Speaker "Jeffrey Bohn" Details Back



Balancing model performance with complexity in real-world analytics applications


Although progress in data science and analytics have vastly improved the possibilities for better decision-making in rich and complex fields such as portfolio-risk management and organizational development, communicating meaningful output often results in complex reports and dashboards appreciated only by “quants.” Improved model performance often comes at the cost of increased complexity in model implementation and interpreting/communicating analytical output. Quantitatively-informed—but not quantitatively-trained—business and policy leaders often ignore important analytical output they don’t understand. This presentation will explore how to determine when model complexity is justified and how to use increasingly complicated models to improve decision making in large organizations.


Dr. Bohn is Chief Science Officer at State Street Global Exchange. He leads GX Labs in San Francisco. Prior to his current appointment, he established the Portfolio Analytics and Valuation Department within State Street Global Markets Japan in Tokyo. (He is fluent in Japanese.) He previously ran the Risk and Regulatory Financial Services consulting practice at PWC Japan. Prior to PwC, he co-founded Soliton Financial Analytics (SFA) in Hong Kong and Soliton Japan in Tokyo. Dr. Bohn often conducts seminars on topics ranging from credit instrument valuation to active credit portfolio management. He has published widely in the area of credit risk. He co-authored with Roger Stein Active Credit Portfolio Management in Practice (Wiley, 2009). Dr. Bohn is an affiliated researcher at U.C. Berkeley’s Center for Risk Management Research. On occasion, he teaches financial engineering at U.C. Berkeley, National University of Singapore’s Risk Management Institute and Tokyo University.