Hear from Bo Xu, a Principal at Boston Consulting Group (BCG) and a member of GARP’s Risk and AI Advisory Committee, about GenAI use cases and challenges, as well as its impact on modeling, governance, regulation and risk careers. Even though generative AI is in its early days, its already having a big effect in financial risk management. As a powerful, interactive technology that can understand natural language, quickly search through reams of data and provide human-style answer to questions, GenAI is being used today for everything from data processing to risk monitoring and measurement to quantitative risk modeling. At the same time, financial institutions must decide how to properly govern GenAI, particularly as critics have expressed concerns about data leakage, intellectual property protection and third-party risk. What’s more, there are questions about the impact GenAI could have on risk jobs and about how regulators are going to respond to this innovative technology. Relevant Links: GARP Benchmarking Initiative Risk Intelligence: Technology Section   Speaker’s Bio Bo Xu serves as a Principal at Boston Consulting Group (BCG), where he is a core member of the global GenAI expert team. His professional journey at BCG began in 2019, following a four-year tenure at KPMG in the risk consulting practice, concentrating on CCAR/DFAST model development and validation work. In his role at BCG, Xu leads a multi-disciplinary team focused on AI and GenAI programs. His responsibilities encompass strategy development, AI/GenAI implementation, and change management. He also has expertise in credit risk analysis, model risk management, and data governance from his earlier career.

Hear from Terisa Roberts, Global Head of Risk Modeling and Decisioning at SAS and Sarah Murphy, Principal Director of Accenture Data and AI, as we explore real-time customer decision making and what it means for portfolio monitoring. Thanks to the internet and artificial intelligence, consumers today can make financial decisions through multiple channels, resulting in a new level of competitive pressure for the sector. Financial services firms must make decisions that are not only fast and reliable, but also automated. Real-time customer decisioning plays a pivotal role in achieving these goals throughout the credit value chain, from the point of onboarding (including KYC, credit risk and fraud assessments and marketing) and beyond. Today’s episode will focus on: What are the global trends driving change in customer decisioning in financial services? What problems/challenges are there with conventional approaches? What are the benefits of modernizing your credit decisioning infrastructure? How are forward-thinking organizations deriving concrete business value from their decisioning modernization projects? Links from today’s discussion: SAS and Accenture Risk Model Decisioning Risk-Based Decisioning in an Age of Uncertainty Part 1 Risk-Based Decisioning in an Age of Uncertainty Part 2 Speakers Bios: Terisa Roberts Global Head of Risk Modeling and Decisioning, SAS Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks other financial services providers and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning. Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney Australia   Sarah Murphy, Principal Director, Accenture Data and AI As a Principal Director at Accenture, Sarah leads the growth of Intelligent Decisioning within the Applied Intelligence practice, leveraging 25+ years of risk management and operational experience in financial services and global consulting. ​  Sarah has a proven track record of solving complex risk issues across the credit customer lifecycle, applying predictive analytics and decision management to transform business culture, minimize exposure, increase profitability, and create risk management centers of excellence. She also has a strong executive presence and excellent communication skills, enabling her to partner with clients and stakeholders at all levels and deliver value-added solutions. ​ Passionate about staying at the forefront of the latest trends and technologies in intelligent decisioning, her mission is to help organizations harness the power of data and analytics to optimize their decision making, enhance their customer experience, and achieve their strategic goals.    Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   About SAS SAS is a global leader in data and AI. We help organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. No matter how you prioritize risk, SAS has proven solutions and best practices to help organizations establish a risk-aware culture, optimize capital and liquidity, and meet regulatory demands. SAS® provides on-demand, high-performance risk analytics to ensure greater efficiency and transparency. Strike the right balance between short- and long-term strategies. And confidently address changing regulations and manage compliance.  Discover why 90% of Fortune 100 companies choose SAS to solve their toughest challenges at sas.com/riskmanagement.

Here from Cristian deRitis, deputy chief economist at Moody’s analytics, about the evolution of stress testing, current trends, and the biggest challenges facing banks and regulators. Regulatory stress tests play a vital role in ensuring that large banks hold enough capital to withstand extreme recessions, while internal stress tests at banks are used for everything from capital and liquidity planning to risk monitoring, risk identification and operational resilience. The 2023 failures of a group of mid-sized U.S. banks, however, have led some critics to question whether the Federal Reserve’s annual stress test is broad enough, comprehensive enough and sufficiently proactive – particularly with respect to emerging threats and rare tail risks. Globally, meanwhile, we’ve seen stress testing expand beyond capital and liquidity and into areas like climate risk, which has created a whole new set of hurdles for regulators and banks. In the future, to address perceived flaws, it’s feasible that we could see a broadening of regulatory stress tests and changes to central banks’ approaches to scenarios. Banks, meanwhile, may consider increasing the frequency of their internal tests and expanding their use of AI models to rapidly factor in a wider array of scenarios. Relevant Links: GARP Benchmarking Initiative Modeling Risk (Risk Intelligence column by Cristian deRitis)   Speaker’s Bio Cristian deRitis is Managing Director and Deputy Chief Economist at Moody's Analytics. As the head of econometric model research and development, he specializes in the analysis of current and future economic conditions, scenario design, consumer credit markets and housing. In addition to his published research, Cristian is a co-host on the popular Inside Economics Podcast. He can be reached at [email protected].

Nirav Shah, a founding partner at Versor Investments, speaks with GARP editorial director Robert Sales about the pros and cons of artificial intelligence and machine learning for buy-side institutions. Though significant concerns remain about the bias, fairness an explainability of AI and ML, these innovative technologies have made great inroads in financial services. Banks, for example, now use AI and ML for everything from anti-money laundering to fraud detection to risk modeling and analysis, while asset management firms employ these tools for portfolio optimization and risk mitigation. Nirav Shah discusses the role ML plays in risk reduction and alpha generation at buy-side institutions, and offers his thoughts on, among other topics, data governance and data management challenges, the growth of generative AI, the importance of regulation, and potential future applications of this technology. Speaker’s Bio Nirav Shah is a founding partner at Versor Investments, where he has built innovative, scalable systems for using alternative data and AI/ML techniques. These tools are used in the firm's investment strategies, particularly within the futures and equities markets. He has also worked on various parts of the investment process at Versor, ranging from research to portfolio construction and trading.   He has nearly two decades of experience in quantitative and systematic investment management. Prior to Versor Investments, he founded a consulting firm focused on quantitative research. Earlier, he served as Vice President at Investcorp in New York, where he focused on asset allocation and quantitative research. His career also includes a role as a Quantitative Researcher at Phoenix Global Capital Management, a CTA based in Chicago.

Hear from Daniel Wagner, CEO of Country Risk Solutions, about the complexities of the global geopolitical risk landscape. In these volatile and uncertain times, identifying, measuring and managing geopolitical risk is a daunting task. Everywhere we turn, geopolitical struggles are grabbing headlines, whether we’re talking about, for example, the Israel-Hamas and Russia-Ukraine wars, U.S.-China strategic relations, or Red Sea hostilities. These multi-layered events are having a huge impact across the risk management spectrum, affecting everything from market risk to supply-chain risk to credit risk, cyber risk and liquidity risk. Complicating matters further, they are idiosyncratic and very difficult to predict. Keeping all this in mind, there are certainly still steps that financial risk managers can take to better measure and mitigate geopolitical threats. Our guest speaker, Daniel Wagner, is the perfect person to shed light on today’s complex geopolitical environment and to peer into the future.  Links From Today’s Discussion: GARP Benchmarking Initiative (GBI)®   Speaker’s Bio Daniel Wagner, founder and CEO, Country Risk Solutions Daniel as more than three decades of experience assessing cross-border risk. He is an authority on political risk insurance and analysis and has worked for some of the world’s most respected and best-known companies, including AIG, GE, the African Development Bank, the Asian Development Bank, and the World Bank Group. Until the end of 2023, he was Adaptation Finance Lead and Technical Advisor on Private Capital Mobilization for COP28 in Abu Dhabi. Prior to that, he was Senior Investment Officer for Guarantees and Syndications at the Asian Infrastructure Investment Bank in Beijing and Abu Dhabi. Daniel has published 10 books – Decision-Making in the Polycrisis Era, The Chinese Epiphany, The Chinese Vortex, The America-China Divide, China Vision, AI Supremacy, Virtual Terror, Global Risk Agility and Decision-Making, Managing Country Risk, and Political Risk Insurance Guide – as well as more than 700 articles on current affairs and risk management. He is a regular contributor to such publications as the South China Morning Post, Sunday Guardian, Diplomatic Courier and Fair Observer, among many others. Please see www.countryrisksolutions.com for a full listing of his publications and media interviews.

 In this podcast, Julie Muckleroy, Global Banking Strategist from SAS, and Abraham Izquierdo, Managing Director of Trading and Treasury Risks at Grupo Financiero Banorte, explore the top risk management trends for 2024. With the start of 2024, persistent high interest rates and inflation remain key concerns. Adding to these challenges are potential conflict escalation in the Middle East, threats to global shipping lanes, and historically low water levels in Panama, among others. The fallout from the failure of Silicon Valley Bank and the rapid growth of Generative AI are also being analyzed, impacting both smaller financial institutions' balance sheets in the U.S. and the wider financial landscape.   Speakers’ Bios: Abraham M Izquierdo, FRM: Managing Director of Trading & Treasury Risks at Grupo Financiero Banorte, overseeing balance sheet oversight, policy compliance, hedging strategies, and interest rate risk management. He also manages liquidity risk framework and the Basel III directive, as well as capital management and surveillance for Grupo Financiero Banorte. Julie Muckleroy: Global Banking Strategist in SAS’ Global Industry Marketing organization. With a background in marketing leadership roles at SaaS organizations and large US banks like Bank of America and Wells Fargo, Julie brings extensive knowledge and expertise in global banking trends and marketing strategies. She evaluates the future state of banking as a strategist at SAS. Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   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 Moody’s Analytics’ Cris deRitis about geopolitical risk, cybersecurity, political unease, supply-chain threats, and other key issues that will impact risk managers this year. 2023 was a hectic and extremely challenging year for risk managers. The U.S. regional banking crisis grabbed headlines, with failures being blamed on everything from poor risk culture and ineffective risk modeling to interest-rate volatility – and even to the speed at which news travels in the social media era. Geopolitical risk and supply-chain risk also contributed to an environment of volatility and uncertainty, fueled by the start of a violent conflict between Israel and Hamas, the ongoing Russia-Ukraine war, and attacks on commercial shipping vessels in the Red Sea. Technology, moreover, has evolved, with cyberattacks becoming more sophisticated and more prevalent, and with new innovations – like generative AI – bringing both risks and opportunities. That leads us to today’s topic: namely, how will the remainder of 2024 shake out? What changes may be on the horizon, and which trends will have the greatest impact on the financial risk management landscape? Cris deRitis, the deputy chief economist at Moody’s Analytics, sheds some light on what lies ahead for risk managers.   Links From Today’s Discussion: GBI® survey on energy security risk | Global Association of Risk Professionals (GARP) posted on the topic | LinkedIn https://www.garp.org/garp-benchmarking-initiative https://www.garp.org/risk-intelligence/modeling-risk/all   SPEAKER' 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. Cristian is also a co-host on the popular Inside Economics Podcast. He can be reached at [email protected].

Hear veteran risk manager, advisor and professor Clifford Rossi’s viewpoints on trends, threats and opportunities in the commercial and residential real estate markets.  The past couple of years have been an extremely challenging time for risk practitioners charged with measuring and managing real estate risk. In both commercial real estate and residential real estate, concerns have been raised globally about interest rates, inflation and economic uncertainty. Indeed, in a recent Federal Reserve survey on salient risks – part of the Fed’s October Financial Stability Report – roughly 75 percent of respondents cited the potential for “large losses on CRE and residential real estate.” CRE, more specifically, has been plagued by escalating vacancy rates for office buildings, thanks in part to the remote work trend that started during the pandemic and has since taken off. Residential real estate, meanwhile, has dealt with worries about housing affordability. As a former CRO at multiple banks and as an ex-senior risk manager at Fannie Mae and Freddi Mac, Cliff Rossi, our honored guest today, knows all about the CRE and residential real estate risks facing financial institutions today. Cliff, the current Director of the Smith Enterprise Risk Consortium at the University of Maryland (UMD), speaks with GARP editorial director Robert Sales about global real estate concerns and challenges, and offers advice on how firms can more effectively manage their exposures.   SPEAKER’S BIO: Clifford Rossi (PhD) is the Director of the Smith Enterprise Risk Consortium at the University of Maryland (UMD) and a Professor-of-the-Practice and Executive-in-Residence at UMD’s Robert H. Smith School of Business. He is also the author of GARP’s monthly “CRO Outlook” column. Prior to entering academia, Rossi had nearly 25 years of experience in banking and government, having held senior executive roles in risk management at several of the largest financial services companies. His most recent position was Managing Director and Chief Risk Officer for Citigroup’s Consumer Lending Group, where he was responsible for overseeing the risk of a $300+B global portfolio of mortgage, home equity, student loans and auto loans with 700 employees under his direction. While there he was intimately involved in Citi’s TARP and stress test activities. He also served as Chief Credit Officer at Washington Mutual (WaMu) and as Managing Director and Chief Risk Officer at Countrywide Bank. Previous to these assignments, Rossi held senior risk management positions at Freddie Mac and Fannie Mae. He started his career during the thrift crisis at the U.S. Treasury’s Office of Domestic Finance and later at the Office of Thrift Supervision working on key policy issues affecting depositories. Rossi was also an adjunct professor in the Finance Department at the Robert H. Smith School of Business for eight years and has numerous academic and nonacademic articles on banking industry topics. Rossi is frequently quoted on financial policy issues in major newspapers and has appeared on such programs as C-SPAN’s Washington Journal and CNN’s Situation Room. His book for risk practitioners and graduate students, A Risk Professional's Survival Guide, was published in 2014 by John Wiley & Sons, Inc. His research interests are in financial and nonfinancial risk management, risk governance and analytics and climate risk.

Hear from Wall Street veteran and author Aaron Brown about the impact of fast-evolving technology on risk management. Financial institutions are now using everything from machine-learning modeling and generative AI to blockchain and public-key cryptography for risk monitoring, measurement and mitigation. What’s more, we can see on the horizon the development of other tools – like central bank digital currencies – that could further alter the landscape. However, each of these technologies present their own set of challenges, and it’s important for risk managers to understand both their advantages and potential drawbacks. Aaron Brown, a renowned author and former CRO of AQR Capital Management, has had a front-row seat to the evolution of technology in financial risk management. He joins GARP editorial director Robert Sales to discuss the pros and cons of technological innovations, and to explore what’s on the horizon, drawing on his previous work as a trader, portfolio manager, head of mortgage securities and risk manager for several global financial institutions. SPEAKER'S BIO Aaron Brown teaches finance and mathematics as an adjunct at NYU and writes Risk Intelligence’s monthly “Tech Perspectives” column. He is a distinguished risk manager who has held a variety of high-level positions on Wall Street, dating back to the early 1980s. Most recently, he served for 10 years as chief risk officer of the large hedge fund AQR Capital Management. His books on risk management include The Poker Face of Wall Street, Red-Blooded Risk, Financial Risk Management for Dummies and A World of Chance. In 2011, he was named GARP’s Risk Manager of the Year.

In this podcast Zeynep Salman, Senior Business Solutions Manager at SAS, will explore the top trends and market practices for financial institutions as they adapt to digitizing credit decisioning. We will dive deeply into key success factors for establishing innovative credit customer journeys while achieving successful business outcomes that keep the lending business profitable. We will also discuss how a country’s regulatory requirements and market dynamics can affect the transformation journey. Link from today’s discussion can be found here: The Value of Credit Risk Transformations and the Role of AI   Speaker’s  Bio Zeynep Salman is a credit risk professional with experience managing originations, customer management, and collections teams for consumer and small business portfolios. She joined SAS in 2022 and is currently leading risk decisioning advisory activities across EMEA. Zeynep is passionate about driving automation, seamless customer experiences, convergence of credit and fraud evaluations across customer lifecycle, AI-driven customer engagements, and working with clients to support near and long-term strategic roadmaps to drive value. Before joining SAS, Zeynep held key roles at financial institutions including Citibank, HSBC, Toyota Finance, and UniCredit, as well as software vendors such as FICO.   -----------------------   Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   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

Is it possible for financial institutions to offer on-demand, superior customer experiences while making risk decisions in near real-time in an increasingly digital and interconnected world? That is the question we’ll explore in this podcast featuring Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning at SAS, and Bruce Erb, Director – Credit Risk Consulting, KPMG. Traditional financial institutions are encountering additional hurdles, including fierce competition from agile newcomers, new regulatory demands for operational resiliency, and increased technology risk. In an age of digital lending driven by artificial intelligence, what are modern financial institutions doing differently to remain agile and profitable while keeping costs in check? We’ll delve into several strategies that financial institutions are adopting for risk-based decision-making to bolster their resilience in times of uncertainty.   Speakers   Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks, other financial services providers, and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning. Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia.   Bruce Erb, Director – Credit Risk Consulting, KPMG Bruce Erb has been a risk professional for over 23 years in both industry and consulting. At KPMG, he has supported financial services clients in a variety of risk programs and initiatives with a current focus on transformation of credit and risk governance operating and execution models leveraging alternative approaches including automation, advanced analytics, and cognitive technologies.    Bruce was the product owner and co-inventor of an audit investigation tool that leveraged digitization, automation, and cognitive components to augment the way risk professionals evaluate and score a commercial loan. He was a loan officer for more than nine years before joining KPMG.   -----------------------   Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.   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 veteran risk manager, advisor and professor Clifford Rossi’s perspective on recent turmoil in the banking system, on where risk management fell short, and the profession’s readiness for future challenges. The collapse of Silicon Valley Bank (SVB) and subsequent events inevitably invited comparisons with past crises. It was widely assumed that the damages of 2023 would be more contained than those of the Great Financial Crisis of 2008. But they could similarly leave a long tail, with economic and regulatory repercussions well into the future. A clear parallel between 2008 and 2023 is the spotlight placed on risk management. In the intervening years, the risk function in banking and financial services grew in prestige and responsibility – and its failings were documented as having played a role in SVB’s demise.   Speaker Bio Drawing from regulatory experience early in his career, to senior risk and credit positions at major financial institutions, to his current professorship at the University of Maryland, Cliff Rossi has lived through multiple crises while observing the effectiveness and evolution of risk management. GARP Risk Intelligence’s CRO Outlook columnist, Rossi has been especially critical of boards of directors’ risk governance, one of many timely subjects covered in his podcast conversation with GARP contributing editor Jeff Kutler.

Hear from Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions at SAS, and Professor Robert Jarrow of Cornell University’s SC Johnson College of Business as we continue our discussion of the current banking climate as it relates to integrated balance sheet management — and specifically asset and liability management (ALM). This special two-part podcast series will explore conditions under which a bank is at risk of a “run” by looking internally at their assets and liabilities. We will also consider how to model simulations to project when assets will become negative relative to liabilities and determine how to ensure resiliency within financial institutions. Part 1 of this series will tackle the following topics: Introduction to deposit models for FDIC insurance How to handle hedging and mismatched balance sheets Determining what analytical methods are essential to "doing it right"  An introduction to non-maturity demand deposit runoff that will be a key component for part 2 of this series   Speaker Bios Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions @ SAS He 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.   Robert Jarrow is the Ronald P. and Susan E. Lynch Professor of Investment Management at Cornell University’s SC Johnson College of Business. He is a co-creator of the Heath-Jarrow-Morton (HJM) model, the reduced form credit risk model, and the forward price martingale measure, the standards for pricing and hedging derivatives at major financial institutions. Jarrow is a pioneer of arbitrage-pricing theory and has written seven textbooks and over 225 pieces for academic journals. Jarrow is on the advisory board of numerous academic journals including the Frontiers of Mathematical Finance. His research has won many awards, and he was named IAFE Financial Engineer of the Year in 1997. Jarrow is in the Fixed Income Analysts Society Hall of Fame, Risk Magazine’s 50-member Hall of Fame, is listed in the Who’s Who of Economics, and received Risk Magazine’s Lifetime Achievement Award in 2009. He is currently an IAFE senior fellow and serves on various industry advisory boards.   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

Welcome back for the conclusion of this special two-part podcast series featuring Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions at SAS, and Professor Robert Jarrow of Cornell University’s SC Johnson College of Business. We continue the discussion of the current banking climate as it relates to integrated balance sheet management — and specifically asset and liability management (ALM). Part two of this series will tackle the following topics: A further exploration of non-maturity demand deposit runoff Deeper understanding of the estimated default probabilities for a bank that funds investments in Treasury securities with deposits Examples of how those default probabilities vary by maturity and the bank's initial capital position Tangible actions for aligning your balance sheet and optimizing your risk profile    Speaker Bios Dr. Donald van Deventer, Managing Director--Risk Research and Quantitative Solutions @ SAS He 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.   Robert Jarrow is the Ronald P. and Susan E. Lynch Professor of Investment Management at Cornell University’s SC Johnson College of Business. He is a co-creator of the Heath-Jarrow-Morton (HJM) model, the reduced form credit risk model, and the forward price martingale measure, the standards for pricing and hedging derivatives at major financial institutions. Jarrow is a pioneer of arbitrage-pricing theory and has written seven textbooks and over 225 pieces for academic journals. Jarrow is on the advisory board of numerous academic journals including the Frontiers of Mathematical Finance. His research has won many awards, and he was named IAFE Financial Engineer of the Year in 1997. Jarrow is in the Fixed Income Analysts Society Hall of Fame, Risk Magazine’s 50-member Hall of Fame, is listed in the Who’s Who of Economics, and received Risk Magazine’s Lifetime Achievement Award in 2009. He is currently an IAFE senior fellow and serves on various industry advisory boards.   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 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.