Modeling of Bank Credit Risk Management Using the Cost Risk Model

This article deals with the issue of managing bank credit risk using a cost model. Modeling management was proposed based on neural-cell technologies, which expand possibilities modeling complex objects and processes provide high reliability determination. The purpose is to improve develop methodical support practical recommendations for reducing level value-at-risk (VaR) methodology its subsequent combination methods fuzzy programming symbiotic support. model makes it possible create decision subsystems nonperforming loan neuro-fuzzy approach. For this paper, economic mathematical tools (based VaR methodology) were used, made analyze forecast dynamics overdue payment; assess quality portfolio bank; determine trends in development. A scientific approach taken degree problematicity by qualitative criteria technology, can increased default at an early stage process monitoring forecasting changes change indicators. analysis indicators troubled debt, should be implemented as software included system during bank’s portfolio.