Account Aggregator: Opening the floodgates of innovation

Until the advent of Account Aggregator (AA), banks played Jekyll and Hyde — on the one hand they would strictly warn against sharing net banking credentials, and on the other hand, they would insist on sharing the same when they had to lend.

This confusion was resolved by AA — the fiduciary entity sitting in the middle of Financial Information Providers (FIPs) and Financial information Users (FIUs). AA ensures customer consent as FIUs retrieve data from FIPs in usable formats. Therefore, the AA framework opened up new avenues for data-driven businesses, giving API economy a bigger boost.?

The beauty is that AA not only democratised data but also added a privacy layer.?

However, the AA ecosystem is still in its nascent stage. But the time is ripe for new entrants to be movers and shakers in the space.?

Hence, I have outlined some of the AA use cases that could serve as the base for new business models.?

1. With read-only access to account information, banks can offer highly personalised financial products and take the CX journey a notch higher.
2. AA can help lay the foundation for software services that cater to segments such as personal finance management, wealth management, and digital financial accounting.
3. It can form the skeleton of financial modelling tools that help startups strategize better, optimise growth, and of course, build better pitch decks with ease.
4. The most obvious use case is lending; banks and FinTechs can factor account information (that too with user consent) into their credit-scoring models. All underwriting-based businesses stand to gain significantly from AA.?
5. Big data technology players can create models built on large databases of account information by procuring data from users through explicit content. This way, ordinary users will also be able to monetise their data.?
6. AA can help Enterprise Resource Planning providers improve their products by enabling better forecasting capabilities based on real-time insights.
7. Last but not the least, platforms that facilitate sharing of information with a NBFC AA licence make for a great business model. They can earn revenue through a fee-based or transaction-based model, and the beauty is that financial institutions are willing to pay for data.?

Above all, AA puts ordinary men and women in charge of their own data. Until a few years ago, all data was proprietary. And that’s why service providers could afford to offer mediocre financial products and be unaffected by it. But that’s changing. The industry is becoming highly competitive.?

Going beyond AA

AA is a step in the right direction. But it cannot stop at AA.? Because there are several more information gaps that need filling which would enable lenders to truly realise India’s dream of financial inclusion.?

Access to information must go beyond financial data and electronic footprint for lenders to be able to ace the underwriting game, and reach a level where unsecured loans create zero insecurities.

For instance, consider use cases such as gig economy workers, say a Swiggy delivery partner or an Uber cab driver, or for that matter, a larger part of the unorganised workforce with little to no credit history.?

In these cases, integration of non-financial data points such as history of trips done by an Uber driver/partner in the last one year, customer ratings, trip cancellations, off days, etc can further enrich credit algorithms and reduce cost and time to process the loan.?

Gig platforms and aggregators like Ola, Uber (transportation), Swiggy and Zomato (food delivery), Oyo, MakeMyTrip, Yatra (hotels and home businesses), Urban Company, HouseJoy (professional services), Dunzo, Big Basket, JioMart (hyper-local delivery platforms), can have linkages with the AA platform and function as ancillary information systems sharing non-financial data of gig workers — this can further improve access to affordable credit and help new-to-credit customers borrow viably.??

AAs have a pivotal role to play in this emerging ecosystem. Democratising data in meaningful ways can reveal innumerable opportunities, hitherto unimagined.?