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India's Account Aggregator (AA) framework is arguably the most ambitious open banking initiative in the world. Built on the Data Empowerment and Protection Architecture (DEPA), AA enables consent-based financial data sharing between institutions — without the institution holding the data needing to build a bilateral integration with every requesting party.
For FD distribution, this is transformative.
The AA ecosystem has four participants:
| Role | What They Do | Examples | |------|-------------|---------| | Financial Information Provider (FIP) | Holds user's financial data (bank statements, investment records) | Banks, mutual fund houses, insurance companies | | Financial Information User (FIU) | Requests and uses the data (with user consent) | Lending platforms, wealth managers, FD distributors | | Account Aggregator | Facilitates the data flow between FIP and FIU | CAMS Finserv, Finvu, OneMoney, NADL | | Customer | Owns the data, grants/revokes consent | End user |
The flow:
Critically, the AA never stores the data. It's a consent-mediated pipe, not a data store.
Today, FD booking requires the customer to manually enter income, occupation, and bank account details. With AA, this data can be pulled from existing bank accounts — with consent.
Before AA: Customer types income as "Rs 5-10 lakh" (often inaccurate), manually enters bank account number and IFSC code.
With AA: System pulls actual income data from salary credits in bank statements, verifies bank account details directly from the source.
Result: Fewer errors, faster booking, higher conversion.
For certain FD products (particularly those with loans-against-FD features or higher-value deposits), income verification adds a layer of trust. AA provides:
This enables:
With AA data, FD platforms can match customers to the right issuer more intelligently:
This moves FD distribution from "show all rates, let the user figure it out" to "here's the best option for your specific situation."
AA data can complement the KYC process:
Combined with Aadhaar eKYC and CKYC, AA creates a path to near-instant KYC for customers who have existing banking relationships.
Early implementations of AA-enhanced financial product applications show measurable conversion improvements:
| Metric | Without AA | With AA | Improvement | |--------|-----------|---------|-------------| | Application completion rate | 60-70% | 80-90% | +15-25% | | Data accuracy | Self-reported (variable) | Source-verified | Significant | | Time to complete application | 8-12 minutes | 3-5 minutes | 50-60% faster | | Drop-off at income/bank details step | 15-20% | 3-5% | 75% reduction |
These numbers are directional (based on lending applications using AA), but the FD booking flow has similar friction points — and similar potential for improvement.
AA adoption varies across the banking ecosystem:
| Bank Category | AA Readiness | FD Distribution Impact | |--------------|-------------|----------------------| | Large private banks (HDFC, ICICI, Axis) | FIP-ready, active | Data source for FD applicant verification | | Public sector banks (SBI, PNB, BOB) | FIP-ready, growing | Large customer base available for AA data sharing | | Small Finance Banks | Emerging FIP participation | Can be both FIP (data source) and beneficiary (FD issuer) | | NBFCs | FIU-active, some FIP | Primarily consuming AA data for underwriting | | Fintechs | FIU-active | Primary users of AA data for product enhancement |
For FD distribution, the key dynamic is: the banks where customers already have accounts (data sources) are different from the banks offering the highest FD rates (issuers). AA bridges this gap — a customer's SBI bank statement data can inform their FD booking with a Small Finance Bank offering 9%+.
AA is built on consent. Every data request requires:
For FD platforms, this means:
For fintech platforms looking to add AA-enhanced FD distribution:
User initiates FD booking
→ Platform requests AA consent
→ User approves on bank app
→ AA fetches data from FIP (user's bank)
→ Platform receives encrypted data
→ Data processed for:
- Income verification
- Bank account pre-fill
- Rate recommendation
- Risk profiling
→ FD booking continues with enhanced data
| Requirement | Details | |------------|---------| | AA certification | Register as FIU with AA ecosystem | | Consent management UI | Present consent requests clearly, manage consent lifecycle | | Data processing | Parse bank statement data, extract income patterns, verify accounts | | Encryption | End-to-end encryption as per AA technical specifications | | Audit trails | Log all data access with consent references |
The convergence of AA with FD distribution infrastructure points to several near-term innovations:
"Your salary of Rs 75,000 was credited today. Based on your spending pattern, you could save Rs 25,000 this month in a 9% FD."
"Move any balance above Rs 50,000 in your savings account into an FD at the end of each month" — powered by AA balance monitoring + automated FD booking.
When an FD approaches maturity, AA data can inform the renewal recommendation: "Your income has increased 20% since you booked this FD. Consider a larger deposit this time."
With AA providing a consolidated view of the customer's deposits across banks, platforms can recommend optimal allocation: "You have Rs 6 lakh in one bank. Consider splitting across 2 banks for full DICGC coverage."
AA doesn't replace FD infrastructure — it enhances it. You still need the KYC engine, payment orchestration, multi-bank integration, and compliance framework. But AA adds an intelligence layer that:
For platforms already using white-label FD infrastructure, AA integration is the next evolution — turning a standardized booking flow into a personalized financial experience.
Blostem's FD infrastructure is built to work with India's evolving open banking ecosystem. Explore our platform.
Get in touch with our team to discuss how Blostem can power your platform.
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