Sharing bank data makes applicants 3x more likely to get Rs10–25 lakh business loans in India

A new joint study by CRIF Credit Information Services and industry alliance Sahamati finds that sharing bank data through India’s Account Aggregator (AA) framework substantially raised the odds that a borrower with no prior credit history would obtain a mid-sized business loan.

The research shows new-to-credit borrowers made up 28.5% of Rs 10 lakh–25 lakh business loans issued by AA-enabled lenders in the 12 months ended June 2026, compared with 8.6% for lenders that did not use the framework.

That gap, the report says, amounts to more than a threefold increase in approval likelihood for applicants who consented to share their banking data via AA systems.

The AA channel also accounted for large volumes of lending: Sahamati estimated AA-enabled disbursals at Rs 3.82 lakh crore across 3.68 crore loans in FY26, and the study reported that AA-originated lending made up 8.4% of retail and MSME lending by value and 11.8% by volume — roughly 1.1% of India’s GDP by the authors’ calculation.

The report found lenders using AA grew faster and extended more credit to first-time borrowers and to Tier‑3 markets while registering comparable or lower delinquency rates than peers that did not use the framework. Data in the study show the AA effect extends beyond business loans.

In personal lending, first-time borrowers accounted for 9% of AA-enabled originations in the year to June 2026, versus 3.8% for non‑AA lenders, and the average AA-enabled personal loan size stood at Rs 2,67,500 compared with Rs 1,81,100 for non‑AA personal loans. The report also noted higher average ticket sizes for AA-originated auto and two‑wheeler loans.

Sahamati’s ecosystem figures, reported in the coverage, indicate substantial operational scale: as of August 2026 there were 16 operational AAs, 176 financial information providers and 1,144 financial information users regulated by RBI, SEBI, IRDAI and PFRDA, with more than 566 million consents fulfilled and retail users linking over 338 million bank accounts.

The study’s authors argue that the AA framework can reach borrowers who have been excluded from conventional credit scoring and underwriting because consented bank data gives lenders richer signals of income and cash flow. Coverage of the study across outlets repeats the core numeric findings but emphasizes different implications.

Some reporting highlights the faster growth and lower delinquencies among AA‑using lenders; other pieces focus on the framework’s role in extending credit to first‑time borrowers and increasing average loan sizes for AA originations. All sources in this pack cite the same CRIF‑Sahamati statistics for the Rs 10–25 lakh segment and the FY26 aggregate.

The study does not, in the sourced reporting, provide an experimental causal estimate that isolates AA consent as the sole driver of higher approvals from all other lending changes; it presents comparative shares and averages from lenders that did and did not use AA.

The authors’ policy framing, quoted in reporting, suggests AA could become “a foundational pillar of India’s digital credit infrastructure,” but that statement is an interpretive forecast rather than an empirically proven outcome in the materials cited.

For lenders and policymakers, the findings offer a data point on how consented bank-data sharing correlates with broader access to credit and larger average tickets, particularly for borrowers without prior credit records.