Overview

Mumbai, 07 October 2026 – Data Sutram released its FinSecure 2026 landscape report, highlighting the critical role of trust infrastructure as India pursues its ambition of a $30 trillion economy by 2047.

Private Credit Outlook

The report estimates that India’s private credit stock, currently around $4 trillion, must grow to $45 trillion over the next 21 years, which translates to an annual dollar‑denominated growth rate of 12.2%. At 102.3% of GDP, private credit in India lags behind the United Kingdom (132.6%), the United States (140.3%) and China (200.8%) according to BIS data.

Credit Penetration Gaps

Only 28% of the 89 crore credit‑eligible adults in India are currently borrowing, leaving roughly 60 crore potential borrowers – including young consumers, micro‑enterprises and rural households – with limited or no formal credit history. Traditional credit‑bureau data is limited for first‑time borrowers, and the share of new‑to‑credit borrowers has fallen from 23.5% to 17.8% of originations over the past four years (CRIF).

Secured Lending Challenges

The report identifies paperwork, limited information and lengthy processing timelines as key obstacles in secured lending. In FY25, 8.56 crore income‑tax returns were filed, of which only 11.4 lakh were filed by companies and 16.6 lakh by firms. Moreover, only 41% of MSMEs have accessed formal credit, underscoring persistent information gaps.

Fraud Landscape

India’s suspected digital fraud rate stands at 7.1% of transactions, well above the global average of 3.8% (TransUnion). The Indian Cyber Crime Coordination Centre (I4C) recorded losses of ₹22,495 crore across 28.15 lakh complaints in 2025, with investment scams accounting for 76% of the loss value. Fraud networks are increasingly sophisticated, employing mule accounts, synthetic identities and organised scam infrastructure.

Demographic Opportunities

Gen Z now represents half of new‑to‑credit‑card consumers. Although this cohort makes up 34% of the eligible population, credit penetration is only 16%, indicating substantial room for responsible credit expansion. Rural and semi‑urban areas contribute 46% of new‑to‑credit consumers, yet more than 25 crore Indians continue to rely on feature phones and 2G networks (IDC & Counterpoint).

Micro‑finance Trends

Between June 2024 and March 2026, the micro‑finance sector saw 1.8 crore borrowers exit. During the same period, average ticket sizes rose by 23% and the Portfolio at Risk (PAR) for 180‑day arrears more than tripled to 16.3%. These shifts highlight the need for credit and servicing models that function across diverse devices and consumer contexts.

AI‑Driven Transformation Areas

1. Real‑time large‑ticket lending – Consent‑based data from the Account Aggregator ecosystem (which has crossed 538 million consents), GST records and bank statements can bridge information gaps for borrowers lacking formal records. AI agents can automate document verification, due‑diligence and credit‑memo preparation, shortening processing times.

2. Real‑time fraud detection – AI enables a shift from post‑transaction reporting to proactive risk intelligence, identifying mule accounts before transactions occur, detecting synthetic identities at onboarding and distinguishing legitimate from fraudulent activity. The Supreme Court has directed the RBI to issue a Standard Operating Procedure for mule accounts, underscoring regulatory focus.

3. AI‑led underwriting for Gen Z – By analysing behavioural and alternative signals during transactions, AI can embed credit decisions within the purchasing journey, eliminating separate application steps.

4. Voice‑based financial services for rural India – Voice AI in local languages can support application processes, verification, repayment communication and customer servicing for feature‑phone users, improving economics of servicing smaller‑ticket borrowers where field‑based collection is costly.

FinSecure Index

FinSecure 2026 introduces the FinSecure Index, a five‑level framework that assesses the evolution of financial‑trust capabilities—from point‑in‑time bureau assessment to continuous, agentic trust. The framework includes a diagnostic tool for chief risk officers to evaluate their organisation’s current trust maturity.

Methodology

The report draws on interviews with eight CXOs across Indian banking, fintech and consulting firms, proprietary Trust Score data from seven lenders, and public data from the RBI, BIS, IMF, CRIF, TransUnion CIBIL and Sahamati.

About Data Sutram

Founded in 2020 and headquartered in Mumbai, Data Sutram builds Trust AI, an enterprise AI trust platform for India’s financial sector. Its product suite comprises Trust (an agentic back‑office automation platform), Auth (a risk‑intelligence platform built on alternative data and proprietary models, including Trust Score 2.0) and Echo (a voice‑agent platform for customer conversations and collections). The company is backed by Lightspeed and B Capital and serves more than 40 Indian banks and financial institutions.

Disclaimer: This press release is provided under an arrangement with NRDPL. PTI takes no editorial responsibility for the content.