The Bayesian approach to analysis of financial operational risk
Abstract
The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of using the tool to solve practical problems of operational financial risk estimation. The study results can be used by financial institutions as a tool for resolving specific practical issues of risk estimation.
The object of research: methods for constructing Bayesian Networks for modeling operational risk in financial institutions.
Investigated problem: modeling operational risk under conditions of uncertainty.
The main scientific results: overview of methods for constructing Bayesian Networks for modeling operational risk under conditions of uncertainty; the methodology in the form of sequence of actions necessary for creating the model in the form of the network; methods for computing a probabilistic output in BN; examples of applying such approaches to solve practical problems of operational financial risk estimation.
The area of practical use of the research results: The research results can be used in the following financial institutions: banking system, insurance and investment companies.
Innovative technological product: computer based decision support system, allowing for high quality modeling and estimation of operational risks.
Scope of the innovative technological product: the practice of usage the proposed models in financial organizations provides an evidence of their high efficiency in terms of formal description and estimation of operational risk
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References
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