We present an overview of methods to estimate risk arising from operational losses. Our approach is based on the study of the statistical severity distribution of a single loss. We analyze the fundamental issues that arise in practice when modeling operational risk data. We address the...

This paper evaluates several alternative formulations for minimizing the credit risk of a portfolio of financial contracts with different counterparties. Credit risk optimization is challenging because the portfolio loss distribution is typically unavailable in closed form. This makes it...

Purpose – This paper seeks to describe a new approach to analyzing critical resource investment plans, Dynamic Decision Making (DDM), an A.T. Kearney innovation based on a sophisticated modeling process that can improve the quality and transparency of decision making....

This paper explores insurance as a source of financial system vulnerability. It provides a brief overview of the insurance industry and reviews the risks it faces, as well as several recent failures of insurance companies that had systemic implications. Assimilation of banking-type activities by...

Value-at-Risk (VaR) models often are used to estimate the equity investment that is required to limit the default rate on funding debt. Typical VaR "buffer stock" capital calculations produce biased estimates. To ensure accuracy, VaR must be modified by: (1) measuring loss relative to initial...

In this paper, we present an integrated framework for the measurement and management of market and credit risk in fixed income portfolios. The framework based on the Mark-to-Future approach promoted by Algorithmics is used to analyze the contribution of market and credit risk to portfolio risk...