In a country as vast and diverse as India, access to credit remains uneven. While banks have traditionally catered to customers with an established credit history, a significant population, first-time borrowers with little or no formal credit footprint continues to be underserved. These individuals are commonly referred to as “thin-file” customers.
For Non-Banking Financial Companies (NBFCs), this segment represents both a challenge and a massive opportunity. With innovative credit assessment models, alternative data, and regulatory tailwinds, NBFCs are uniquely positioned to reimagine creditworthiness and unlock the next wave of financial inclusion.
Who Are the Thin-File Borrowers?
“Thin-file” doesn’t mean poor — it simply means “invisible” to traditional lenders.
It could be a gig economy worker in Jaipur, a first-jobber in Nagpur, or a self-employed artisan in a small town. These individuals may never have taken a loan or owned a credit card, so credit bureaus have no data on them. According to industry estimates, over 450 million Indians fall into this category.
Banks often view this segment as high-risk due to the absence of data. But for NBFCs, which thrive on agility and risk appetite, thin-file borrowers represent an untapped goldmine — provided they have the right tools to assess risk.
Understanding the Thin-File Dilemma
Traditional credit scoring relies heavily on formal borrowing patterns — past loans, timely repayments, credit card behavior. But what if none of those exist? That’s the core dilemma.
And yet, the absence of a credit score doesn’t equate to an absence of creditworthiness. It simply means lenders must look elsewhere for cues into areas that were previously unmeasured, unstructured, or overlooked.
This is where NBFCs are stepping up, rewriting the credit rulebook.
Tech to the Rescue: Reassessing Risk with Intelligence
NBFCs are increasingly leveraging Artificial Intelligence (AI) and Machine Learning (ML) to go beyond the bureau. These technologies analyze patterns in alternative data, making sense of how individuals behave financially even if they’ve never taken a loan before.
One standout example is Revfin, a digital lender that uses psychometric testing developed in collaboration with IIT Kharagpur. Their models evaluate traits like honesty, intent to repay, and emotional intelligence, building a psychological profile of the borrower, not just a numerical one.
Meanwhile, digital underwriting tools now analyze everything from UPI usage to electricity bill payments, building a 360-degree view of an individual’s financial habits.
Alternative Data: The New Credit Language
If traditional credit data is a book, alternative data is a podcast — it requires a different way of listening.
Here’s how NBFCs are using it:
- Utility & Rent Payments:
Regular payments for mobile bills, gas, water, or rent reflect financial discipline — a critical marker for assessing repayment behavior. - Mobile & Digital Footprint:
Patterns in app usage, digital wallet transactions, e-commerce activity, and even typing speed during application processes are now being analyzed to gauge stability. - Social and Professional Networks:
Who you’re connected with, how long your digital accounts have existed, and the tone of your online interactions can offer subtle yet meaningful signals about your reliability.
Some NBFCs even use hybrid models, combining community validation (shopkeeper testimonials, employer feedback) with tech intelligence — especially in rural areas where paperwork is thin but reputations are rich.
From Gig Worker to Borrower: A Real-World Example
Consider a delivery agent working with a food-tech platform. They may not have a credit score, but they receive weekly digital payments, pay rent through UPI, and maintain a consistent mobile recharge pattern. Their e-commerce return rate is low, and they’ve used the same email ID for over 5 years.
A traditional lender may overlook this profile. But for an NBFC equipped with behavioral scoring tools, this is a promising candidate, low default risk, digitally engaged, and financially stable in unconventional ways.
Regulatory Support: Enabling the Ecosystem
Recognizing the thin-file challenge, regulatory bodies are building supportive infrastructure to de-risk lending for NBFCs.
- The Credit Guarantee Fund Trust for Micro and Small Enterprises (CGTMSE) has enabled over 1 crore loan guarantees, covering ₹5.2 lakh crore in credit. 45% of beneficiaries were first-time borrowers, helping them access formal finance without historical credit data.
- The Reserve Bank of India (RBI) has introduced the Unified Lending Interface (ULI), which will enable lenders to access verified data from government repositories like land records, national Ids like PAN, making KYC and underwriting faster and more secure.
Together, these initiatives give NBFCs the confidence to lend to new segments without increasing risk exposure.
The Business Case: Inclusion Meets Scale
The opportunity isn’t just social — it’s economic.
India’s digital lending market is expected to cross $350 billion by 2025, with a significant portion driven by borrowers who are new to credit. For NBFCs, focusing on this group means:
- Diversifying risk by entering new segments
- Gaining early loyalty from financially rising individuals
- Creating competitive advantage through innovation
And unlike saturated urban markets, this segment isn’t maxed out — it’s barely been touched.
The Road Ahead: Data-Driven, Inclusive Lending
The lending playbook is evolving. NBFCs that rely solely on credit bureau data risk missing out on India’s next 500 million borrowers. The future lies in contextual underwriting — understanding a person’s intent, behavior, and life circumstances through data that’s all around us.
Thin-file borrowers aren’t a risk; they’re an opportunity wrapped in complexity. And NBFCs that master this complexity will not only win market share but also become champions of true financial inclusion.
Leave a Reply