The Indian digital banking sector is one of the fastest growing sectors in the country. What used to be largely unorganized has seen a lot of progress and unprecedented growth in the last decade. At almost 200 million, the unbanked population in India is one of the highest in the world, keeping them outside the gambit of formal credit.
Digital Banking with its technological innovations has changed all this. We have come to realize that lending or other banking services are no longer constrained to the doors of a bank. Technology has changed the way customers use financial services. In the past getting a loan was a lengthy and cumbersome process with huge paperwork involved. Now with the rise of digital lending platforms using the latest cutting edge technology, borrowers can get instant loan approvals and money in their banks in a matter of a few hours.
Technological innovations have led to major changes in the efficiency, productivity, inclusion and competitiveness in the market. However, this unprecedented growth has also resulted in unintended consequences like breaches in customer data and mis-selling to customers.
In order to make sure that the industry continues to grow while benefiting the end consumer, the need for regulation became necessary. Regulation often gets a bad rap for either not doing enough in times of crisis or doing too much — creating barriers to progress and innovation and slowing us down. However if you look at it from a different perspective, you realize that, when it comes to public money, a world without regulation is a world of chaos.
RBI’s new guidelines on Digital Lending were released in November 2021, with an aim of curbing rising malpractices in the digital lending ecosystem. The guidelines were formulated following the recommendations of a working group for digital lending, whose report was made public in November 2021. These new guidelines will ensure that the fintech ecosystem stays ahead of the curve while safeguarding customer data.
The latest guidelines broadly address the following areas:
- Customer protection
- Technology requirements
- Regulatory requirements like appropriate disclosure of information to customer and documentation
These much awaited guidelines to regulate the digital banking industry provide clarity on digital lending practices, seek to protect the customer and accountability of stakeholders in digital lending. These guidelines apply to existing digital loan customers and those who apply for loans in the future via digital banking channels.
Digital lenders have played a crucial role in widening the reach of credit across the country and lowering the cost of borrowing for many segments. The RBI guidelines while focussing on protecting the borrower also emphasize on the need for innovation in technology. A fintech platform that is adaptive is especially useful in times of change.
Agile tech stack for quick adaptability
During the pandemic, RBI announced successive loan repayment moratoriums between Mar-Aug 2020 with considerable uncertainty on further extensions. To complicate matters, the customers had a choice to avail it or not. Lenders had to work double time to take requests from customers and regenerate the payment schedule on the tap. Accounting for interest capitalization and interest-on-interest was again unclear as the RBI, the Govt. and the Supreme Court were considering the issue at length. Lenders had to be extremely nimble to accommodate any changes quickly. This requires a modern loan management system and the associated customer communications platforms to work efficiently.
At the end of the moratoriums, there was considerable stress in the economy with high unemployment rates. Borrowers were unable to make loan repayments. The RBI allowed one time restructuring of loans to reduce the monthly cash-outflow for the borrowers. This required customers to understand the new terms & conditions and sign new agreements.
A nimble yet resilient software architecture was the key to achieve this. This enables the company to better engage with the customers and not be limited in terms of product offering.
Credit Risk Model using Machine Learning
Data Sciences based credit models offer better user engagement for customers to transact securely. Data Sciences based Credit models are not only easy to moderate but also can be replicated to offer products contextual to different segments. These models continuously monitor correlating variables and adjust weightages accordingly, to churn out the best predictions on risk profiles. This is a continuous self learning loop mechanism. The models are built modular in structure which helps in customization based on various available data sets. Being modular makes them more scalable.
Working within the existing framework gives finance experts the chance to think outside the box, and come up with systems that make our financial lives easier while implementing new ideas that keep the consumer secure.
Regulation exists in lending to protect the most vulnerable. Digital lending companies have to embrace the regulation and stop exploiting any loopholes that might exist. Implementing all of this requires considerable change in the culture of software development and technology.
Companies that absorb regulation as part of their DNA can innovate while knowing the boundaries and how to push them without compromising the customer.
Views expressed above are the author’s own.