Deep Learning Applications in Valuation and Risk of Trading Books

Antoine Savine, PhD - Superfly Analytics at Danske Bank, Lecturer and Author

Antoine Savine is a French mathematician, academic and leading Derivatives practitioner with Superfly Analytics at Danske Bank --winner of the Excellence in Risk Management and Modelling RiskMinds 2019 award. Antoine previously held multiple leadership positions in quantitative finance, including Global Head of Research at BNP-Paribas. Antoine is an expert C++ programmer and one of the key contributors to Danske Bank's Superfly platform -- winner of the In-House System of the Year 2015 Risk award. He holds a PhD in Mathematics from Copenhagen University, where he teaches Volatility, Computational Finance and Machine Learning in Finance. He is a regular speaker and chairman in professional and academic conferences in quantitative finance, including QuantMinds, RiskMinds and World Business Strategies. Antoine wrote the book on AAD: Modern Computational Finance, John Wiley and Sons, 2018. He is known in the industry for his work on volatility and multifactor interest rate models. He was influential e.g. in the adoption of cashflow scripting, the application of generalized derivatives in the context of local and stochastic volatility models, and the wide adoption of AAD in the financial industry. His current research revolves around deep analytics, the application of artificial intelligence (AI) and machine learning (ML) to risk management. He published 'differential machine learning' with Brian Huge, a novel family of ML algorithms that combine with automatic differentiation (AAD) with spectacular results. Among other applications, the methodology resolves computational bottlenecks with CVA/XVA, FRTB, CCR, MVA and other capital calculations. Antoine will be presenting the latest work and achievements of the department 'Superfly Analytics' at Danske Bank during his ESS talk.