Beyond Bureau Scores: Rethinking Credit Underwriting in India | Author: Vivek Singh, Vice President of Products at IDfy

Authored Article: Vivek Singh, Vice President of Products at IDfy

The future of underwriting is set to diverge sharply from traditional methods. In the next five years, underwriting will not only rely on data-driven models but will also adopt more granular approaches for pricing and risk differentiation. This shift reflects a move towards forward-looking assessments that better capture borrowers' true financial potential and future risk, leaving behind the limitations of conventional credit bureau scores.

Limitations of Traditional Bureau Scores

Traditional credit scores, once an important factor when financial data was limited, have now become increasingly inadequate in India's evolving financial landscape. With less than 30% of Indian adults covered by formal credit records, many borrowers are labeled as “thin file,” leaving potentially creditworthy individuals and MSMEs overlooked. Additionally, bureau scores are backward-looking, assessing past payment behavior rather than current financial stability, which limits their ability to accurately predict future risk. This outdated model excludes upwardly mobile borrowers and hinders MSME growth.

Rethinking Traditional Credit Scoring Methods

Today, bank statements show cash flows, deposits, and spending habits. This can offer a more accurate and predictive view of a borrower’s financial health than static credit scores. This real-time data enhances lenders' ability to assess repayment capacity and serve a wider segment of the population more effectively.

So what will the next 5 years look like for underwriting?

Transaction data becoming a primary indicator of financial health

Bank statements now provide a clearer view of cash flows, deposits, and spending habits, offering a more accurate, predictive assessment of a borrower’s financial health than static credit scores. This real-time data enhances lenders' ability to evaluate repayment capacity and serve a broader population.

In time, lending institutions will increasingly rely on high-frequency financial data to assess applicants. With formalized transactions, all sales and purchases are visible in GST records and can be thoroughly verified in bank statements. These 2 data points can easily reveal the level of stress or buffer an MSME is operating in. These insights are not captured by traditional credit reports or financial statements. By focusing on “liquidity,” “margin,” and “top-line growth,” lenders can assess MSMEs in ways that were previously reserved for corporate bankers to differentiate between good and bad companies. Regular inflows and disciplined spending patterns will be key indicators of future creditworthiness, especially for those without a lengthy credit history but strong financial practices. In the next five years, cash-flow-based lending will dominate the MSME lending ecosystem.

Account Aggregators and ULI becoming key tools for credit operators

The Indian government is fostering data-driven lending through the 

• Account Aggregator (AA) framework that empowers consumers to share financial data securely 

• Unified Lending Interface (ULI), aims to be the “UPI of lending.

These initiatives enable secure sharing of bank statement data, creating a more responsive and inclusive credit ecosystem. While some skepticism exists, fintechs are building more use cases around this public infrastructure to enhance lending. With growing adoption, AA and ULI will become core data platforms around which credit processes will be designed. Lenders, working with tech providers to interpret data, will leverage data science to make model-based decisions. This will enable customized pricing, improving risk-adjusted returns for lenders and offering the best pricing to borrowers.

Shift from simple scorecards to advanced explainable models

Currently, most lenders rely on scorecards, which are very basic and rely heavily on demographics and bureau variables. However, with AI and advanced statistical tools becoming mainstream, these scorecards will be replaced by AI models for decision-making. Significant efforts will be made to ensure these models are explainable to regulators. This shift will not only make credit operations more efficient but also allow lenders to forecast their books under various stress scenarios. While Indian lending has been traditionally cautious, this forecasting ability will enable better-informed risk-taking, leading to improved return on assets.

Global Insights: Lessons from Jumo and Sesame Credit

Here are some international examples that highlight how alternative data expands credit access. 

African fintech Jumo uses mobile and transaction data to offer credit to millions of unbanked customers. China’s Sesame Credit has built an expansive credit ecosystem by tapping into online behaviors and social interactions.

Despite privacy concerns, both models demonstrate that broadening the spectrum of data can improve risk assessment and promote inclusivity.

Bridging the Credit Gap for Retail and MSME Borrowers

India’s credit gap highlights the flaws of traditional scoring methods. Estimates suggest that the MSME credit gap ranges between Rs 20 to 25 lakh crore, reflecting the substantial under-penetration of formal lending channels. Similarly, many retail borrowers remain underserved due to rigid underwriting that doesn’t capture their financial resilience. By adopting a model that combines bank statement analysis and alternative data, lenders can better assess creditworthiness more accurately and expand access to formal credit for millions.

Conclusion

The future of credit underwriting in India requires a shift from traditional bureau scores to real-time bank data and alternative behavioral metrics. By embracing real-time bank statement data and alternative behavioral metrics, lenders can develop more nuanced and inclusive risk models. This approach enhances underwriting accuracy and expands credit access for underserved borrowers and MSMEs. With strong government support, Indian lenders are poised to adopt forward-thinking models that promote financial inclusion and sustainable economic growth.