دورية أكاديمية

Credit Risk Prediction Based on Psychometric Data.

التفاصيل البيبلوغرافية
العنوان: Credit Risk Prediction Based on Psychometric Data.
المؤلفون: Duman, Eren, Aktas, Mehmet S., Yahsi, Ezgi
المصدر: Computers (2073-431X); Dec2023, Vol. 12 Issue 12, p248, 16p
مصطلحات موضوعية: CREDIT risk, DECISION support systems, FINANCIAL management, DISEASE risk factors, CREDIT analysis
مستخلص: In today's financial landscape, traditional banking institutions rely extensively on customers' historical financial data to evaluate their eligibility for loan approvals. While these decision support systems offer predictive accuracy for established customers, they overlook a crucial demographic: individuals without a financial history. To address this gap, our study presents a methodology for a decision support system that is intended to assist in determining credit risk. Rather than solely focusing on past financial records, our methodology assesses customer credibility by generating credit risk scores derived from psychometric test results. Utilizing machine learning algorithms, we model customer credibility through multidimensional metrics such as character traits and attitudes toward money management. Preliminary results from our prototype testing indicate that this innovative approach holds promise for accurate risk assessment. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:2073431X
DOI:10.3390/computers12120248