dubai, UAE

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DISCOUNTS AVAILABLE FOR 2 OR MORE PEOPLE CALL – 971-4-3352483 E-MAIL – a.watts@iirme.com WEB BC4977 Event

Course Fee Before 1 September 2013

Course Fee Before 22 September 2013

Final Fee

US$ 3,895

US$ 4,395

US$ 4,695

Credit Risk Modelling (BC4977) 17 – 20 November 2013

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Course fees include documentation, luncheon and refreshments. Delegates who attend all sessions will receive a Certificate of Attendance.

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Cancellation If you are unable to attend, a substitute delegate will be welcome in your place. Registrations cancelled more than 7 days before the Event are subject to a $200 administration charge. Registration fees for registrations cancelled 7 days or less before the Event must be paid in full. Substitutions are welcome at any time.

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Event Venue: Jumeirah Emirates Towers Hotel, Dubai, UAE Tel: +971 4 330 0000 Accommodation Details We highly recommend you secure your room reservation at the earliest to avoid last minute inconvenience. You can contact the IIR Hospitality Desk for assistance on: Tel: +971 4 407 2693 Fax: +971 4 407 2517 Email: hospitality@iirme.com © Copyright I.I.R. HOLDINGS B.V.

ON/ST FN140506 Credit Risk