passing the turing test

A risk management system solely designed for complicated situations will definitely pass a Turing Test. The human manager will not be distinguished from the computer. A risk management system that relies solely on rigid rules and procedures can (and probably should) be replaced by a computer or a bot. However, a computer or a bot (or other form of artificial intelligence) cannot deal with complex situations.

Complex risks require judgment, intuition and context sensing – all characteristics that are unique to the human mind. Processes and algorithms that can be programmed do not have the required flexibility or adaptability of the human manager. While risk managers as individuals, or as departments also have their flaws and errors and biases, these shortcomings are not as bad as assuming that all risks are complicated.

So, take a minute and consider the most critical risks that your organization is facing. Do most of these risks follow well-defined rules like the laws of physics, or are they related to the underpinnings of complexity; agents, who can interact and who can adapt? Are your most critical risks complicated or complex? Does your risk management pass a Turing Test?

As a follow-up to this article, join us for a PRMIA thought leadership webinar on March 29

Rick Nason will sit down with Carl Densem, Intelligent Risk editor, to discuss VUCA, AI, and the future of risk management. Learn more

peer-reviewed by

Carl Densem

Rick Nason

Rick Nason, PhD, CFA, is an Associate Professor of Finance at Dalhousie University where he been awarded numerous awards for teaching excellence. His academic work includes researching corporate risk management and complexity in business. As a former capital markets, as well as corporate learning professional, he remains active in consulting and corporate training, specializing on applications of complexity science and risk management.

He is the author / co-author of seven books and textbooks, including It’s Not Complicated: The Art and Science of Complexity in Business, published by University of Toronto Press, and Rethinking Risk Management, by Business Experts Press.

Synopsis

Technological innovation has already made strides in advancing parts of the financial system, notably the payments sector, increasing access to customers who now have more choice. At the same time, there is a growing awareness of risks stemming from rapid technological advancement, with regulatory scrutiny increasing too. There are ways, however, for financial firms to continue to achieve innovation, without compromising systemic risk mitigation effort.

Systemic Risk Mitigation Should Be Front Of Mind In Technological Innovation

by Michael Leibrock

Emerging technologies hold considerable promise and benefits for the global financial system. Distributed ledgers, for example, could be used to validate and track transactions on a distributed and decentralized platform, providing a compelling alternative to today’s centralised payment infrastructures. More specifically blockchain, a type of distributed ledger technology (DLT), could improve efficiency in existing international payments systems and infrastructures. The payments sector is a great example of how technology has helped increase client access to the financial system while enhancing the user experience leveraging innovative payment tools.

After all, new technologies are significantly changing the way society and the financial services industry conduct business. Initially, many fintech developments focused on enhancing existing capabilities through innovative technologies, such as the cloud, Application Programming Interfaces (APIs) and machine learning. Today, fintech applications are looking to fundamentally transform the way counterparties interact with one another, for example by using distributed ledgers, smart contracts and digital assets.

Introduction Addressing New Risks

Despite the multiple current and potential use cases, no new technology application comes without risks. First and foremost, the interdependency or interconnectedness of the global financial marketplace should be front of mind when considering new technology implementations. Recent events in the crypto industry highlighted the increased risk of contagion to the financial sector and the real economy.

Indeed, a recent report by the Financial Stability Board (FSB) has shown that correlations between crypto asset prices and mainstream equity indices have been steadily increasing. Meanwhile, the use of DLT, while minimizing some risks and providing efficiencies, simultaneously increases the number of points of potential failure, as well as the risk of data breaches, hacking and other types of third-party risk. According to DTCC’s most recent Systemic Risk Barometer survey, the threat posed by cyber risk is considered one of the top three risks in financial services. Consistently ranked as one of the top risks since the survey first launched in 2013, against the backdrop of increasing adoption of new technology solutions and the related risks to the industry, this trend is only likely to accelerate in coming years.

There are also a number of other influential factors that should be addressed. For example, models, including AI-based models, have contributed to faster and often better decision-making. However, an over-reliance on models that are calibrated largely on historical data and events can be less effective when unprecedented, exogenous shocks occur. For example, the Covid-19 pandemic led to widespread deficiencies in credit rating models, as the dislocation of historically stable fundamental credit risk factors and macro-economic variables produced unreliable probability of default estimates. Additionally, the overreliance on high-speed processing and output decision making can lead to errors, lack of transparency, and underpin unintended biases. Furthermore, conflicting national priorities can also impede cross-border data sharing, compromising efforts around tackling cyber terrorism and financial crimes – both of which are on the rise. Finally, the use of social media platforms and online forums has the potential to negatively impact market volatility and risk, enabling frictionless retail financial participation on low-cost digital platforms and brokerages which, for example, contributed to the 2021 meme stock event.