Analyzing the impact of customer compliance on credit collectibility among people's business credit (KUR)

Access to financing remains a major challenge for micro, small and medium enterprises (MSMEs) in rural Indonesia. The People's Business Credit (KUR) program is present as a government effort to expand access to financing, but credit performance, especially the collectability level is still a concern. This study aims to analyze the effect of customer compliance on the level of credit collectibility of KUR recipients in Lekopancing Village, Maros Regency. This research used an explanatory quantitative approach with a sample size of 200 respondents taken by simple random sampling from a population of 415 KUR customers. The data analysis technique used was Structural Equation Modeling (SEM) with the help of AMOS software. The results showed that customer compliance had a positive and significant effect on the level of credit collectibility (standardized coefficient = 0.68; p < 0.001), indicating that the higher the level of compliance, the better the credit quality as reflected in the collectability classification. This finding corroborates the theoretical link between debtor behavior and credit risk management, particularly in the context of rural banking. This study provides an empirical contribution at the micro level that has been under-explored, and emphasizes the importance of improving customer compliance in supporting the sustainability of inclusive financing programs such as KUR. Future research is recommended to explore the application of a mixed-method approach, which combines quantitative and qualitative data, to gain a more thorough understanding of compliance behavior and credit risk.

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Publication Details

Journal
Jurnal Konseling dan Pendidikan
Published
2025-07-01
DOI
https://doi.org/10.29210/1148100
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
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article

Analyzing the impact of customer compliance on credit collectibility among people's business credit (KUR)

Asrin Tandi, Naomi Patiung, Machmud Junaidy
2 links
Jurnal Konseling dan Pendidikan
Impact of AI and Big Data on Business and Society
article

Analyzing the impact of customer compliance on credit collectibility among people's business credit (KUR)

Asrin Tandi, Naomi Patiung, Machmud Junaidy
article en

Abstract

Access to financing remains a major challenge for micro, small and medium enterprises (MSMEs) in rural Indonesia. The People's Business Credit (KUR) program is present as a government effort to expand access to financing, but credit performance, especially the collectability level is still a concern. This study aims to analyze the effect of customer compliance on the level of credit collectibility of KUR recipients in Lekopancing Village, Maros Regency. This research used an explanatory quantitative approach with a sample size of 200 respondents taken by simple random sampling from a population of 415 KUR customers. The data analysis technique used was Structural Equation Modeling (SEM) with the help of AMOS software. The results showed that customer compliance had a positive and significant effect on the level of credit collectibility (standardized coefficient = 0.68; p < 0.001), indicating that the higher the level of compliance, the better the credit quality as reflected in the collectability classification. This finding corroborates the theoretical link between debtor behavior and credit risk management, particularly in the context of rural banking. This study provides an empirical contribution at the micro level that has been under-explored, and emphasizes the importance of improving customer compliance in supporting the sustainability of inclusive financing programs such as KUR. Future research is recommended to explore the application of a mixed-method approach, which combines quantitative and qualitative data, to gain a more thorough understanding of compliance behavior and credit risk.

Jurnal Konseling dan PendidikanVol. 13(2)
Universitas Kristen Indonesia Paulus (ID)
Openalex Percentile: Top 81%
Impact of AI and Big Data on Business and Society
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