Perfios vs Finvu: Account Aggregator Integration Compared

Data Categorization vs Gateway Middleware

The strategic choice between Perfios and Finvu hinges on a single architectural question: does your product require an end-to-end analytical underwriting engine, or does your team want a clean, raw data conduit that you can parse using custom code?

• Perfios: An industry giant that provides end-to-end data analysis. Beyond simple document fetching, Perfios parses raw bank transactions, identifies salary credits, detects circular transactions, flags default risks, and classifies over 200 expense categories with 98% accuracy. Its analytics system turns messy bank statement data into a structured score, which is highly valuable for credit underwriting teams.
• Finvu: A specialized, highly efficient Account Aggregator gateway. Finvu focuses on maintaining ultra-reliable, low-latency API connections to retrieve raw bank statements. It doesn't parse or analyze the statements, leaving developers free to run their own custom scoring algorithms on the raw JSON. Its lightweight footprint is ideal for startups that want full control over their data pipeline.

Understanding the Account Aggregator Framework

The Account Aggregator (AA) network is a RBI-regulated financial data sharing framework. It operates under a strict consent architecture where the user acts as the consent giver. Data flows securely from a Financial Information Provider (FIP)—such as a bank (HDFC, SBI, ICICI) or mutual fund registry—to a Financial Information User (FIU)—such as your lending or wealth management app. The data is encrypted end-to-end: the AA itself cannot decrypt the data payload; only the receiving FIU possesses the private keys necessary to decrypt and read the transaction history.

Finvu API Integration: Requesting Consent

Integrating Finvu begins by requesting user consent to fetch their bank statements. Your application backend calls Finvu's consent creation endpoint, which returns a redirection URL where the customer registers or logs in with their AA ID (e.g. username@finvu) and approves the data access request.

Finvu Consent Creation Payload Example

Below is a structured JSON code example showing how to programmatically initiate a consent request via Finvu's network:

{
  "consentRequest": {
    "customer": {
      "mobileNumber": "9988776655",
      "vpa": "customer@finvu"
    },
    "consentDetails": {
      "fiuId": "FIU_PRODUCT_GROWTH_AA",
      "consentTypes": ["PROFILE", "TRANSACTIONS"],
      "fiTypes": ["DEPOSIT", "TERM_DEPOSIT", "MUTUAL_FUND"],
      "purpose": {
        "code": "101", // Wealth management or Lending
        "refUri": "https://api.productgrowth.in/loan/10982",
        "text": "Assessing eligibility for personal credit extension"
      },
      "dataDateTimeRange": {
        "from": "2025-12-26T00:00:00Z",
        "to": "2026-06-26T20:15:30Z"
      },
      "dataLife": {
        "unit": "MONTH",
        "value": 12
      }
    }
  }
}

Once the user enters their OTP and approves the request in the Finvu web view, Finvu sends a webhook callback containing a consentId. You then query their endpoint to retrieve the encrypted financial data, decrypting it using your private key registered in your local HSM (Hardware Security Module).

Detailed Comparison: Perfios vs. Finvu

Parsing Scanned Documents vs. AA Data

In India, while the Account Aggregator network is expanding rapidly, it is not yet universal. Many users—specifically in Tier-2 and Tier-3 cities—bank with local cooperative societies or Gramin banks that have not integrated with the AA framework. If your credit application only supports AA-based statement retrieval, you will reject a massive segment of creditworthy applicants.

To capture 100% of your funnel, you must maintain a hybrid integration architecture. Start by offering the Finvu AA gateway as the primary, low-friction option. If the user's bank is not supported on the AA network, provide a fallback interface to upload statement PDFs. This is where Perfios's OCR engine becomes essential. Perfios parses physical scans and password-encrypted PDFs, cleaning up alignment issues, decrypting statements, and extracting clean ledger values to feed your underwriting models.

Compliance and DPDPA Erasure Guidelines

Data retrieved via Account Aggregators falls under the strict purview of the Digital Personal Data Protection (DPDP) Act. Under DPDPA rules: - Lenders must specify a clear data retention limit in the consent request. - Once a loan is closed or rejected, all financial records must be purged. - Your system must include a dedicated data-management dashboard where users can view active consent permissions and revoke them in real-time. Developers must design their backend models with modular architectures, ensuring that deletion triggers target all tables storing transaction histories while preserving aggregated statistical metadata for regulatory audits.