The Account Aggregator framework launched in production in September 2021, and at that point it was being talked about as the credit-data equivalent of UPI — a piece of public digital infrastructure that would transform consumer and SME lending in India. Almost five years on, the picture is more mixed. AA has gained meaningful traction in specific lending verticals and remained largely peripheral in others. The next phase of adoption depends on solving problems that aren’t really technological.

The Sahamati-published statistics for March 2026 show roughly 240 million successful AA-mediated data sharing events cumulatively, with monthly run rates averaging 14–16 million for the past two quarters. That’s a real volume, but it’s still a fraction of what the framework was projected to be doing by now. Why?

Where AA has worked

Personal loan underwriting at fintech-driven NBFCs and digital banks is where AA has clearly delivered. The ability to pull six months of bank statement data, with explicit consent, in under 90 seconds has compressed loan decisioning timelines from days to minutes. PaisaBazaar, BankBazaar, and most of the fintech-NBFC partnerships are now AA-default. The traditional alternative — emailing PDF statements that customers manually export — looks archaic by comparison.

SME working capital lending has been the second strong adoption vertical. The combination of GSTN data (via Sahamati’s GSTN Connect) and AA-mediated bank statement data gives SME lenders a much richer underwriting picture than they had pre-AA. KreditBee, Lendingkart, and several bank SME divisions have built credit models that explicitly use the AA-derived cash flow signals.

Wealth management and personal financial management apps form the third category. Smallcase, INDmoney, and a few of the neo-bank apps use AA to consolidate account views for retail users. This is a less commercially intense use case but it’s driving meaningful end-user familiarity with the framework.

Where AA has stalled

Mortgage and home loan underwriting has been a disappointment. The AA framework should be ideal for this — long-tenor decisions, large data needs, strong customer incentive to consent. But the major bank mortgage processes still rely heavily on traditional documentation flows, and the integration of AA into the underwriting workflows hasn’t happened at the pace of the smaller-ticket products. SBI, ICICI, and HDFC have all made progress but it’s incremental rather than transformational.

Insurance underwriting was supposed to be a major AA use case for life and health insurance. It’s largely not. The IRDAI regulatory framework around AA-mediated insurance data sharing has lagged the RBI’s framework, and insurers have been slow to redesign underwriting processes. The 2024 IRDAI consultation paper on this is still working through industry comments.

The credit card application process is another disappointing area. Most issuers continue to use legacy bureau-and-statement processes rather than AA-default flows, partly because the credit card customer onboarding is more sales-led than digital-led for many issuers, and the operational change management hasn’t been prioritised.

The financial information user side

The FIU side of the framework — the entities that consume data through AA — has been dominated by NBFCs and digital lenders. Banks, while present, have been slower to integrate. Insurers have been slowest. The mutual fund industry has been almost entirely absent from FIU activity, which is surprising given the obvious use cases for KYC and consolidated account views.

The technology integration cost has been a barrier for smaller financial institutions. While the Sahamati standards are open, the implementation work — including consent management, data parsing, and integration with core systems — has typically been a six-to-twelve-month project. Some banks have worked with technology partners on this, but the AA-FIU technology vendor space remains underdeveloped relative to the equivalent UPI ecosystem. There’s a gap there for AI-focused implementation specialists who can help banks build the consent and decisioning logic. Some Indian banks have worked with international firms, including Australian groups like Team400, on the Microsoft AI consulting and Azure-side architecture for AA-integrated underwriting platforms.

The financial information provider side

The FIP coverage has improved materially. All major banks are live as FIPs, GSTN data is accessible, and several insurers have completed integration. The remaining gaps are around mutual fund and depository data, where the SEBI-side consent framework intersection with AA has been complex.

The GSTN integration through Sahamati Connect is actually one of the most underrated infrastructure pieces. SME credit assessment that uses both bank flows and GST returns is fundamentally better than either signal alone. The fraud-resistance of GST data — because of the matching against counterparty filings — adds a layer that bank statements don’t have on their own.

Consumer awareness — still poor

The end-user understanding of AA remains weak. Most consumers who’ve used AA-mediated flows in lending applications don’t realise the framework is a thing distinct from “the bank checking my statements.” The branding decision to keep AA largely invisible to consumers — embedded inside lender flows rather than presented as a consumer-facing infrastructure — was probably correct from an adoption perspective, but it has limited the broader consumer conversation about consent-based financial data sharing.

The Reserve Bank Information Technology Private Limited (ReBIT) has done some good work on standardising the consent UI. The newer consent flows in Onemoney, CAMS Finserv, and Finvu are noticeably cleaner than the 2022-era versions. The cognitive load on consumers around AA consent is still higher than it should be.

What the next phase needs

I’d argue four things are needed for AA’s next adoption phase:

Insurance regulator alignment. IRDAI needs to operationalise its AA framework with the same firmness the RBI has shown. The consultation cycle has been too long.

Public sector bank operational integration. The PSB AA-FIU activity is well below what their balance sheet share would suggest. The IT integration backlogs and process change inertia are real, but solvable with focused effort.

Mortgage lender redesign. The home loan underwriting process is the obvious unconquered vertical. Whoever cracks the AA-native digital mortgage at scale will win meaningful share.

Better consumer narrative. The privacy and consent advantages of AA over the old screen-scraping and PDF-emailing approaches are genuinely strong, and a clearer public conversation about that would help sustain the framework politically and improve user trust. Bloomberg’s coverage of comparable open banking frameworks in the UK and Australia has been more substantive than the Indian press coverage of AA, and that’s a missed opportunity.

The framework is solid infrastructure. The next phase of adoption is fundamentally a change-management and policy alignment problem more than a technology problem. The next 18 months will determine whether AA becomes the credit infrastructure backbone everyone hoped for, or settles into being a useful-but-bounded tool used mainly by the digital-native fintechs.