Аналитические модели для решения задачи классификации данных

Credit risk management is the main task of banks and other credit institutions. Untimely partial or complete non-repayment of the loan body, as well as the interest part, within the period established by the agreement and in compliance with all the conditions provided for, is one of the main causes of losses of financial institutions. Data mining technologies contain effective tools for building scoring models – neural networks, decision trees, and logistic regression to predict the value of the target variable that allows you to assess the creditworthiness of the client. The purpose of this article is to show the relevance of the problem of data classification on the example of the financial and credit sphere (credit loan).