GARP Risk Podcast

Hear from risk modeling expert Tony Hughes about the parts various risk management techniques played in recent bank failures, as well as the current challenges facing modelers.

Risk models have grabbed headlines for all the wrong reasons over the past couple of years, and now they are in the news again thanks to the sudden collapses of Silicon Valley Bank and Signature Bank. People want to know why the internal risk models at these banks did not properly account for interest-rate risk and why they seemed completely unprepared when their depositors made a mad dash for the exits.

The failures have also raised thought-provoking questions about liquidity risk management deficiencies, the proper use of stress testing, risk governance problems, and the flaws in current bank regulation.

What’s more, these issues are being raised at a time when modelers are contending with other significant challenges, such as forecasting for expected credit losses during a time of great uncertainty.

Risk modeling maestro Tony Hughes, Risk Intelligence’s “Risk Weighted” columnist, joins GARP editorial director Robert Sales to discuss some of the hottest FRM issues of today.

Speaker's Bio:

Tony Hughes is a risk modeling and ESG expert. He has more than 20 years of experience as a senior risk professional in North America, Europe and Australia, specializing in model risk management, model build/validation and quantitative climate risk solutions.

Hear risk management prognostications from Cris deRitis, the deputy chief economist at Moody’s Analytics.

Risk managers have been severely tested over the past 12 months. Rising interest rates, supply-chain problems, inflation and heightened geopolitical risk contributed to an environment of volatility and uncertainty, and many financial institutions grabbed headlines for all of the wrong reasons.

Operational risk disasters, for example, have cost large banks hundreds of millions of dollars. Credit risk modelers, meanwhile, are still trying to figure out the best path forward after wrongly forecasting a wave of defaults amid the pandemic.

The financial sector was also hit hard by data breaches that exposed cybersecurity flaws, while cryptocurrencies, highlighted by the collapse of FTX, experienced a host of failures as part of the so-called “crypto winter.” Last but certainly not least, we’ve witnessed the expansion of artificial intelligence in financial risk management, though concerns about explainability, bias and transparency remain.

How will the remainder of 2023 of shake out? What regulatory changes may be on the horizon, and which trends will have the greatest impact? Cris deRitis, the deputy chief economist at Moody’s Analytics, speaks with GARP editorial director Robert Sales about what lies ahead for risk managers.

Speaker’s Bio:

Cristian deRitis is the Deputy Chief Economist at Moody's Analytics. As the head of model research and development, he specializes in the analysis of current and future economic conditions, consumer credit markets and housing. Before joining Moody's Analytics, he worked for Fannie Mae. In addition to his published research, Cristian is named on two U.S. patents for credit modeling techniques. He can be reached at [email protected].

Hear from Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions @ SAS, as we discuss the impact of current market trends on asset liability management

With a possible recession looming and inflation near its highest levels since the 1980s, navigating around balance sheet issues remains complex. In this first of a series of podcasts on asset and liability management (ALM) featuring academic and industry experts, we will tackle the following topics:

·         The current regulatory and marketplace-driven challenges for risk analytics

·         How to handle term structure modeling in times of rising interest rates and inverted yield curves

·         Requirements for quantitative approaches in ALM in the current environment

Speaker Bio

Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions @ SAS

Dr. Donald van Deventer joined the Risk Research and Quantitative Solutions group at SAS Institute, Inc. in June 2022 through SAS’ acquisition of his previous firm, the Kamakura Corporation. He founded Kamakura in 1990 and served as Chairman and Chief Executive Officer until the acquisition.

Dr. van Deventer's emphasis at SAS Institute, Inc. is enterprise-wide risk management and modern credit risk technology. His primary financial consulting and research interests involve the practical application of leading-edge financial theory to solve critical financial risk management challenges.

Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to risk management. This time, we are partnering on a brand-new podcast, Risk and Resiliency to take a closer look at ways to face the challenges ahead, to be more agile, vigilant, and quickly adapt to shifting market conditions. 

 About SAS

As a leader in analytics, SAS’ award-winning capabilities in analytics, risk management, and other technology areas have helped customers across the globe solve their toughest and ever-evolving business problems. Its unrelenting commitment to innovation enables organizations across financial services to modernize and sustain a competitive edge. Through the latest developments in machine learning, natural language processing, forecasting, and optimization, SAS supports diverse environments and scales to meet changing needs. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk

Hear from Alla Gil, the co-founder and CEO of Straterix, as we examine the liquidity risk challenges and trends that have been fueled by extremely rare market conditions.

In a recent survey conducted by the Securities Industry and Financial Markets Association, 80% of economists named stagflation – or a combination of high inflation and stagnant growth – as the greatest long-term risk to the U.S. economy. The economists said that stagflation presents an even bigger threat than a 2023 recession, and this news has undoubtedly added to the consternation currently felt by liquidity risk managers.

We haven’t seen a true period of stagflation in the U.S. since the oil crisis of the 1970s, and its therefore very difficult to factor this anomalous macroeconomic risk into contemporary liquidity risk models.

Alla Gil joins GARP editorial director Robert Sales to discuss the impact of stagflation and the steps risk practitioners responsible for modeling and managing liquidity risk can take to ensure that they have enough cash on hand, both now and in the future?

SPEAKER’s BIO:

Alla Gil is CEO and co-founder of Straterix Inc. With an academic background in theoretical mathematics, she began her Wall Street career at Goldman Sachs, working on stochastic models for derivative pricing. While heading Global Strategic Advisory teams at Citigroup, Nomura - and again at Goldman Sachs - she introduced stochastic modelling and an optimization approach to the world of corporate finance. Over a 20-year period, Alla advised banks, sovereign treasuries, insurance companies, asset managers, and pension funds on ALM, stress testing, long-term risk projections, liquidity, optimal capital allocation and balance sheet optimization With Straterix, she has developed a methodology and tools that enable clients to automate the process of scenario creation and expansion to assist in strategic capital planning and optimization, as well as risk management and stress testing.

Hear from Prof. Clifford Rossi as we examine some of today’s biggest financial risk modeling challenges.

In the financial services industry, risks related to climate change are now considered major, resulting in all firms assessing how to incorporate climate risk in financial decision making. As we find ourselves in the decisive decade, there is an urgency for financial services to not only better manage the financial and non-financial risks of climate change but also lead the way in sustainable finance. The scale and complexity of the problem demand new thinking and new technologies that will integrate well with existing risk management ecosystems.

In this episode, we’ll explore how AI and advanced analytics can help assess and address climate risk, while keeping the business lights on.

This episode concludes a four-part series examining Responsible AI. Listen to the previous episodes here:

Part One: Alternative Data in Risk Modeling

Part Two: Explainable/Interpretable AI

Part Three: Addressing Bias and Fairness in AI Systems

Learn More: From Crisis to Opportunity: Redefining Risk Management | SAS

Speakers

Mark Nasila, Chief Data and Analytics Officer, FirstRand Risk

Dr. Mark Nasila is the Chief Data and Analytics Officer of FirstRand Risk, a Singularity University Faculty. He is also a steering committee member of the National Institute for Theoretical Physics and Computational Sciences (NITheCS). As an experienced AI and data science expert, he ensures the techniques and methodologies he introduces into FNB are at the forefront of where banking is headed, both locally and internationally. He is the developer and the brain behind Manila, an AI system FNB has harnessed to reimagine its risk management and forensic due diligence processes. He holds a PhD in Mathematical Statistics from the Nelson Mandela University, and is also an alumni of the SingularityU South Africa Executive programme. He was named one of the Corinium Global Intelligence “2020 Global Top 100 Innovators in data and analytics.”

Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS

Terisa Roberts is a well-rounded risk management professional with 15 years of risk management experience working predominantly in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS.

She has extensive experience in risk modeling topics for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks other financial services providers as well as regulators on innovations in Risk Modeling and Decisioning including Artificial Intelligence and Machine Learning.

She holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia with her family.

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Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our podcast series.

About SAS

As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

In this episode, we will continue with part three of a four-part series looking at Responsible AI (Listen to part one: Alternative Data in Risk Modeling and part two: Explainable/Interpretable AI).

“Fairness in AI” is getting a lot of attention, especially related to credit decisioning, not only for onboarding but throughout the credit lifecycle. This episode explores the intersection of fairness and trust, demonstrates why defining - much less ensuring - fairness is more difficult than it sounds, and provides strategies organizations can use to enable fair and trustworthy AI.

Learn More: From Crisis to Opportunity: Redefining Risk Management | SAS

Speakers

Preeti Shivpuri, Head of AI Strategy and Governance, Deloitte Canada

Preeti Shivpuri is a leader in data and analytics strategy helping organizations effectively manage data and information assets to generate insights, elevate customer experience, drive growth and operational efficiency, while meeting evolving regulatory demands. She advises clients on execution strategies and sound governance, enabling them to realize benefits aligned to their business goals throughout their data insights journey. She leads Trustworthy AI and Ethics within Deloitte helping organizations to operationalize and scale AI solution responsibly with the right balance of innovation vs controls.

Kimberly Nevala, Strategic Advisor, SAS 

Kimberly Nevala is a Strategic Advisor at SAS. Kimberly provides counsel on the strategic value and real-world realities of emerging advanced analytics and information trends to companies worldwide. Kimberly is currently focused on demystifying the business potential and practical implications of artificial intelligence (AI) and machine learning (ML).

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Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our COVID podcast series.

About SAS

As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

In this episode, we will continue with part two of a four-part series looking at Responsible AI (Listen to part one: Alternative Data in Risk Modeling).

One of the major challenges with effectively developing, deploying, and managing AI systems are often related to the “black box” nature of the model. Specifically, the complexity and non-linear nature of variables in some black-box AI models may be difficult to explain or understand. This includes explainability of the model logic as well as the individual decisions made by the model. In addition, the relative lack of transparency challenges model development and model validation teams to foresee unintended consequences from model usage, which could create an operational risk if the model is implemented in production.

Speakers

Iain Brown, Ph.D., Head of Data Science, SAS UK&I

Matthew Jones, Ph.D., Head of Retail Decision Modelling, Risk Community, Nationwide Building Society

Moderator:
Lisa Ponti, Ph.D., Vice President, Educational Outreach, Global Association of Risk Professionals (GARP)

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Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our COVID podcast series.

About SAS

As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

In this episode, we begin a four part series looking at Responsible AI by looking at Alternative Data in risk Modeling. Over the course of the coming months we will also look at Explainable / Interpretable AI, Fairness and Bias in AI, and the new frontier of climate models. 

Survey Says: Risk management key to resiliency in 2021 and beyond; click her to learn more and read the full report.

To view GARP's DE&I webcast, "Risk Modeling to Further Diversity and Inclusion", mentioned in this episode - click here. 

Learn More: From Crisis to Opportunity: Redefining Risk Management | SAS

Speaker Bio

Terisa Roberts is a well-rounded risk management professional with 15 years of risk management experience, working predominantly in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS.

She has extensive experience in risk modeling topics for retail and commercial portfolios including regulatory capital, stress testing and IFRS9/CECL. She advises banks, other financial services providers as well as regulators on innovations in Risk Modeling and Decisioning including Artificial Intelligence and Machine Learning.

She holds a Ph. D in Operations Research and Informatics and lives in Sydney, Australia with her family.

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Over the years, GARP and SAS have worked together to bring risk practitioners unique insights on a variety of topics related to financial risk and have partnered on this episode of our COVID podcast series.

About SAS

As a leader in analytics, SAS has more than 40 years of experience helping organizations solve their toughest problems. Our unrelenting commitment to innovation enables banks to modernize and sustain a competitive edge. SAS provides an integrated, enterprise-wide risk-management platform for managing risk in an organization, from strategic to reputational, operational, financial or compliance-related risk management. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk.

Many companies are considering their de-risking options and strategies for pension risk transfer (PRT). PRT is steadily increasing in the U.S. but comes with a high-level liability. Today we speak with Sarvesh Soi, Principal, Wealth Practice at Buck to get insight on the latest strategies around pension de-risking.

Speaker Bio:

Sarvesh Soi, FCA, EA, CFA | Principal, Wealth practice, Buck

Sarvesh serves as the head of the Financial Risk Management group at Buck. He is a seasoned actuary with 19 years of broad and diverse experience in pensions and investments. In recent years, his primary focus has been developing, implementing, and monitoring liability driven investment solutions for defined benefit pension plan sponsors. Sarvesh graduated with a bachelor's degree in actuarial mathematics from the University of Michigan and is an Enrolled Actuary (EA), CFA Charterholder, and a Fellow of the Conference of Consulting Actuaries (FCA). 

Please note that in discussing pension policies during COVID, Mr. Soi intended to say “withdrawal funds” and not “borrow funds.”

To view the video referenced in the discussion, click here.