Research Article
A Modelling Consumer Credit Risk Using Survival Analysis: A District-level Study from Badulla, Sri Lanka
Issue:
Volume 11, Issue 4, December 2026
Pages:
90-97
Received:
5 August 2026
Accepted:
17 August 2026
Published:
6 November 2026
DOI:
10.11648/j.mma.20261104.11
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Abstract: Credit risk models in many rural lending settings are still largely static, focusing on whether default occurs rather than when it occurs. This study develops a time-to-event (survival) framework to analyze the timing and determinants of consumer-loan default in the Badulla District of Sri Lanka. Using microdata on consumer instalment loans originated between January 2015 and December 2020 (followed up to end-2020), loans were modelled in months from loan origination to first default (≥90 days past due), early full settlement, or right-censoring. Kaplan–Meier estimates and log-rank tests were used to describe overall loan survival and compare survival patterns across borrower and loan groups. Kaplan–Meier results show high early survival at 12 and 36 months (S (12) =0.943, S (36) =0.938) followed by a pronounced deterioration after four years, with survival falling from S (48) =0.923 to S (60) =0.343. A multiple Cox proportional hazards model was estimated using 1,168 loans. Education was a consistent determinant: compared with higher education, primary, secondary, and tertiary (non-degree) groups had significantly higher hazards of default. Higher interest rates and lower income categories were associated with elevated default hazards. Model diagnostics suggested that the proportional hazards assumption was broadly reasonable for most covariates, but collateral exhibited time dependence. Furthermore, the findings highlight a critical risk window beyond 48 months and support strengthening monitoring, borrower support, and risk-based pricing for vulnerable groups in rural Sri Lankan credit portfolios.
Abstract: Credit risk models in many rural lending settings are still largely static, focusing on whether default occurs rather than when it occurs. This study develops a time-to-event (survival) framework to analyze the timing and determinants of consumer-loan default in the Badulla District of Sri Lanka. Using microdata on consumer instalment loans origina...
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,
Chathuri Lakshika Jayasinghe
