Case Article—Quantifying Operational Risk in Financial Institutions

Risk management is essential in today's business environment for banks and other financial institutions to survive in highly competitive and volatile markets. As the subprime mortgage debacle of 2008 has shown us, risk management, or the lack thereof, affects more than just the individual institution. Hence, banks and other financial institutions are subject to frequent reviews by federal regulators. The regulatory reviews require that the institutions set aside capital (cash reserves) to offset the potential risk of loss that they face every day. This case study focuses on a large regional bank, for which we use the pseudonym A Bank, and guides students through developing a risk model for operational risk. The students develop their models using maximum likelihood estimation, goodness-of-fit testing, convolution of distributions, and order statistics. The pedagogical objectives of the case study include applying statistics to a real-world problem while establishing connections among statistics, optimization, and simulation. The case can be used in different disciplines such as engineering (e.g., an engineering statistics class) or business (e.g., a hybrid operations research/statistics MBA class or an elective class on quantitative finance) and for graduate or undergraduate education by changing the intensity of the technical skills required and by using a different mix of case documents.

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