Why Indian MSMEs Struggle to Access Formal Credit

India has never had more registered small businesses. Registrations on the government’s Udyam portal crossed 4.77 crore by 2024, and the number keeps rising. Yet the gap between what these enterprises need to borrow and what the formal financial system lends them remains one of the Indian economy’s most persistent features. Estimates of that gap vary widely by method, from around Rs 15 lakh crore to Rs 45 lakh crore, but every serious estimate puts it in the tens of lakh crore.

The usual explanations are that banks are too cautious, that MSMEs are too informal, or that paperwork is too heavy. Each contains some truth, but none explains why the gap has proved so stubborn across decades of schemes, mandates and targets. The deeper answer is structural. The formal credit system was built to assess a particular kind of borrower, and most Indian MSMEs do not look like that borrower.

Understanding why matters because it also explains which recent changes are likely to work and which are not.

Part one: why the gap exists

Information asymmetry: the lender cannot see the business

Every lending decision rests on one question: will this borrower generate enough cash to repay? For a large listed company, the lender can answer it from audited accounts, credit ratings, market data and years of public disclosure. For a small enterprise, almost none of that exists.

Many small businesses run personal and business money through the same accounts. A meaningful share of sales may be in cash. When they exist, financial statements are often prepared once a year for tax purposes, months after the year ends, and they may understate income for that reason. The lender is being asked to estimate future cash flow from a picture that is old, incomplete, and shaped by other incentives.

Economists call this information asymmetry: the borrower knows far more about the business than the lender can verify. Lenders respond in predictable ways. They charge higher rates to cover the uncertainty, demand collateral to protect themselves if their estimate is wrong, or simply decline. Each response pushes good borrowers away along with bad ones.

There is also a cost problem. Manually assessing a borrower takes roughly the same effort whether the loan is Rs 10 lakh or Rs 10 crore. On a small loan, the interest margin often cannot cover that cost. Without cheaper ways to assess risk, small-ticket MSME lending isn’t just risky for banks. It is unprofitable.

Thin credit files: no history, no score

Credit bureaus solve part of the information problem by recording past repayment behavior. But a bureau can only report history that exists. A business that has never borrowed formally has no commercial credit record. A proprietorship is often assessed on the owner’s personal record, which may also be thin.

This creates a circular trap. A business cannot get formal credit without a credit history, and it cannot build a credit history without formal credit. The firms most likely to be caught are young enterprises, service businesses and first-generation entrepreneurs, precisely the segments that most need capital to grow.

Collateral designed for a different kind of borrower

Indian bank lending grew up around a model in which security did much of the work. Land, buildings, plant and machinery could be mortgaged or hypothecated, valued and, if necessary, sold. That model fits a manufacturer that owns its factory.

It fits much less well for the businesses that make up most of the MSME population today. Traders and service firms usually operate from rented premises. Their most valuable assets are customer relationships, receivables, skilled people and know-how, none of which can be mortgaged. Even where property exists, unclear titles, joint family ownership and slow enforcement reduce its value as security.

Policy has tried to close this gap. Banks are directed not to take collateral for loans up to Rs 10 lakh to micro and small enterprises, and the Credit Guarantee Fund Trust for Micro and Small Enterprises guarantees collateral-free loans. These measures have helped, but they work around the collateral model rather than replacing it. The guarantee fee adds to cost, and lenders have often continued to prefer borrowers who could offer security anyway.

Delayed payments make even good businesses look risky

One more structural factor rarely gets enough attention. MSMEs are owed enormous sums by their customers. The Economic Survey 2025-26 estimated that around Rs 8.1 lakh crore owed to MSMEs is locked in delayed payments. A profitable business that waits 120 days to be paid has erratic cash flows, frequently overdrawn accounts, and occasional delays in meeting its own obligations. To a lender reading its bank statements, it looks weaker than it is. The credit problem and the payment problem are tied together.

Informal lending fills the gap, at a cost

When formal credit is unavailable, business does not stop. It turns to other sources: moneylenders, chit funds, family and community networks, extended credit from suppliers, and delays in paying statutory dues. These sources are fast, flexible, and require little documentation. For a business that needs Rs 5 lakh by Friday to buy material for an order, they are often the only practical option.

That flexibility is expensive. Informal rates of 24 to 36 per cent a year are common, and much higher rates are not unusual for short emergencies. At those prices, informal credit eats into the thin margins most small businesses earn. It also leaves no trace in the formal system, so businesses build no credit history and remain invisible to banks. The informal market fills the gap and, in doing so, helps keep it open.

Part two: what has actually shifted

For most of the last two decades, policy responses focused on pushing more money through the old model: lending targets, priority sector rules, interest subventions and guarantees. The more significant change of the last few years is different in kind. It attacks the information problem directly by creating verifiable data about small businesses that didn’t exist before.

GST data as an underwriting input

The Goods and Services Tax created something Indian lenders had never had: a near real-time, verifiable record of business transactions. A GST-registered business files returns showing its sales, purchases, and, through invoice matching, its customers and suppliers. Unlike annual accounts, this data is frequent, standardized, and checked against the counterparty’s own filings.

For a lender, this changes the question. Instead of relying on a borrower’s declared turnover, it can see actual invoiced sales over many months, how stable they are, how concentrated the customer base is and whether the business pays its own tax on time. GST data does not capture cash sales or unregistered businesses, but for a large and growing share of MSMEs it provides the evidence lenders previously lacked.

Account aggregators and consented data sharing

The RBI-regulated account aggregator framework allows a business to share financial data, such as bank statements, from one institution to another digitally, and only with explicit consent. Before, a lender wanting six months of bank statements relied on PDFs, scans, or physical copies, which were slow to collect and easy to manipulate.

With consented data flowing directly from the source, a lender can analyze inflows and outflows, average balances, bounced payments, and seasonality within minutes. Combined with GST data, this gives a far richer picture of the business’s actual cash flow than a balance sheet prepared once a year.

Udyam as a formal identity

Udyam registration is free, online and linked to PAN and GST data. Its direct benefits include access to priority sector lending, government schemes, and, for micro and small enterprises, delayed-payment protections under the MSMED Act. Its less obvious contribution is identity. A Udyam number gives a small business a recognized, verifiable presence in the formal system, which lenders, buyers and government programs can all reference. In August 2026, Parliament also passed an amendment to the MSMED Act that gives the Udyam portal statutory standing, with provisions applying as the government notifies them.

Cash flow-based lending

These data sources come together in a shift from collateral-based to cash flow-based lending. Instead of asking what the borrower owns, the lender asks what the borrower earns and how reliably.

The clearest public sector example is the digital footprint-based credit assessment model launched in March 2025, under which public sector banks assess MSME borrowers in-house using GST data, bank statements obtained through account aggregators, income tax returns, and bureau data. According to Business Standard, public sector banks sanctioned Rs 28,724 crore of MSME loans under the model between April and October 2025, with a rejection rate of about 20 percent and a substantial share going to borrowers new to the bank or with limited prior access to formal credit.

Alongside bank lending, a broader set of MSME finance products now relies on transaction data and the buyer’s credit rather than the small supplier’s. Invoice discounting, the RBI’s TReDS platforms and buyer-led supply chain finance programs allow a business to raise money against invoices accepted by a creditworthy customer. For a supplier with a thin credit file but strong customers, this can be the first route into formal finance, and the repayment history it creates builds the record that later makes conventional credit easier to obtain.

What has not shifted yet

It would be a mistake to read these changes as a solution. Several limits remain.

The data covers the formal edge first. GST, account aggregators and Udyam all work best for businesses that are already partly formal. Cash-heavy micro enterprises, informal workshops and businesses below the GST threshold have little digital footprint to share. The tools that help a Rs 20 crore GST filer may do little for a Rs 40 lakh enterprise in a small town.

Some business structures remain hard to assess. Lenders have reported difficulty analyzing partnership firms and businesses with complex group accounts through automated models. Proprietorships, where business and owner are effectively one, are easier to score.

The models are young. Cash flow-based models have mostly operated through a period of steady growth and falling interest rates. How they perform in a downturn, when cash flows fall across many borrowers at once, remains untested.

Formalization has its own cost. Becoming visible to lenders also means becoming visible to tax authorities, compliance requirements and buyers who may now classify the supplier differently. For some businesses, that trade-off still doesn’t look worth it.

Payment discipline remains the missing link. As long as large buyers pay late, the cash flows lenders now analyze so carefully will look weaker than the underlying business really is. Better data cannot fully compensate for money that has not arrived.

The direction of travel

The formal credit gap for Indian MSMEs was never mainly about a shortage of money in the banking system. It was about the cost and difficulty of knowing which small businesses were safe to lend to. For decades, collateral substituted for that knowledge, and businesses without collateral were left to the informal market.

What has changed is that knowledge is becoming cheaper. GST records, consented bank data, formal registration and buyer-backed invoice platforms are gradually giving lenders a view of small businesses that was simply unavailable a decade ago. That does not close the gap on its own, and it will help the more formal end of the sector first. But it moves the question lenders ask from “what can you pledge?” towards “what does your business actually do?”, and for millions of small enterprises that is the more favorable question.