Council Post: Account Aggregators are the way forward for the Lending Industry

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An overview of the Lending industry

Lending has been an industry that can be traced back to 3000 B.C. ancient Mesopotamia. Farmers would borrow seeds with the promise of harvest. In India, lending has been present since Vedic times. Post-independence, Indian banking went through rapid growth during 1947-1983 and the Reserve Bank of India was set up to regulate the banking and financial institutions of the country. The banking Regulations Act, empowered the RBI to control the interest rates of loans issued by banks. Let’s now take a leap into the lending market today.

Advent of Digital Lending

Previously, the entire loan application process was highly manual with a huge amount of documentation and few key people possessing absolute power in disbursing the loan. This system had many loopholes and occasionally led to controversies. Nowadays, with digitisation many flaws in the system have been fixed. With AI/ML and statistical analysis, lending institutions are able to make more accurate decisions. Another leap is the credit score.  Every individual’s liability information is shared with certain organisations whose sole purpose is to store and collate financial liability information of individuals which can be then statistically analysed to assign a credit score. This credit score is a number that can be then used by organisations to assess the credit worthiness of a loan applicant. Every financial institution responsibly shares the borrower and loan information along with the repayment behaviour with these organisations as they also benefit by using this information. 

With the percolation of smartphones, digital lending has taken the market by storm as a loan can be applied with the click of a button. All this is possible with a centralised financial infrastructure along with data analytics which gives insights into consumer financial behaviour and strength. But there is a striking grey area here as well.

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The Grey Area

In India, we are observing more and more people taking loans for a variety of purposes. So, naturally, there are a lot of first timers whose liability information is unavailable. Thus, with no credit score, it’s tough for organisations to take a call on these cases. Another scenario is that the credit scores are updated at fixed intervals which means the latest information may not be available. This therefore does not assure us of the individuals’ future abilities to clear out his liabilities. Thus, the idea of consensually sharing financial information came up wherein users can consent their financial data being shared with certain designated organisations who can then share it with the financial institutions when requested. These are called account aggregators, let’s take a look into them.

Account Aggregators as Alternate Options

The account aggregator, often known as AA, is a Non-Banking Finance Company (NBFC) under the control of the RBI that makes it possible for customers’ financial information to be collected from financial information providers (FIP) with their permission. Customers can consent to sharing of this information which will eventually benefit them. This is mainly because this information can clearly highlight the financial strengths of an individual to lending institutions by giving them the leverage to calculate an accurate credit worthiness compared to traditional credit bureau scores. The Financial Information Provider (FIP) is an Entity who would have the financial information of an individual and who would, upon request, share it with the account aggregator. The Financial Information User (FIU) is an entity who would be using the customers financial information for their analysis and assessments. The Account Aggregator is an intermediary who provides a smooth pipeline for exchange of this information. The primary responsibility of an Account Aggregator seems to be managing the permissions and consent of data exchange as well providing a safe harbour to share this information. 


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Current State of Account Aggregators

As of January 2023, it already has approximately 266 organisations registered as financial information users (FIUs), 54 banks, and 24 life insurers and other financial entities totalling 96 financial information providers (FIPs) on its platform under various stages of implementation. According to estimates, the yearly transaction volume for the possible transfers of bank account statements through AA for various use cases across the financial sectors would reach 1 billion by 2025 and 5 billion by 2027.

Pros 

  • There is improved revenue as companies can provide better value proposals to the customers. This also leads to customer satisfaction and deeper customer engagement as services can be better personalised. 
  • There is also better productivity as products can be fine-tuned to cater to a larger customer base. 
  • With the availability of financial information, every company can take additional factors into consideration when assessing an individual for credit worthiness. The bureau only provides liability information which is also not very recent as the bureau takes time to update information at their end. 
  • As account aggregators will directly partner up with the Financial Information Sharing institutions, it will be easier for them to give more recent information. This information gives deep insights into the financial behaviour of the person which in turn will help in behavioural analytics which can then be used to generate a better credit report. 
  • The amount of fixed investments in the form of bank deposits, income generated every month, the expenditure, investments in equity markets, bond market and more give an insight into the customers’ investment and expenditure behaviours which, in turn, helps the lending institutions to fine-tune their products for the customers and also have a detailed picture of their worthiness to pay any loans.

Cons

  • The downsides that have been brought out are majorly on the privacy concerns. Since confidential financial information is being stored, there is a huge concern about who is privy to all this information. 
  • The security infrastructure of the data storage organisation is also of great concern as any leakage would cause an enormous privacy risk. Thus, this also highlights the need for a strong data governance platform. 

Use Cases Using AA Framework

The income expense data can be analysed to give best possible investment options in the form of Personal Financial Management (PFM) products with less or more risk and returns. The institution can also issue timely advisories on newer financial products or the status of existing products if they find that the customer’s financial behaviour can be used to improve their wealth based on the market trends. This level of micro-level analytics would in turn help the customer to benefit from better investments. Lending institutions can use this information to assess the credit worthiness of a customer with in-depth analytics combined with credit score which can serve as an additional guardrail for them.  

Conclusion

With the advent of a new financial data aggregation framework, lending institutions can cater to their customers with even more personalised products. As the saying goes “money loop must continue”, thus it creates more opportunities for lending institutions to utilise this new platform, highlights its benefits to the customers and gets the solutions off ground as soon as possible. This will expand the lending business in India, further creating more market opportunities, inclusion for common citizens and scope for expansion, thus beginning a new dawn for lending.

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here

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Gaurav Bansal
Gaurav is a technology leader whose focus is on building, implementing data strategy for organisations using enterprise data lake and subsequently providing hyper personalised customer experience through data analytics. He has published 5 patents in Machine Learning, Analytics and Innovation, Presented papers in AI/ML forums & Agile adoption and is known for enabling people on the ground and building high performing engineering teams. Gaurav is currently the Head of Analytics at L&T Financial Services.

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