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. Risk modelers have recently been befuddled by rare and powerful non-financial events, including the pandemic, geopolitical conflicts, radical weather happenings, and a supply-chain crisis. What are the characteristics and impacts of these unpredictable incidents? In this podcast, University of Maryland professor and GARP CRO Outlook columnist Clifford Rossi will address these issues, and also share his views on how financial institutions can better understand these risks and link them properly to financial losses.

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. ----------------------- 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). ----------------------- 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) ----------------------- 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. ----------------------- 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.    

Artificial intelligence and machine learning are transforming the ways in which financial institutions manage risk. Driven by a proliferation of data and computing power, institutions are harnessing these tools to build predictive models that enhance decision making. Today, firms are using AI and ML to improve risk management by identifying early warning signals to manage credit risk and providing investment managers with capabilities to interpret unstructured ESG data for portfolio management.    In this podcast, Jeff D’Avignon, from FIS Global, leads a conversation with Riyaz Nakhooda, Vice President of Strategic Partnerships at Accern and Justin Chan, Product Director for FIS’ Cross Asset Trading and Risk business. They discuss the machine learning revolution and what it means for the financial services industry, practical applications of new and emerging technologies, potential challenges to adoption, and their outlook for the future.     Justin Chan, Product Director, Cross-Asset Trading & Risk, FIS Global  Jeff D’Avignon, Senior Sales Executive, Cross-Asset Trading & Risk, FIS Global  Riyaz Nakhooda, Vice President of Strategic Partnerships, Accern   

Over the next two years, driven in part by the economic consequences of COVID-19 and the shift toward work-from-home, financial institutions are expected to pay a lot of attention to credit risk, cybersecurity, ESG, non-financial risks, data management, third-party risk and AI. In this podcast, GARP editorial director Robert Sales discusses these trends and other findings from Deloitte’s recent worldwide risk management survey with J.H. Caldwell - the risk advisory leader for Deloitte’s financial services practice globally.    Speaker Bio J.H. Caldwell is a partner at Deloitte Risk & Financial Advisory, Deloitte & Touche LLP, and serves as the risk advisory leader for Deloitte’s financial services practice globally. In this role, he is responsible for the development of the overall strategic direction of the practice, including helping clients in key areas like digital, technology, financial, cyber, strategic, regulatory and operational risks. He has more than 30 years of experience in the risk space.

Circling back on the issue of cybersecurity after many months of COVID, we speak with Robert H. Rosenzweig, RPLU, a SVP and National Cyber Practice Leader at Risk Strategies on the current environment for cyberthreats, what are the trends/issues firms are facing and implications for risk managers. Topics discussed include: the changing nature of threats, the urgency for firms to build a resilient cybersecurity strategy that incorporates strong data governance and protection, protecting IT infrastructure and systems in the remote work environment, potential financial impacts due to cyber threats and the increased use of cyber insurance to offset risks.   Speaker Bio Robert H. Rosenzweig, RPLU, is a Senior Vice President and the National Cyber Risk Practice Leader at Risk Strategies.  In this role Rob oversees all of the firm’s cyber professionals and works directly with the firm’s clients and prospects on creating comprehensive and customized coverage for their data security, privacy, and errors & omissions exposures. Rob is also responsible for coordinating the firm’s overall cyber strategy nationally.  A published writer and frequent interview subject on cyber liability topics, he also has participated on panels and led seminars on a variety of related topics. Rob currently holds the Cyber COPE Insurance Certification from Chubb & Carnegie Mellon University and a designation as a Registered Professional Liability Underwriter.  Rob received his Bachelor of Arts Degree in Government & Economics from Hamilton College.