Open AccessCredit rating of natural person by expert knowledge compilation in logic basis of neural networks
Author(s) -
Ramin Rzayev,
Alovsat Aliyev,
O Ja Kravets
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/537/4/042028
Subject(s) - solvency , computer science , ranking (information retrieval) , artificial neural network , expert system , artificial intelligence , basis (linear algebra) , heuristic , natural (archaeology) , machine learning , business , mathematics , finance , geometry , market liquidity , archaeology , history
The paper discusses the combined use of expert systems and neural network to evaluation the solvency of natural person. Corresponding comprehensive approach to individual credit rating is proposed by compilation of the expert and/or heuristic knowledge about the estimates of the solvency of potential borrowers under uncertainty. Obtained expert estimates of the current solvency of individuals are based on the preliminary expert estimate of influence factors for their ranking and the weights of their relative influence. Adequate translation of the external knowledge relative to weighted summary estimates of natural person solvency in effective internal knowledge is compiled in the logical basis of a multi-layer feedforward neural network.