MODELING OF THE BANK CLIENTS CREDITABILITY ASSESSMENT BY A ARTIFICIAL INTELLIGENCE METHOD
Journal Title: Проблеми системного підходу в економіці - Year 2018, Vol 3, Issue 65
Abstract
The article examines the existing methods of credit assessing, their shortcomings and advantages. An analysis of approaches to assessing the bank client’s creditworthiness is proved the need to develop a model, which implementation help to analyze all the bank clients and determine the lower limit of creditworthiness, which will be a normative indicator, considering the existing conditions. The basic method for the model that should be the most common and simplest is a scoring estimate. A tool that allows to analyze a large amount of information is the method of data mining. Based on the analysis of shortcomings of existing methods, requirements for the model of credit rating of bank clients are formulated. The method of modeling the bank's creditworthiness assessment with the help of artificial intelligence method is proposed. Approach consists in the identification and analysis of a large number of unstructured information using statistical and mathematical methods in order to obtain new, structured data on the creditworthiness of the bank's clients. The method of using the artificial intelligence method is in this sequence of actions: 1. determination of output quantities; 2. converting categorical data into numeric; 3. implementation of the forecast; 4. estimation of the obtained model using Fisher's coefficient, R-square and Student's coefficient; 5. checking the significance of each factors by constructing the sum of squares matrix and vector products, calculating the standard deviation for each coefficients, t-statistics and p-value of the error. The model is implemented on the real data and its advantages are defined, which consists in the ability to teach the existing model to determine the lower limit of credit based on really existing customer characteristics, which significantly increases the efficiency of determining the bank's insolvent clients.
Authors and Affiliations
D. V. Bilenko, I. G. Syvytska, D. G. Telenkova
Keywords
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