Patent ID: 7409357

Claim:
A computer-readable medium storing a program, said program directing a computer to measure an operational risk of an institution by executing the steps comprising of: inputting multi-dimensional loss data, a plurality of analysis nodes thereby being formed by said multi-dimensional loss data, wherein a plurality of node inputs are provided corresponding to said analysis nodes; performing a data analysis for each of said analysis nodes using at least one of a Q-Q plot or a mean excess function for each of a frequency distribution and a severity distribution; including expert loss data for at least one of said analysis nodes in response to said data analysis, a weight being assigned to said expert loss data; selecting one of a plurality of advanced measurement approaches to model said loss data at said analysis nodes, said advanced measurement approaches comprising at least a loss distribution approach and a scorecard approach, wherein different of said advanced measurement approaches are selectable for different of said analysis nodes; calculating said plurality of advanced measurement approaches, wherein multiple models of said loss data are calculable for each of said analysis nodes, wherein calculating said loss distribution approach comprises at least modeling a frequency distribution with a Poisson distribution or a negative binomial distribution, separating low severity events and high severity events in a severity distribution with a Hill estimator, modeling said low severity events with a log normal distribution and modeling said high severity events with a generalized Pareto distribution, and determining an user bound for losses using Chebychev's inequality, and wherein calculating said scorecard approach comprises at least using Bayes transformations to incorporate new loss data into an existing loss estimation; calculating the effect of insurance coverage for each of said analysis nodes; performing a sensitivity analysis for each of said analysis nodes by changing a mean of the frequency distribution and a parameter of the severity distribution by at least 10%; defining aggregations, said aggregations being defined by structures aggregating said analysis nodes; calculating a value at risk of said aggregations, said calculated value at risk being calculated in response to said advanced measurement approaches selected for said analysis nodes; and outputting said calculated value at risk.