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Banks are looking for technology solutions to tap the 'New to Credit' consumer segment

With ‘New to Credit’ borrowers, banks often come across stringent risk modelling challenges. Unique solutions can help to protect their quality of assets.

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CIOL Bureau
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Banks are looking for technology solutions to tap the 'New to Credit' consumer segment

Ever since the outbreak of Covid-19 in 2020, Indian banks and the NBFC sector has taken a huge toll in terms of asset quality and future business prospects. After the first wave subsided early this year, there was some optimism in terms of loan recovery. But the second wave seems to have taken over way too quickly. It has led to state-level lockdowns, almost all around the country. While such moves are important to save lives, it hampers jobs and businesses. Thus, it will have a direct impact on the repayment ability of millions of people.

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Banks and NBFCs have to be cautious about recoveries in their existing portfolio in such a difficult scenario. At the same time, they also need to tap newer opportunities with optimal risk vs rewards calculations. In such times, a high potential business segment in such a time is people in the ‘new-to-credit’ segment. Many of them are rebuilding their lives after the first wave of Covid-19 or even planning to start a new business as they fear that the second wave may not let them keep their existing jobs. For banks and NBFCs, identifying these people, making credit affordable and accessible to them, is the key for business growth.

The endeavour is also key to the economic revival of the country amid such times. Technology will play a very important role in enabling banks to tap into this opportunity and strengthen their retail lending portfolio. Here are some ways this can be done:

Credit decisioning

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‘New to Credit’ customers have unique needs and psyche. Banks can partner with technology companies that offer AI-driven behavioural templates to understand these needs and psyche in greater depth and take credit decisions more objectively. Some elements of these templates could be repayment patterns, how consumers respond to bank’s messages, and compliance with the documentation process.

If there are any anomalies on these fronts, the bank can move swiftly to step in and take relevant action. Such insights also help create a customized, positive experience for borrowers. Moreover, the experience leads to a better relationship between lenders and borrowers and ensures timely repayments, more often than not.!

Risk modelling

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When engaging with ‘New to Credit’ borrowers, banks often come across stringent risk modelling challenges. However, thanks to technologies such as AI-driven risk management, collections digitization and user behaviour-driven fraud prediction, the risk modelling for this segment is much simpler.

Additionally, with the proliferation of data sciences, tech companies can build solutions that leverage a low & mid-income borrower’s smartphone as virtual collateral for a microloan. By deploying such unique solutions, banks can serve billions of unbanked and underbanked people even as they protect their quality of assets.

Process automation

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The entire journey for a ‘New to Credit’ customer contains several steps which can be easily automated through technology. Some of these steps include initial documentation, payment reminders, and repayments etc. Automating these processes reduces the turnaround time & operating costs improves collection efficiency & productivity of on-ground collection agents, and simplifies the overall experience for borrowers.

The potential of technology is extremely significant when it comes to creating universal access to formal credit. As lenders move into safer, untapped avenues, they can grow their loan book without having to compromise the asset quality. At the same time, borrowers also become part of the financial mainstream; take care of their financial needs, and create credit history that is useful for their future borrowing. At the end of the day, it is a rewarding experience for all the stakeholders.

Author: Neel Juriasingani, CEO & Co-founder, Datacultr

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