India’s Account Aggregator (AA) framework is one of the most ambitious data infrastructure projects in global financial services. The concept is elegant: give consumers control over their financial data by allowing them to share it — with consent — between banks, insurers, tax authorities, mutual funds, and other financial institutions through a standardised, secure pipeline.

Launched in September 2021, the AA framework was expected to dramatically reduce friction in loan applications, insurance underwriting, and wealth management onboarding. Three years later, the architecture works. The adoption doesn’t match the ambition.

How It Works

The ecosystem has three participants. Financial Information Providers (FIPs) hold customer data — banks, mutual fund houses, insurance companies. Financial Information Users (FIUs) need customer data to provide services, typically lenders assessing loan applications. Account Aggregators manage the consent and data flow between them without storing or reading the data.

The customer controls everything. They choose what data to share, with whom, for how long, and can revoke consent at any time. Data flows encrypted end-to-end. Licensed AAs include CAMSfinserv, Finvu, OneMoney, and NADL.

This is genuinely good design. The architecture respects privacy, puts the customer in control, and eliminates the current mess of PDF bank statements and manually uploaded documents.

The Adoption Numbers

As of early 2026, the AA ecosystem has processed approximately 80-90 million consent requests since launch. That sounds substantial until you consider that India has over 150 crore bank accounts and processes several billion financial transactions monthly.

The Sahamati Foundation, which serves as the industry body for the AA ecosystem, reports that most usage is concentrated in lending — specifically personal loan and MSME loan origination, where lenders pull bank statements for income verification.

Usage in insurance, wealth management, and other financial services remains negligible. The vision of a comprehensive data-sharing ecosystem spanning all financial services is still largely aspirational.

Why Banks Are Dragging Their Feet

The primary bottleneck is on the FIP side.

Technical readiness. Many banks, particularly public sector banks, haven’t fully integrated with the AA framework. Some can share savings account data but not loan account data. Others have intermittent connectivity. The integration requires changes to core banking systems and ongoing maintenance.

Incentive misalignment. When a bank shares a customer’s bank statement data with a competing lender, it’s helping a competitor win business. This creates structural reluctance to invest heavily in making FIP systems work well.

The RBI has mandated FIP participation by all scheduled commercial banks, but the quality of that participation varies enormously. A mandate to connect isn’t a mandate to make the connection work reliably.

Customer awareness. Most bank customers have never heard of Account Aggregators. Without customer demand, banks feel limited pressure to improve their integration.

Where It Is Working

For MSME lending, AA-based data sharing reduces loan processing time from days to hours. Instead of asking a small business owner to collect six months of bank statements from multiple banks, a lender can pull the data in minutes with digital consent.

Some digital lenders report that AA-enabled applications have 40-50% lower dropout rates. The friction reduction directly translates to more completed applications and faster disbursements.

For credit assessment, AA data provides a richer picture than a credit bureau score alone. Cash flow patterns — salary regularity, spending behaviour, existing EMI commitments — help lenders make better decisions, particularly for borrowers with thin credit files.

Missing Use Cases

The more transformative applications remain unrealised. Insurance underwriting through AA is virtually non-existent. Tax filing integration with the Income Tax Department hasn’t materialised despite being discussed. A consolidated view of all financial assets for wealth management planning remains aspirational. Government benefit targeting through income verification is still theoretical.

Each of these use cases would make the AA framework significantly more valuable, but requires institutional agreements and technical integrations that haven’t been completed.

What Would Accelerate Adoption

Regulatory pressure on FIP quality. The RBI should set minimum uptime and data completeness standards for FIP participation, with consequences for banks maintaining poor connections.

Consumer awareness campaigns. The RBI and NPCI ran extensive campaigns for UPI adoption. A similar push for AA would build the demand-side pressure that’s currently absent.

Expanding data categories. Adding GST data, income tax data, and telecom data would make the framework useful for a wider range of applications.

Incentivising FIPs. Creating a revenue model where FIPs receive compensation for data sharing — even nominal amounts — would better align incentives.

India’s AA framework is architecturally superior to most international equivalents, including the EU’s PSD2 open banking framework. The gap between architecture quality and adoption rate is a product of execution challenges, not design flaws. The infrastructure is ready. The institutions need to catch up.