title: ÐÑÐµÐ½ÐºÐ° Ð¿Ð»Ð°ÑÐµÐ¶ÐµÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ð¾ÑÑÐ¸ ÐºÐ»Ð¸ÐµÐ½ÑÐ¾Ð² Ð±Ð°Ð½ÐºÐ° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Assessment of the solvency of bank customers using machine learning methods
Creators: name: ÐÐ¾Ð¿Ð¾ÑÐ¾Ð²Ð°, Ð®Ð»Ð¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÑÐºÐ¾ÑÐ¸Ð½Ð³
Ð»Ð¾Ð³Ð¸ÑÑÐ¸ÑÐµÑÐºÐ°Ñ ÑÐµÐ³ÑÐµÑÑÐ¸Ñ
ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ
ÑÐ»ÑÑÐ°Ð¹Ð½ÑÐ¹ Ð»ÐµÑ
scoring
logistic regression
classification
random forest

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description: Theme of final qualification work: "Assessment of the solvency of bank customers using machine learning methods". This work is devoted to the study of approaches to assessing the solvency of bank customers using machine learning methods. Tasks that were solved during the study: Review of the literature on the use of machine learning in the banking sector; Study and preparation of a data set for subsequent analysis; Construction of solvency assessment models using machine learning methods. The work was carried out using the R language and the R Studio integrated development environment, where a significant part of the research was carried out. It contains a preliminary analysis of the data set, attribute values are converted to the correct data type, and the structure of the data set is shown. Solvency assessment was carried out using classification methods such as logistic regression, the method of support vectors, the algorithm of a random forest and the algorithm of decision trees. As a result of the work done, four machine learning methods were applied to solve the task. For each model, graphs of ROC curves are obtained, showing the quality of the predicted model. Additionally, the quality metrics of the obtained models are given, on the basis of which the choice of the best model is made.