How Lendingtech Startups Are Using AI, ML To Revisit Underwriting To Boost Financial Inclusion

How Lendingtech Startups Are Using AI, ML To Revisit Underwriting To Boost Financial Inclusion

SUMMARY

Instead of focussing on collateral-based bank loans, these fintech startups are using artificial intelligence (AI), machine learning (ML) and data analytics to offer loans to the underserved players of the country’s key sector

Fintechs look at things more broadly by analysing huge amounts of data and correlating it to make lending decisions – unlike banks that conduct underwriting in a more traditional way, says Progcap’s Shrivastava

Speaking at Inc42’s TMS 2023, Lendigkart’s Lunia highlighted the need for innovation in collections

Despite being one of the chief contributors to India’s GDP, the country’s micro, small and medium enterprises (MSMEs) are marred by a plethora of challenges ranging from energy crisis and cost of power to unavailability of financing options due to inadequate working capital, insufficient bureau score, and lack of documents.

According to the RBI, the credit demand in the MSME space stands at $490 Bn against the overall supply from formal sources at $192 Bn, indicating how this sector remains underserved.

Further, even though the outstanding micro and small loans as on March 2022 grew by 21.5% to INR 4,95,281 Cr as against INR 4,07,675 Cr as on March 2021, the availability of credit continues to remain a pressing challenge for SMEs.

At Inc42’s The Maker Summit 2023 last month, Indifi cofounder and CEO Alok Mittal, Progcap cofounder Pallavi Shrivastava, and the CEO of Lendingkart Harshvardhan Lunia talked about how many fintech startups have emerged in the area over the past few years to bridge the gap.

Instead of focussing on collateral-based bank loans, these fintech startups are using artificial intelligence (AI), machine learning (ML) and data analytics to offer loans to the underserved players of the country’s key sector, according to the fintech leaders.

“The very reason why fintechs exist today is primarily because of the gap that’s been left by traditional lenders. There is a certain category or segment of customers which have been financially excluded. The idea has been that how do we find an alternative way to be able to assess the creditworthiness of these customers to make them financially included,” Progcap’s Shrivastava said.

Talking about how fintech players are doing a better job of financial inclusion, the Progcap cofounder said fintechs look at these things more broadly by analysing huge amounts of data and correlating it to make lending decisions – unlike banks that conduct underwriting in a more traditional way.

She, however, highlighted that lendingtech startups today need to work on feedback loops and understand customer pain points are some of the areas to be worked on.

“Once you’ve given out the money, what are you doing, what interventions are you doing in terms of capacity building for these customers in terms of ensuring that the customers are well aware, they understand the new financial product, they understand what you’re offering to them and can understand the importance of repaying the loan in time. So, it just doesn’t stop with data and underwriting. It’s a lot more to be able to keep the credit quality and portfolio healthy,” Shrivastava added.

Seconding the idea of having feedback loops, Indifi’s Mittal said that innovation is required in terms of usage.

“You disburse sort of loans and then performance comes by in another 12 months and then you define. In our case, decisions are also overseen by underwriters. So, there is this interesting play between what the model is saying and what the underwriters are saying and there is a learning opportunity by having the human in the loop there,” he added.

At the panel discussion organised by Inc42, Lendigkart’s Lunia highlighted the need for innovation in collections. He said that his startup has an algorithm which helps in understanding if a borrower is a middle-risk or high-risk customer.

“I think a lot of data that we are generating right now and the rightful use of that data could be used in collections as well,” he concluded.

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