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Abstract Context. The problem of credit assessment of a client is considered. It is a simultaneous processing of lender’s data of different nature with further definition of the credit rating. The object of this study was the process of lending to individuals by credit institutions. Objective. The purpose of the work is to study the process of improving the quality of lending through the development and use of a scorecard model. Method. An analytical review of the domain area was conducted. A business process model for assessing clients’ creditworthiness in the form of an IDEF0 diagram is developed. Dedicated groups of indicators characterizing a potential lender from different directions. Selected sets of values for each indicator of credit separately. The methods of solving the problem of clients’ creditworthiness are analyzed. Selected Bayesian naive classifier as a method for solving the problem of classification of potential lenders. The existing information systems for assessing the creditworthiness of clients are analyzed. A scoring model for assessing credit ratings by the client in the form of an algorithm is developed. The list of functional requirements of the information system, which is presented in the form of a use case diagram is determined. Three-level architecture for the information system is proposed. A database model has been developed to preserve customer information. An information system was developed for determining the credit rating of a client based on the developed scoring model. Numerous studies have been conducted to determine the class of a potential creditor. The process of determining the quality of credit activity is analyzed. Quality indicators for assessing the creditworthiness of clients are selected. The method of calculating the quality of credit activity is offered. Results. The scoring model was developed, which was used in solving the credit assessment of clients through the help of the proposed information system. The process of improving the quality of credit rating is investigated. Conclusions. The conducted experiments have confirmed the proposed scoring model and allow recommending it for use in practice for assessment process of client creditworthiness. Scientific novelty is to improve the process of credit activity by automating the use of naïve Bayes classifier, which reduces the human factor in decision-making. Author Biographies K. V. Melnyk, National Technical University “Kharkiv Polytechnic Institute”, Kharkiv PhD, Associate Professor of the Department of Software Engineering and Management Information Technologies N. V. Borysova, National Technical University “Kharkiv Polytechnic Institute”, Kharkiv PhD, Associate professor of the Department of Intelligent Computer Systems References Bank Lending Survey [Electronic resource] / Access mode:https://bank.gov.ua/control/en/publish/category;jsessionid=4

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