Banks vs NBFCs: How Artificial Intelligence Is Changing India’s Credit Race

India's lending market is already massive. Total outstanding credit in the country stands at approximately ₹232 trillion (roughly $2.6 trillion), according to the Economic Times.

Yet compared with many other major economies, India remains relatively underleveraged. The country's credit-to-GDP ratio is around 53%, which is significantly lower than China, where total debt-to-GDP ratios exceed 100%. What this percentage means in practical terms: India still has a lot of room to grow its lending ecosystem. As incomes rise, businesses expand, and financial inclusion improves, demand for credit is likely to keep rising.

Today, banks account for more than 70% of total lending in the system, while NBFCs hold a smaller share. But projections suggest that gap will narrow. Research estimates indicate NBFC credit could grow at roughly 17% annually between FY25 and FY35, compared with about 12% for bank lending over the same period.

Why AI Is a Bigger Advantage for NBFCs Than for Banks

A key reason NBFCs are gaining ground is their ability to adopt artificial intelligence faster than traditional banks. Many public sector banks and older private banks operate on outdated core banking systems that are difficult and expensive to replace. NBFCs typically operate on more modern, flexible technology stacks, allowing them to integrate AI tools across lending operations without the same institutional inertia.

In India, this advantage is amplified by the sheer scale of digital financial activity now generating usable data:

• India has over 1 billion internet users
• UPI processed more than 21.7 billion transactions in January 2026, with values exceeding ₹28.33 lakh crore
• Digital payments now dominate retail transactions across urban and semi-urban India

Each of these transactions creates a data trail. AI systems analyse this data to transform how credit is discovered, assessed, and priced in ways that traditional rule-based underwriting simply cannot match.

How AI Is Changing Lending Operations for NBFCs

Smarter credit underwriting

AI models analyse large datasets — income patterns, bureau scores, repayment history, existing liabilities — to evaluate borrower risk more precisely than rule-based systems. This reduces both over-lending to high-risk borrowers and under-lending to genuinely creditworthy ones.

Pre-qualification before application

AI tools can estimate loan eligibility before a borrower formally applies. This reduces unnecessary applications, prevents multiple hard inquiries on credit reports (which damage scores), and improves approval probability for the borrowers who do apply.

Use of alternative data for thin-file borrowers

Beyond traditional financial records, AI models can analyse digital payment patterns, transaction behaviour, small-ticket repayment history, and spending habits. This allows NBFCs to assess new-to-credit borrowers, the self-employed contractor, the small kirana owner, and the first-time urban migrant, who have no formal credit history but demonstrable financial behaviour. This segment represents one of the largest untapped credit opportunities in India.

Better borrower-product matching

AI-driven systems align borrower profiles with suitable loan products, improving targeting and reducing rejection rates. A borrower who fits better in a secured MSME loan than an unsecured personal loan gets routed accordingly — improving outcomes for both lender and borrower.

Faster decisions

Automated risk models allow NBFCs to process applications in minutes rather than days. For borrowers who need working capital quickly or want to finance a purchase at the point of sale, this speed is a genuine competitive differentiator.

A note on the limits of AI in lending: AI does not replace lender judgment. Final credit decisions still follow institutional risk policies and RBI regulatory requirements. But AI significantly improves speed, accuracy, and efficiency across the lending process, particularly at scale.

NBFCs Have Already Grown Their Footprint

This shift is not just theoretical. It is already visible in the structure of India's financial system.

• NBFC share of banking sector assets rose from 13% in March 2013 to 18.7% by March 2023
• India now has over 9,300 RBI-registered NBFCs (as of June 2024), one of the largest non-bank lending ecosystems globally
• NBFC total balance sheets reached ₹61 lakh crore by March 2025
• NBFC credit-to-GDP has grown from 16% in FY19 to 26% in FY26

The growing influence of NBFCs is also visible in the stock market. Several listed NBFCs command significant market capitalisation across consumer finance, asset management, and diversified financial services.

Source: Tickertape

Retail Lending: Where NBFCs Are Gaining the Most Ground

Another reason for NBFC growth is their aggressive push into retail lending. While many NBFCs historically concentrated on wholesale financing, over the past decade they have moved into vehicle loans, consumer durable loans, personal loans, and microfinance segments, where demand in India remains strong.

NBFCs accounted for approximately 92% of new personal loan volumes in June 2025 by number of accounts (driven by small-ticket digital loans), though their share by loan value stood at around 41% as banks focused on larger-ticket borrowers. This split reflects one of the most important structural differences between the two: NBFCs serve the mass market at small ticket sizes, while banks concentrate on larger, wealthier borrowers.

The MSME Opportunity

India's MSME sector contributes over 30% of GDP but remains significantly underserved by formal credit. Many small businesses—traders, manufacturers, and self-employed professionals find it difficult to access bank credit because they lack collateral, formal income documentation, or credit history.

NBFCs have stepped into this gap, offering financing solutions tailored to small entrepreneurs. Cash flow-based lending, supply chain financing, and microenterprise loans are areas where NBFCs have built strong positions, often using AI to assess creditworthiness from transaction data rather than formal documents.

What This Means for Investors Tracking Financial Stocks

For investors in India's financial sector, the NBFC-bank dynamic deserves attention for two reasons.

First, the growth trajectory. If NBFC credit grows at 17% annually versus 12% for banks over FY25–FY35, the compounding effect on NBFC balance sheets and earnings over a decade is significant. Companies like Bajaj Finance, Chola Finance, and others operating in consumer and MSME lending are positioned at the intersection of India's credit expansion and AI-driven efficiency gains.

Second, the risk profile. NBFCs do not have access to low-cost deposits the way banks do. They fund themselves through borrowings, commercial paper, and NCDs, which makes them more sensitive to interest rate cycles and liquidity conditions. The IL&FS and DHFL crises earlier showed how quickly funding can dry up for NBFCs in a credit stress event. AI improves the asset side of the book; the liability side remains a structural vulnerability.

Both factors matter when assessing NBFC stocks: the growth opportunity is real, and so are the risks.

Disclaimer: This article is for informational purposes only and does not constitute financial advice, investment recommendations, or an offer to buy or sell any security. Readers should conduct their own research or consult a SEBI-registered financial advisor before making any investment decisions.