Credit Risks Management Technology

Abstract

AbstractWe describe Risk management technologies for credit risks: task setting; the choice of admissible risk; price for risk; accuracy and robustness of logic and probabilistic (LP) model; transparency of LP-risk model.Building the LP-model of credit risk by the identification method was the first and, perhaps, the most difficult task, which was solved for economics and had all the basic components of Risks management technology.We describe Risk management technology for assessment, analysis and management of the bank credit risk, using the LP-risk model of the LP-classification class. The peculiarities and advantages of the LP-model of LP-classification class are their accuracy, robustness and transparency.All banks are different, as they provide services to different social groups in different cities and regions of the country and enterprises of various industries and sizes, with different forms of ownership. Competing also stimulates the differences of banks.Technology has the following advantages: twice as more precise assessment of good and bad credits, seven times as greater stability of the classification of credits, absolute transparency of the credit risk assessment and analysis, solving the tasks of risk analysis, forecasting and management.KeywordsCredit RiskCorrelation MatriceNatural PersonFailure RiskGood CreditThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.