AI-based systems can be used to determine good, bad credit risk: Nilekani
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Infosys chairman Nandan Nilekani also said the AI-based credit disbursal systems would make access to funds easier, especially for small and medium enterprises. Photo: PTI

AI-based systems can be used to determine good, bad credit risk: Nilekani

Infosys chairman Nandan Nilekani on Tuesday explained that Artificial Intelligence (AI) can be used to figure out good and bad credit risk, and rates at which loans are given can be tweaked based on such assessment.


Infosys chairman Nandan Nilekani on Tuesday (February 4) explained that Artificial Intelligence (AI) can be used to figure out good and bad credit risk, and rates at which loans are given can be tweaked based on such assessment.

“Today, big guys get cheap credit, small people get expensive credit through money lenders and all. All that will go away,” he added. Asked about his message for entrepreneurs, the Aadhaar architect said they should focus on “getting to the path of profitability fast,” Nilekani said at an event.

He also said the AI-based credit disbursal systems would make access to funds easier, especially for small and medium enterprises.

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“We shouldn’t get distracted by the current challenges. Obviously we have an issue with bank Non-Performing Assets (NPAs), non-banking financial company NPAs, but out of this will emerge the next generation of credit which is going to be entirely tech and data-based,”

He said credit decisions by AI-driven systems will be based on business flows rather than being asset-based. “It is good for newcomers because they may not have assets,” he said.

A recent Reserve Bank of India (RBI) report had said non-bank lenders witnessed stress in their asset quality in the first half of the current fiscal, with gross NPA ratio increasing to 6.3% in September 2019 from 6.1% in March.

He added that internet businesses globally had turned profitable after a few years of losses, and therefore, getting to that path should be kept in mind.

(With inputs from agencies)

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