The probabilistic behavior of the claim severity variable plays a fundamental role in calculation of deductibles, layers, loss elimination ratios, effects of inflation, and other quantities arising in insurance. Among several alternatives for modeling severity, the parametric approach continues...

Over the last decade, researchers, practitioners, and regulators had intense debates about how to treat the data collection threshold in operational risk modeling. For fitting the loss severity distribution, several approaches have been employed: the empirical approach, the “naive” approach,...

Over the last decade, researchers, practitioners, and regulators had intense debates about how to treat the data collection threshold in operational risk modeling. There are several approaches under consideration --- the empirical approach, the "naive'' approach, the shifted approach, and the...

Financial institutions manage operational risk by carrying out the activities required by regulation, such as collecting loss data, calculating capital requirements, and reporting. The information necessary for this purpose is then collected in the OpRisk databases. Recorded for each OpRisk...

Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult task. In this paper, we demonstrate how this can be successfully accomplished when losses follow the multivariate Pareto distribution of the second kind, which is an attractive...

We introduce and explore Gini-type measures of risk and variability, and develop the corresponding economic capital allocation rules. The new measures are coherent, additive for co-monotonic risks, convenient computationally, and require only finiteness of the mean. To elucidate our theoretical...

Determining aggregate risk capital has become a fundamental problem in modern Enterprise Risk Management, and the determination process has been fairly well studied. The consequent exercise of allocating the aggregate risk capital to constituents has also been given high priority in, e.g., both...