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Editors Pick
Credit is entering a new era.
For decades, lending decisions have largely depended on a familiar equation: credit history, income, collateral and conventional risk models. But the rise of digital financial infrastructure, artificial intelligence, alternative data and embedded finance is fundamentally changing how lenders understand borrowers.
The next credit revolution will not simply be about faster loans. It will be about making lending more intelligent, inclusive and precise.
For India, this transformation could be particularly significant. The country has built one of the world’s most sophisticated digital financial ecosystems, combining Aadhaar, UPI, Account Aggregator, digital banking and emerging credit infrastructure. The opportunity now is to translate this infrastructure into a more responsive and responsible credit system.
From Credit Scores to Credit Intelligence
Traditional credit scores remain important, but they provide only a partial view of a borrower.
A consumer may have limited formal credit history but demonstrate consistent cash flows, disciplined digital payments or stable financial behaviour. Similarly, a small business may not possess extensive collateral while maintaining predictable receivables and healthy transaction activity.
Artificial intelligence can potentially bring these signals together.
Instead of asking only, “What has this borrower borrowed and repaid?”, intelligent underwriting can ask, “What does the borrower’s overall financial behaviour tell us about future repayment capacity?”
This shift from static credit scoring to dynamic credit intelligence could enable lenders to evaluate customers with greater context and precision.
India is already moving in this direction. The Reserve Bank of India’s Unified Lending Interface, or ULI, is designed to connect lenders and data providers through standardized APIs, enabling access to multiple data sources for credit assessment. As of March 2025, the platform had 44 lenders using more than 60 data services across 12 loan journeys, including Kisan Credit Card and MSME lending.
The Inclusion Opportunity
The biggest impact of intelligent lending could be felt among customers who have historically remained underserved.
MSMEs, gig workers, rural entrepreneurs, first-time borrowers and individuals with limited formal credit histories often face challenges in accessing affordable credit.
This is where alternative data and consent-based financial information sharing can become transformative.
India’s Account Aggregator ecosystem is creating a framework in which customers can securely share financial information with regulated institutions based on explicit consent. By March 2026, more than 2.88 billion financial accounts were enabled for data sharing through the framework, with more than 284 million accounts linked by users.
The significance goes beyond technology.
A more complete financial profile can allow lenders to understand customers who may have been invisible to traditional underwriting models.
For a small entrepreneur, GST-linked information, banking transactions and business cash flows could potentially provide a richer picture of financial health than collateral alone.
For a salaried customer, recurring income and expenditure patterns could complement traditional bureau information.
For a new-to-credit borrower, responsible financial behaviour could become a meaningful signal.
The result could be a shift from credit exclusion to contextual lending.
Precision Lending: The New Competitive Advantage
The future of lending is unlikely to be about giving everyone more credit.
It will be about giving the right credit to the right customer at the right time, at the right price and with the right safeguards.
That is precision lending.
AI can help lenders segment customers more accurately, identify changing risk patterns and personalize credit products. Instead of treating thousands of borrowers as statistically similar, institutions can potentially create more granular risk profiles.
This can improve several dimensions of lending simultaneously:
For customers: faster decisions and more relevant products.
For lenders: better risk management and potentially lower acquisition and servicing costs.
For the economy: improved access to productive capital.
But precision cannot come at the cost of fairness.
The AI Governance Imperative
The same algorithms that can expand financial inclusion can also amplify bias if they are trained on incomplete or distorted data.
That makes explainability, privacy, fairness and accountability critical.
The RBI’s 2025 Digital Lending Directions emphasize borrower creditworthiness assessment, transparency, data governance, privacy and technology standards. The regulatory direction is clear: digital lending must combine innovation with customer protection.
For financial institutions, this means AI models cannot simply be accurate. They must also be auditable, explainable, secure and responsibly governed.
The question for lenders should therefore not be only:
“Can AI predict default?”
It should also be:
“Can we explain why this decision was made?”
Embedded Credit Will Change Customer Expectations
Credit is also moving closer to the point of need.
Embedded finance is bringing lending into commerce, payments, business platforms and digital ecosystems. Customers increasingly expect financial services to be available within the platforms where they already operate.
This could fundamentally change customer acquisition.
Instead of customers searching for loans, financial institutions could increasingly identify relevant credit opportunities through consented financial relationships and contextual interactions.
For an MSME, working-capital finance could appear alongside business transactions.
For a farmer, credit could become integrated with agricultural activity.
For a consumer, financing could become part of a digital purchase journey.
The future of lending could therefore be less about the loan application and more about the financial journey.
Trust Will Define the Winners
Technology can make lending faster. Data can make it smarter. AI can make it more predictive.
But trust will determine whether customers embrace the next generation of credit.
India’s digital lending framework has increasingly focused on transparency, responsible data usage, customer protection and regulated accountability. This is essential because the expansion of digital credit also creates risks around privacy, fraud, over-indebtedness and irresponsible lending.
The winners will not necessarily be the institutions with the most sophisticated algorithms.
They will be those that combine data intelligence with human judgment, automation with accountability, and speed with responsible lending.
The Road Ahead
India’s financial inclusion journey is moving from access to intelligence.
The first phase was about opening bank accounts.
The next phase was about enabling digital payments.
The emerging phase is about creating intelligent financial services that understand individual needs and deliver appropriate products responsibly.
AI, Account Aggregator, ULI, UPI and Digital Public Infrastructure could collectively reshape how credit originated, assessed, priced and serviced.
The next credit revolution will therefore not be defined simply by how much money lenders can distribute.
It will be defined by how precisely they can understand customers, how inclusively they can serve them and how responsibly they can manage risk.
In the future of lending, intelligence will drive decisions, inclusion will expand opportunity, and precision will define performance.
The smartest lender will not be the one that says “yes” to everyone. It will be the one that knows when, why and how to say “yes.”
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