Higher spending on telecom services, convenience stores, taxis and cafes is associated with greater credit risk, a new study finds. [Generated using ChatGPT]
Higher spending on telecom services, convenience stores, taxis and cafes is associated with greater credit risk, a new study finds. [Generated using ChatGPT]

A convenience store stop on the morning commute, a coffee run, a taxi hailed on a hot evening after work.

These seemingly trivial, habitual expenditures could be decisive clues that drag down a person's credit rating, according to new empirical research. The findings suggest that individual behavioral tendencies reflected in everyday spending patterns — not just income levels — can serve as key indicators for predicting the likelihood of future loan default.

A column in Hana Financial Focus, a research bulletin published by Hana Financial Research Institute, written by Nam Joo-ha, an emeritus professor of economics at Sogang University, and titled "Spending Behavior and Credit Risk," found that spending data showed a credit-risk prediction accuracy of 65 percent — a level the study deemed sufficiently discriminating even under limited information conditions.

The finding is based on an empirical analysis by Nam's research team using more than 200,000 actual payment transaction records. The results indicate that micro-level consumer spending contains meaningful information for predicting an individual's credit risk.

Among 19 subcategories of spending, borrowers with a higher share of expenditure on telecom services, convenience stores, taxis, and cafes and snacks showed significantly elevated credit risk. By contrast, those who spent more on education, sports and exercise, clothing, and medical and health services carried lower credit risk. Even when the total amount spent is identical, credit assessments diverged depending on where the money went.

When the spending categories were regrouped into eight broader classifications, statistically significant associations were confirmed across five areas: human capital, cultural, physical, essential and other expenditures.

The research team traced the explanatory power of spending data to the concept of capital formation.

Spending on education, exercise, healthcare and cultural activities was seen as building human, physical and cultural capital — investments that can reduce credit risk over the long term by raising labor productivity and boosting income, much like a company's capital expenditure.

Consumptive spending on immediate conveniences — convenience stores, taxis and cafes — was seen as eroding disposable income and ultimately weakening future repayment capacity, thereby raising credit risk.

Nam said that once an individual's spending composition is observed, behavioral traits that are difficult to measure directly — such as time preference, risk aversion and self-control — can be inferred through spending patterns as an indirect indicator," adding that this "provides useful additional information for assessing a borrower's future repayment ability in advance."

Nam argues that spending patterns can serve as a tool to reduce information asymmetry in personal credit markets. He said the empirical finding that spending behavior retains a significant association with individual credit risk even after controlling for income suggests that South Korean commercial banks' current income-centered preferential interest rate policies need to be supplemented with a spending-behavior-based approach.

Nam said incorporating spending patterns to address blind spots in the current preferential interest rate structure could help low-income borrowers, young "thin-file" borrowers with limited credit histories and non-standard workers who struggle to access preferential rate benefits due to relatively low ancillary transaction records.

Nam also said "it would be desirable to substantially overhaul the personal credit scoring system by integrating diverse non-financial data — including health information, telecom records, retail data and digital footprints — rather than relying solely on aggregate financial information."

The Financial Services Commission has launched a credit-scoring reform TF to expand and revamp an alternative credit assessment framework that draws on non-financial data.


ehkim@heraldcorp.com