Modeling of Risk Losses Based on Incomplete Data

In this article we present a method for drawing inference about the process of losses experienced in relation with operations of a business. For example, for a bank such losses could be related to erroneous transactions, human error, fraud, harassment lawsuits or a power outage. Information about frequency and magnitude of losses is obtained through search of a number of sources, such as printed or Internet based publications related to Insurance and Finance. The data consists of losses that were discovered in the search; it is assumed that the probability of a loss to appear in the body of sources and be discovered increases with its magnitude. Our approach is based on simultaneous modeling of the process of losses and the process of data base construction. This approach is illustrated based on data related to operational risk losses.

By: Emmanuel Yashchin

Published in: RC23676 in 2005


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