India’s Next Credit Boom Must Not Become a Borrower Trap

By Smita Aggarwal

India is entering a new phase of household credit. Formal lending is moving beyond metros and salaried borrowers into smaller towns, informal-income households, gig workers, micro-entrepreneurs, and new-to-credit customers. This is both necessary and desirable. A growing economy needs households to have access to credit for homes, education, vehicles, working capital, and income smoothing. Used well, credit is not merely consumption brought forward; it can be a bridge to higher future income.

However, the next credit boom must be judged by a tougher standard than loan growth alone. As formal lending moves deeper into small-ticket and new-to-credit segments, the real test of inclusion is not how fast loans are disbursed, but whether borrowers can repay without distress.

India has room for household credit to grow. Household debt remains lower than in many peer economies, and a significant share of borrowing is linked to housing, vehicles, education, agriculture, and business activity. The opportunity is real: first-time borrowers in tier-2 and tier-3 markets are no longer invisible. Digital payments, credit bureaus, account aggregators, goods and services tax (GST) trails and bank-statement analytics now make it possible to understand cash flows that once sat outside the formal credit file.

However, that also makes the lender’s task more complex. The old model of lending against collateral, salary slips and bureau history does not travel neatly into a world of uneven incomes and thin files. A shopkeeper may have healthy daily cash flows but weak documentation. A gig worker may earn well, but irregularly. A first-time borrower may have no score but a reliable payments history. Equally, a borrower juggling several app-based loans may look current today and strained tomorrow. Inclusion at scale, therefore, requires underwriting that is more calibrated, more technology-led, and far more customer-centric.

The first priority is to move from lending based mainly on past history to lending based on actual repayment capacity. India’s digital public infrastructure can make this assessment more evidence-based. With explicit consent, account aggregators can provide source-verified bank transaction data; Unified Payments Interface (UPI) histories, GST trails, bureau records and bank-statement analytics to build a picture of monthly inflows, fixed expenses, equated monthly instalments (EMIs), bounced payments, overdraft use, seasonality, and cash buffers.

AI models can then assess whether income is stable, rising or volatile; whether loan-like outflows are crowding out essentials; and whether the proposed EMI leaves enough room for rent, food, school fees, medical needs, and business expenses. In other words, affordability has to be judged through the rhythm of a household’s real cash flows, not only through salary slips or self-declared income.

Second, product design must move away from one-size-fits-all credit. A small business loan, an education loan and an emergency consumption loan do not have the same purpose, risk profile or effect on the borrower’s financial life. Flexible tenures, step-up or step-down EMIs, repayment pauses linked to verified shocks, and credit lines that expand only with demonstrated repayment behaviour can make credit growth safer. This becomes even more important as credit line on UPI begins to sit inside everyday payments. A carefully framed enabling provision that allows well-regulated non-banking financial companies (NBFCs) to also offer such products, with appropriate guardrails on underwriting, disclosures and pricing could widen responsible access without losing sight of borrower protection. For now, credit line on UPI remains bank-led, so, a calibrated opening for NBFCs could widen access responsibly.

Third, lenders need early-warning systems that intervene before default. The current model often waits for a missed payment and then moves to collections. A better approach would be to identify stress earlier: declining balances, frequent overdrafts, new loan-like outflows, repeated top-ups, rising credit-card revolvers, or a sudden fall in regular income credits. With consent and privacy safeguards, artificial intelligence (AI) and account aggregator data can help lenders offer support before delinquency sets in, whether through temporary restructuring, counselling, limit reductions, tenure adjustments, or a pause on additional credit.

Fourth, customer protection must be built into the credit journey itself. Borrowers should be able to see the true annual cost of credit, the total repayment amount, penalty charges, and the consequences of default in simple language and in local languages, too. Digital consent should be meaningful, not a box-ticking exercise. Collections must remain dignified and rule-bound. The lesson from other digital-credit markets is not that formal credit should slow down, but that speed should not outrun suitability.

Borrower financial health should remain the central measure of success rather than focusing on just repayments. A financially healthy borrower has enough income left after repayments for essentials and emergencies; is not rolling over short-term loans to repay older ones; is not borrowing from multiple apps simply to stay afloat; and is building savings, assets or earning capacity through the loan. For lenders, that means tracking outcomes beyond disbursal and delinquency: whether debt-service burdens remain manageable, whether liquidity buffers improve, whether repeat borrowing is for growth rather than distress, and whether the borrower’s income trajectory strengthens after taking credit.

The next frontier of financial inclusion is not simply reaching more borrowers. It is reaching them with credit that fits their lives and improves resilience. India’s digital public infrastructure gives lenders an unusual advantage: the ability to underwrite more accurately, price more fairly, detect stress earlier and design repayment structures around actual cash flows. Used well, it can help formal credit replace informal and exploitative borrowing. Used poorly, it can create a new class of digitally over-indebted households. The choice is not between growth and caution. India should want household credit to expand, but in a way that raises income mobility and preserves borrower dignity. The strongest lenders of the next decade will not be those that disburse the fastest. They will be those that can show their customers are better off after borrowing than before.

The author is a fintech advisor, board member at BlackSoil, and a nominee director at FMO, the Netherlands government bank