In a country where millions still lack formal credit histories, traditional scoring models fall short. In this exclusive conversation, Rajeev Ranjan, Editor of Digital Terminal, speaks with Suryadip Ghoshal, Co-Founder & Chief AI Officer at Think360.ai, about how their Algo360 platform is reshaping credit assessment in India.
Rajeev: How is Think360.ai’s Algo360 platform fundamentally changing the way creditworthiness is assessed in India, especially for those without a formal credit history?
Suryadip: Assessing creditworthiness is central to lending as it forms the foundation of trust between lenders and borrowers. It lies at the heart of responsible lending for the simple fact that it determines not just if a person or business can borrow money, but also how much and at what interest rate.
In India, creditworthiness has traditionally been assessed with the help of credit bureau scores and formal financial footprints like existing loans, usage of credit cards, income proof, etc. However, this model makes digital lending inaccessible to many as it leaves out millions of potential borrowers, especially first-time borrowers, gig workers, and self-employed. Despite being financially active and responsible, they remain invisible to the traditional credit scoring systems.
Algo360 redefines creditworthiness by using alternate data from UPI transactions, SMS income flows, digital payments, and even mobile recharges to build a more accurate picture of financial behavior. Across the lenders, it has improved the risk visibility for thin-file borrowers by up to 40% when compared to the traditional models. All of this has enabled not just wider access, but smarter and more responsible lending.
Rajeev: What types of alternate data points are proving most effective in building reliable credit scores for India’s underserved segments?
Suryadip: Over the last few years, we have seen how transaction-level behavioral data drawn from UPI activity, digital banking footprints, and SMS based income flows have become one of the most reliable indicators of credit health. These signals go far beyond the traditional scores to offer a deeper and more accurate insight into the borrower’s financial behavior. Some of the Key behavioral indicators (alternate data points) include:
Income regularity and source diversity, especially for gig and self-employed borrowers
Reduced discretionary spending before EMI dates, which is a clear marker of repayment discipline
Repayment timing behavior - whether a borrower pays proactively or only after nudges
Red flags like cheque bounces, missed EMIs, or frequent high-risk transactions (e.g., online gaming or speculative activity)
In many rural and semi-urban contexts, traditional bureau data offers little insight. But when we overlay these alternate data points through Algo360’s enrichment engine, we’re able to generate risk scores that align closely with actual repayment behavior, even in the absence of formal credit history.
Rajeev: How does Algo360 ensure responsible, real-time lending across Tier 2–4 cities while minimizing default risks and supporting financial inclusion?
Suryadip: Algo360 is built on contextual intelligence. It doesn’t just analyze alternate data, it interprets it in relation to a borrower’s location, profession, and stage of financial life. In Tier 2 to Tier 4 markets, where income can be seasonal and credit histories are often informal, our models are designed to work with these realities rather than against them. We enable real-time, event-triggered lending by initiating credit when key signals such as a new income inflow or improved financial behavior emerges. Algo360’s insights plug directly into lenders’ Business Rules Engines (BREs), enabling automated, policy-aligned decisions that are fast, scalable, and tailored to each borrower.
By combining model intelligence with limit management, early warning alerts, and adaptive scoring, Algo360 helps lenders lend responsibly. In rural pilots, this approach has led to up to 70 percent higher approval rates without an increase in NPAs. It’s a clear demonstration that inclusion and strong risk management can go hand in hand.
Rajeev: Why is ethical, transparent, and explainable AI critical in India’s credit ecosystem, and how is Think360.ai ensuring that their AI models are fair and unbiased?
Suryadip: In a country as diverse and complex as India, AI bias can have serious consequences, especially in financial access. When models are opaque, they can unfairly exclude borrowers based on geography, occupation, data gaps, or gender. For instance, only 26% of Indian women have a formal credit history. Many of them don’t even own property or have salaried jobs, the factors that traditional credit systems rely on. Without corrective design, models can inadvertently penalize them due to data invisibility.
At Think360.ai, we’ve made fairness and explainability core principles in building Algo360. Every score is backed by a clear rationale, helping lenders defend decisions and build trust. We regularly audit our models for bias across gender, geography, and employment types, and retrain them on balanced data if any unfair pattern emerges. Ethical AI isn’t optional—it’s essential. As finance becomes more digital, it’s critical to ensure that technology opens doors rather than closes them. For us, fairness is foundational to financial inclusion.
Rajeev: What trends do you foresee in the next 3–5 years for AI-powered credit assessment in India, and how is Think360.ai preparing to stay ahead of the curve?
Suryadip: We see four to five powerful shifts redefining credit assessment in India over the next few years:
Segmented Risk Models Will Take Over
As the demand for credit rises from Tier 2–4 cities, gig workers, and micro-entrepreneurs, lenders will shift towards behavioral underwriting that takes into account the income volatility and informal financial behavior. Additionally, the Algo360 enables this with cohort-specific profiling that adjusts to the realities of each borrower group.
Alternate Data Will Power Credit, Wealth & Insurance
Beyond lending, alternate data is driving personalized insurance and investment targeting. From UPI and SMS flows to geo-linked insights, Algo360 helps underwrite not only unsecured credit but also secured loans and financial products for emerging, data-light segments.
Explainable AI Will Be Mandatory
With regulators putting increasing emphasis on transparency, credit models must be clear, auditable, and easy to justify. Algo360 was built keeping all of this in mind. It offers built-in bias checks, traceable scoring logic, and fairness audits that help lenders stay compliant and earn borrower trust.
GenAI Will Streamline Credit Operations
From underwriting to fraud detection and customer engagement, GenAI is set to transform how lenders operate. At Think360.ai, we’re integrating smart assistants and decision-support tools that help credit teams move faster and make more consistent choices, without compromising oversight.
Consent-Driven, Real-Time Data Will Be the Norm
With the growing adoption of Account Aggregator, CKYC, and OTP-based data sharing, the advantage will go to lenders who can act quickly on fresh, user-approved data. The future of lending will not only be shaped by pricing but also by intelligence, agility, and trust.
At Think360.ai, we are focused on building the next generation of credit intelligence. We are investing heavily in multi-modal data fusion (combining Account Aggregator, SMS, bureau, and behavioral data), explainable AI layers, and plug-and-play APIs that make sophisticated risk intelligence accessible to lenders of all sizes Ultimately, our goal is simple: to make credit evaluation smarter, faster, and more inclusive, without compromising on responsibility.
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