Analysis of Individual User’s Financial Debt Default -- Based on the Construction of Logistic Regression Model
DOI:
https://doi.org/10.54097/sjz3wd34Keywords:
Financial institution, customer debt default, logistic regression, early warning model.Abstract
As an important part of the economy and society, financial institutions bear the important task of providing financial support and financial services to the real economy. However, due to various reasons, customers of financial institutions may default, which will not only bring economic losses to financial institutions, but may also have a negative impact on the stability of the entire financial system. This article uses Logistic regression to establish a customer debt default warning model, and analyzes and evaluates customer data from financial institutions. It is found that the occurrence of customer defaults is mainly related to the customer's occupation (whether a student) and the customer's balance. Through the establishment of this model, it aims to discover potential financial default customers and help financial institutions reduce the risks caused by debt defaults, which has certain research value and practical significance.
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