Risk Management in Bank: Fuzzy Inference Based Process Model

Abstract

Any commercial bank (CB) is trying to determine the degree of acceptable risks of material and/or reputational losses, believing that its potential losses are inversely proportional to the volume of its capital. Therefore, the basis of successful banking is the presence of a Risk Management System (RMS) in the CB structure, the main task of which is to determine the best (or rational) strategy for concluding transactions that ensures maximum profit growth. Within the RMS the statistical analysis tools are used that allow to evaluate and compare the consequences and expediency of certain transactions by establishing a quantitative measure of banking risk from any transaction. Moreover, these tools make it possible to formalize various transactions and, thereby, ensure the accumulation of CB experience. To form heuristic knowledge from the history of the conclusion of various contracts, it is necessary to use and accumulate expert opinions, and, as a result, fuzzy methods of analysis and decision-making relative to banking transactions. There is a system of fuzzy models for assessing internal and external banking risks is considered. This approach involves the use a fuzzy cognitive model, based on which cause-effect relations for assessing banking risks at all levels of the hierarchy of their detailing are described using the Fuzzy Inference Systems. Qualitative evaluation criteria for the areas of localization of banking operations and external influences are used as inputs and outputs.