In India, credit health is defined by scores from 300 to 900, calculated by bureaus such as CIBIL, CRIF, Experian, and Equifax. Scores above 760 indicate strong creditworthiness, but the system depends heavily on repayment history and existing loans, leaving millions of “new-to-credit” Indians at a disadvantage. According to TransUnion CIBIL’s June 2025 Credit Market Report, the share of new-to-credit (NTC) borrowers declined from 19% to 16% YoY, signaling continued caution among lenders. While overall loan originations rose just 5% YoY in March 2025. Notably, enquiry volumes from borrowers aged 30 and below fell from 58% to 56% (Source). This highlights a persistent gap i.e. many individuals struggle to build credit, while lenders miss opportunities to responsibly expand access.
The Role of AI and Alternative Data
Artificial intelligence offers a powerful response to these challenges. Unlike conventional systems that depend narrowly on bureau data, AI can analyze diverse digital signals, ranging from electricity and telecom bill payments to patterns of digital wallet usage and gig-economy earnings. These alternative data points are especially relevant in India, where millions earn outside the salaried workforce and rely heavily on digital payments rather than formal banking.There was certainly a time, when the majority of the Indian population was either unserved or underserved by conventional credit systems. But today, the Financial Inclusion Index (FI-Index) has risen from 56.4 to 64.2, reflecting steady progress but also underscoring the need for AI-led innovation. AI can help close this very gap by creating credit profiles for people who would otherwise be invisible in traditional frameworks. Importantly, this does not mean lowering standards. Machine-learning models can recognize repayment capacity and responsible behavior even without a long borrowing history, allowing lenders to balance inclusion with risk management. The practical impact is significant. Rural households with limited formal credit exposure can be assessed based on their consistent utility payments. Gig-economy workers drivers, delivery agents, or freelancers can demonstrate reliability through transaction histories. In this way, AI expands the lens of credit assessment, creating a fairer and more representative system.
Personalized Planning Through AI
AI is not just improving the scoring process, it is making credit health interactive. Traditional systems leave borrowers in the dark, with little insight into how to improve their score beyond generic advice. In contrast, AI-powered models can provide personalized recommendations in real time.
Lets understand this better through an example. Consider a young professional in Bengaluru who uses multiple credit cards. Instead of simply warning about “high utilization,” an AI tool can suggest the optimal repayment strategy for that month, highlight which card to prioritize, and predict how these actions will impact the individual’s score. For a gig-economy worker in Jaipur, the system could recommend building credit through a small secured product, gradually opening the door to larger loans. These insights transform credit from a backward-looking metric into a forward-looking coach.
Generative AI is accelerating this transformation further. In India, fintech platforms are using these tools to streamline credit assessments, offering both lenders and borrowers quicker feedback. Speed plays a crucial role because it directly influences access when a first-time borrower applies for a two-wheeler loan or a small personal loan, faster decisions can translate into faster opportunities.
Regulatory Momentum and Digital Infrastructure
Technology alone is not enough; it must be supported by the right policy environment. The Reserve Bank of India has been working with credit bureaus to explore daily credit reporting, which would significantly reduce the lag between consumer actions and score updates. If implemented, this would allow a timely repayment or correction to reflect almost immediately, enhancing fairness and transparency.
Equally important is the broader shift in India’s credit system, as highlighted in the RBI’s July 2025 bulletin. The country is steadily moving away from collateral-heavy lending toward digital, data-driven models powered by India’s Digital Public Infrastructure. This ecosystem which already includes Aadhaar, UPI, and Account Aggregator frameworks provides a foundation for AI-based credit assessment to operate securely and at scale. By embedding transparency and consent into the process, regulators aim to ensure that innovation aligns with trust.
Looking Ahead
India’s credit system finds itself at a veritable crossroad and serious innovation awaits at the next signal. In the coming years, credit health will not be characterized solely by static figures. It will be outlined by a dynamic profile that excels in real-time adaptation. This evolution will deliver us the potential to substantially advance the process of financial inclusion at our own terms. By masterfully blending AI’s analytical power with India’s expanding digital infrastructure and regulatory oversight, millions of underserved consumers will gain a long-cherished access to responsible credit. All said and done, the important challenge ahead is ensuring that technology keeps its end of the bargain, i.e., serving people and not the other way around.
