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Modeling of risk losses using size-biased data

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1 Author(s)
E. Yashchin ; IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598, USA

In this paper we present a method for drawing inferences about the process of financial losses that are associated with the operations of a business. For example, for a bank such losses may be related to erroneous transactions, human error, fraud, lawsuits, or power outages. Information about the frequency and magnitude of losses is obtained through the search of a number of sources, such as printed, computerized, or Internet-based publications related to insurance and finance. The data consists of losses that were discovered in the search. We assume that the probability of a loss appearing in the body of sources and also being discovered increases with the magnitude of the loss. Our approach simultaneously models the process of losses and the process of populating the database. The approach is illustrated using data related to operational risk losses that are of special interest to the banking industry.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:51 ,  Issue: 3.4 )