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This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks.

Statistics . --- Risk management. --- Economic theory. --- Bank marketing. --- Applied mathematics. --- Engineering mathematics. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Risk Management. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Financial Services. --- Applications of Mathematics. --- Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Engineering --- Engineering analysis --- Mathematical analysis --- Banks and banking --- Marketing of bank services --- Marketing of banking services --- Marketing --- Economic theory --- Political economy --- Social sciences --- Economic man --- Insurance --- Management --- Economics.