|Title of the article||
COMPARATIVE ANALYSIS OF RISK IDENTIFICATION MODELS
Moiseev Aleksandr Vladimirovich, Candidate of physical and mathematical sciences, head of sub-department of applied mathematics and operations research in economics, Penza State Technological University (1a Baydukova passage, Penza, Russia), email@example.com
Background. The interest to models of risk identification relates to the desire to automate management decision making inconditions of risks when the account of the averaged end result is insufficient. At the present time there are several approaches to risk assessment. In every particular case it requires comparison of models by quality of identification. The study is aimed at consideration of model comparison procedure. In the work the comparison of various models is carried out for concrete results obtained on the basis of real statistics of a bank using the algorithm suggested by the authors.
Recognition System Risk, Credit risk, discriminant analysis, logit model, probit model.
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