Contents included 18 chapters : 1. Introduction to Operational Risk Management and Modeling 2. Random Variables, Risk indicators, and Probability 3.Expectation, Covariance, and Correlation 4.Modeling Central Tendency and Variability of Operational Risk Indicators 5.Measuring Skew and Fat Tails of Operational Risk Indicators 6.Statistical Testing of Operational Risk Parameters 7.Severity of Loss Probability Models 8.Frequency of Loss Probability Models 9.Modeling Aggregate Loss Distributions 10.The Law of Signtificant Digits and Fraud Risk Identification 11.Correlation and Dependence 12.Linear Re gression in Operational Risk management 13.Logidtic Regression in Operational Risk management 14.Mixed dependent Variable Modeling 15.Validating operational Risk Proxies Using Surrogate Endpoints 16.Introduction to Extreme Value Theory 17.Managing Operatiobal Risk with Bayesian Belief Networks 18.Epilogue