Breaking Barriers: How Account Aggregators Are Changing the Game in Data Sharing

Imagine a world where managing your financial life is as simple as using a single app. Whether it's applying for a loan, tracking your investments, or getting insurance, everything is at your fingertips. This is not a distant dream but a reality being shaped by the Account Aggregator (AA) system in India.

The adoption of the AA system has been rapid and promising. Since its public launch in August 2021, the number of linked accounts and consent requests has been growing exponentially. As of now, millions of accounts have been linked through AAs, with a consistent month-on-month growth rate of over 22%. The system's early adoption has been impressive, with over 76 million accounts. Financial institutions and fintech companies have quickly embraced the AA framework to streamline their services and enhance user experience.

Decoding the Account Aggregator: What It Is and How It Works

The Account Aggregator (AA) framework is a revolutionary step in financial data management in India. It simplifies how individuals and businesses can share their financial information with various service providers. Let's break down the key components and processes involved to understand how this system works.

Definition and Roles of AAs, FIPs, and FIUs

To grasp the functionality of the Account Aggregator system, it's essential to understand the roles of the key players: Account Aggregators (AAs), Financial Information Providers (FIPs), and Financial Information Users (FIUs).

Account Aggregators (AAs):

• Definition: Account Aggregators are licensed entities regulated by the Reserve Bank of India (RBI). Their primary role is to facilitate the secure and efficient transfer of financial data from FIPs to FIUs with the explicit consent of the user.
• Role: AAs act as intermediaries that manage the consent process and ensure that financial data is shared only with the user’s permission. They cannot read or store the data themselves; they merely transport it from the source to the requester.
• Example: Think of an AA as a digital courier service. Just as a courier ensures that your package reaches its destination securely, an AA ensures your financial data reaches the intended recipient without any breach of privacy.

Financial Information Providers (FIPs):

• Definition: FIPs are entities that hold a user's financial data. This can include banks, insurance companies, mutual fund houses, pension funds, and other financial institutions.
• Role: FIPs supply the requested financial data to AAs once they receive a valid consent request from the user.
• Example: Your bank, which holds details about your savings and transactions, is an FIP. When you need to share your bank statements with a loan provider, the bank (FIP) supplies this information through the AA system.

Financial Information Users (FIUs):

• Definition: FIUs are entities that need access to a user’s financial data to provide services. These can be lenders, financial advisors, insurance companies, or any other financial service providers.
• Role: FIUs request data from AAs to assess a user’s financial health and offer appropriate services.
• Example: A loan provider (FIU) needs to evaluate your creditworthiness. They use the AA system to request your financial data, such as bank statements and income details, to make an informed decision.

The Process of Data Sharing and Consent Management

The Account Aggregator system revolves around a user-centric consent mechanism that ensures privacy and control over personal financial data. Here's a step-by-step look at how the process works:

User Onboarding and Account Linking:

• The user signs up with an Account Aggregator (AA) through an AA mobile app or an embedded interface within a financial service app.
• The user links their financial accounts (e.g., bank accounts, insurance policies) to the AA using their unique AA handle (e.g., sunny@finvu).

Consent Request and Approval:

• When an FIU (e.g., a loan provider) needs the user’s financial data, it initiates a consent request through the AA system.
• The user receives a detailed consent request on their AA app, specifying what data is needed, for what purpose, and for how long.
• The user reviews and approves or rejects the consent request. If approved, the AA generates a digital consent artifact that is sent to the FIP (e.g., the user’s bank).

Data Fetching and Sharing:

• Upon receiving the consent artifact, the FIP prepares the requested data in a standardized, machine-readable format.
• The AA securely transfers this encrypted data to the FIU.
• The FIU decrypts and uses the data to provide the requested service, such as processing a loan application.

Consent Revocation:

• Users can revoke their consent at any time through the AA app, stopping the FIU from further accessing their financial data.
• Once consent is revoked, the FIU must delete any stored data as per the agreed terms.

Real-World Applications: Transforming Financial Services

The Account Aggregator (AA) system is not just a theoretical concept; it has practical, transformative applications across various sectors of the financial services industry. By enabling seamless, secure, and consent-based data sharing, AAs are poised to revolutionize lending, insurance, and wealth management. This section explores these use cases and highlights the benefits for both individuals and businesses.

Examples of Use Cases for AAs

1. Lending

Streamlined Loan Applications: Traditionally, applying for a loan involves gathering numerous financial documents, which can be time-consuming and cumbersome. With AAs, borrowers can consent to share their financial data directly from their bank accounts, tax returns, and other financial institutions with lenders. This streamlined process accelerates loan approvals and reduces administrative overhead.

Example: Ankit, a small business owner, needs a loan to expand his store. Using an AA-enabled app, he consents to share his bank statements and GST returns with the lender. The lender quickly accesses this consolidated data, processes the loan application in a fraction of the time, and Ankit receives his loan within days instead of weeks.

Enhanced Credit Assessment: Lenders can access a more comprehensive and accurate financial profile of borrowers, including their income, spending patterns, and existing liabilities. This leads to better credit risk assessment and more tailored loan products.

Example: Priya, a salaried employee, applies for a personal loan. By sharing her salary account details and monthly expenditure patterns through an AA, the lender gets a clear picture of her financial health and offers a loan with favourable terms that align with her repayment capacity.

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2. Insurance

Simplified Policy Issuance: The AA framework can simplify the process of buying insurance by allowing insurers to access necessary financial data directly with user consent. This reduces the need for extensive paperwork and accelerates policy issuance.

Example: Rajesh wants to purchase health insurance. Instead of submitting various documents manually, he uses an AA to share his financial and medical history with the insurer. The insurer quickly verifies his information and issues the policy within a day.

Personalized Insurance Products: By accessing detailed financial and health data, insurers can design personalized insurance products that better match the needs and risk profiles of individuals.

Example: Meera, who leads a healthy lifestyle, shares her fitness tracker data and health records via an AA with an insurer. Based on this data, the insurer offers Meera a health insurance policy with a lower premium, rewarding her healthy habits.

3. Wealth Management

Consolidated Financial View: AAs can aggregate data from various financial accounts, providing users and wealth managers with a consolidated view of their financial portfolio. This holistic view facilitates better financial planning and investment strategies.

Example: Sunil, an investor, uses an AA-enabled app to link his bank accounts, mutual funds, and stock investments. His wealth manager accesses this consolidated data to provide personalized investment advice and optimize Sunil’s portfolio for better returns.

Automated Investment Advice: Robo-advisors can use the data provided through AAs to offer automated, algorithm-driven investment advice tailored to individual financial goals and risk tolerance.

Example: Anjali wants to start investing but is unsure where to begin. She uses a robo-advisor app that accesses her financial data through an AA. The app analyzes her income, expenses, and savings to create a customized investment plan, helping Anjali achieve her financial goals.

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The Future: Dynamic Switch and Enhancing Reliability in the Account Aggregator System

Account Aggregators (AAs) are transforming the way financial information is accessed and shared in India. However, one significant challenge that users and businesses face is the reliability of data retrieval. To address this issue, Finsire offers the Dynamic AA solution, which optimises the chances of successfully obtaining users' financial data by recommending the top three AAs with the highest likelihood of success. Here's how this innovative solution works and why it matters.

The Problem: Reliability in Data Retrieval

While AAs promise a streamlined process for accessing financial information, there is no guarantee that users will get the data they need every time they request it. This inconsistency can be frustrating and can hinder the adoption and effectiveness of the AA framework.

Example: Imagine Meera, a small business owner, trying to apply for a loan. She needs to share her financial data through an AA. However, due to reliability issues, her data request fails multiple times, delaying her loan application process. This experience can be discouraging and may lead her to revert to traditional, more cumbersome methods.

The Solution: Finsire’s Dynamic AA

Finsire’s Dynamic AA solution enhances reliability by recommending the top three AAs most likely to succeed in retrieving the required financial data. This recommendation system is built on the integration of the top six AAs, ensuring maximum Financial Information Provider (FIP) coverage, from banks to depositories and RTAs.

How Dynamic AA Works

The Dynamic AA solution employs a recommendation engine that evaluates several parameters to determine the best AAs for data retrieval. Here are the key factors considered:

1. FIP-AA Mapping: The system checks if an AA is integrated with the required FIPs. There is no benefit in recommending an AA that isn't connected to the necessary FIP for the user's data request. Example: If Ramesh needs his bank statements from HDFC Bank, the system ensures that the recommended AAs are integrated with HDFC.
2. Metrics from Sahamati: Sahamati provides open-source data on the success and failure rates of FIPs. This data helps assess the current health and reliability of each FIP, informing the recommendation engine.
3. Hit Rate: This measures the number of successful data retrieval attempts made through AAs within Finsire’s ecosystem. Higher hit rates indicate more reliable AAs.
4. Latency: Lower latency means faster data retrieval, improving user experience. The system evaluates how quickly each FIP responds to data requests, recommending those with optimal performance. Example: Priya uses an AA to link her account with ICICI Bank. The system recommends AAs with the lowest latency for ICICI, ensuring a smooth and quick data fetch process.

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