TITLE:
Application of Precise Loan Qualification Identification Based on K-Means and Decision Tree Model from the Perspective of Consumer Behavior in Universities
AUTHORS:
Yan Fan, Chaosheng Zhang, Xiao Ge
KEYWORDS:
Targeted Loan Disbursement, Student Loans, Consumer Behavior, K-Means Algorithm, Decision Tree Model
JOURNAL NAME:
Journal of Service Science and Management,
Vol.18 No.6,
November
28,
2025
ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models. A questionnaire survey was conducted on 829 students at colleges and universities to collect comprehensive data covering various dimensions such as economic background and consumption patterns. The K-means algorithm successfully predicted and identified the loan eligibility of the samples, with its predictive performance demonstrated by combining it with the decision tree model. Additionally, through in-depth discussions with credit departments, its practical value and reliability were confirmed. This study has enhanced the data-driven intelligent decision mechanism and provided strong support for precise loan disbursement in student loans, paving the way for the application of financial technology in credit areas.