Sahamati and CRIF have released the first report capturing the impact of the Account Aggregator (AA) framework on growth, impact and inclusion. Titled Consent to Credit – The Digital Way, it was launched at SamvAAd 2026, our annual ecosystem event, on 15 October 2026.
Sahamati’s bi-annual lending survey estimates AA-enabled lending at about Rs 3.82 lakh crore across 3.68 crore loans in FY26. That is roughly 8.4% of retail and MSME lending by value and 11.8% by volume, which shows AA has become a prominent data-sharing channel for credit underwriting and monitoring.
The report examines how AA adoption and usage drive growth, expand customer segments, improve portfolio quality and increase financial inclusion.
Drawing on bureau data over two lending cycles (FY25–FY26), it compares AA-enabled and non-AA lending at the lender, loan and pincode levels.
Key findings
1. Higher loan expansion: AA-enabled lender cohorts outpaced non-AA lenders in growth, especially in home loans, personal loans and micro business loans.
2. Higher share of new-to-credit (NTC) loans: Over a 12-month period, AA lender cohorts had a much higher share of first-time borrowers in mid-ticket business loans (28.5% vs 8.6%) and personal loans (9.0% vs 3.8%) than non-AA cohorts.
3. Higher average ticket sizes: AA-enabled applications unlocked notably higher loan amounts. Personal loans averaged ₹2,67,500 for AA vs ₹1,81,100 for non-AA, and auto loans averaged ₹8,14,270 vs ₹6,84,800.
4. Improved portfolio quality: As of June 2026, AA-enabled loans had lower PAR 90+ than non-AA loans: 0.5% vs 5.3% in two-wheeler loans, 2.0% vs 2.2% in personal loans, and 4.1% vs 4.4% in business loans under ₹10 lakh.
5. Better collections efficiency: Collections is emerging as an AA use case. As of June 2026, AA lender cohorts had lower late-stage delinquency (PAR 91–180) than non-AA cohorts in personal loans (1.2% vs 2.3%) and small business loans up to ₹10 lakh (0.1% vs 0.3%).
Impact on economic activity
CAFRAL researchers studied two years of AA-enabled loan data to see its effect on economic activity at the PIN code level. PIN codes with high AA-induced exposure saw a 2.1% increase in night-time light intensity, a strong indicator of economic activity. At the district level, it rose by up to 3.03%.
Lender case studies
The report features case studies from five lenders across home loans, small-business credit and new-to-credit lending. Their experience shows how AA-based underwriting has opened formal credit to borrowers with thin or no credit history in Tier 2 and 3 markets, while helping lenders approve more loans, reduce EMI bounces and keep defaults in check through consented monitoring.