Analysis of Factors Influencing Credit Insurance Claims at PT Asuransi Kredit Indonesia: A Logistic Regression Approach
Abstract
This study aims to analyze the factors influencing the occurrence of claims in credit insurance at PT Asuransi Kredit Indonesia (Askrindo) using a binary logistic regression approach. The analysis was conducted on 14,331 insurance policy records from the period 2021 to 2024, encompassing variables such as regional classification, insured value, premium, gender, age, credit type, insurance duration, and business source. The results reveal that region, debtor age, and credit type have a statistically significant effect on claim probability, with Region III and debtors aged above 55 exhibiting the highest likelihood of claim occurrence. In contrast, insured value and premium show no significant impact, indicating that the current underwriting process may not adequately reflect default risk. The logistic regression model successfully identified seven significant variables and passed all model fit and multicollinearity tests. These findings carry strategic implications for strengthening credit risk management, particularly in refining underwriting policies, improving debtor creditworthiness assessments, and ensuring financial sustainability amid increasing exposure to MSME guarantee programs.
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EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
