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Data Science Seminar Speaker: Arjun Beri, Wells Fargo Date: Tuesday, 9 April 2024 Time: 3:30 to 4:30 PM Venue: NKN hall Introduction to Counterparty Credit Risk Modelling and the Challenges Arjun Beri Wells Fargo. 09-04-2024 Abstract The aim of this talk is to briefly introduce the theory and practice around counterparty credit risk (CCR) modelling. Counterparty credit risk refers to the risk that counterparty to a financial contract will default on its obligations prior to the maturity of the contract, exposing the other side to financial losses. Only OTC (Over-the-counter) derivatives and SFT (security financing transactions) are susceptible to counterparty credit risk. Exchange-traded derivatives are not affected by this risk, since an exchange guarantees the cash-flows to both the counterparties. We will focus on the counterparty credit risk framework for computation of credit exposure and pricing of counterparty credit risk. For the exposure estimation, we will introduce various concepts, such as netting agreements, collateralized trades and margin agreements as risk mitigants; and introduce the concept of aggregating counterparty credit risk exposure at a trade- or portfolio-level. Furthermore, the pricing of counterparty credit risk leads to introduction of Credit Valuation Adjustment (CVA), a critical quantity associated to the pricing and hedging of OTC derivatives and SFT trades. We will also discuss the real-world challenges with the implementation of CCR and mention the utility of Machine Learning based models in estimation of counterparty credit risk exposures. Finally, we will briefly discuss the key risk and banking regulations relevant to counterparty credit risk management. About the speaker: Arjun Beri heads the Stress Testing & Balance Sheet Model Validation, as well as the Capital Market Model Validation function within Corporate Model Risk division at Wells Fargo India & the Philippines. Arjun is an applied mathematician with research interests in stochastic modelling, computational programming and quant finance. Following completion of his MS in Quantitative Finance and PhD in Applied Mathematics from University of Houston, Houston, Texas; he started his professional journey working as a postdoctoral fellow on a collaboration between Credit Agricole and Department of Mathematics, University of Houston; and then working as an NSF Postdoctoral Fellow with Mathematical Biosciences Institute at the Ohio State University, Columbus, Ohio in US. He carried out research on developing mathematical model for emergent properties observed in social insect dynamics, high-dimensional models for biochemical reaction networks, Stochastic Volatility Modelling, and developing algorithms to monitor automated trading portfolios. Arjun is an alumnus of St. Stephen’s College, Delhi University, where he obtained an undergraduate degree in Mathematics. Prior to joining Wells Fargo, he had a stint with CRISIL (an S&P Global Company) working and leading consulting projects in Risk Analytics with multiple US & European banking institutions. He then moved to lead a team of quants at Nomura, Mumbai, India, developing mathematical models for counterparty credit risk exposure calculations in Over-the-counter derivatives. Arjun has published original research papers in applied mathematics and finance in top international journals, including, Journal of Statistical Physics, Quantitative Finance, etc. To unwind, he occasionally cooks, reads/collects books, listens to music, paints, plays sports, watches world cinema while dabbling in scriptwriting.
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