Responsible lending is as important as responsible borrowing: RBI official

Responsible lending is as important as responsible borrowing: RBI official



A senior Reserve Bank of India (RBI) official urged banks to be responsible lenders while commenting on the significance of building consumer trust and protection in digital lending using artificial intelligence and machine learning (AI/ML) models.

“Responsible lending is as important as responsible borrowing,” said chief general manager of the RBI, Vaibhav Chaturvedi

“Customer trust and financial literacy cannot be solved overnight and is tricky, but there is urgency, with how digital lending is picking up”, said Vaibhav Chaturvedi, CGM, RBI, said speaking at Global Fintech Fest in Mumbai.

His comments are made amidst increased reliance on AI by banks, finance companies and fintech to assess a borrower’s creditworthiness and repayment capabilities.

The RBI CGM said that right now the central bank is leveraging AI models with a board based approach focusing on governance in the risk management guidelines, which is used to prevent negative experience for customers.

The size of digital lending is expected to be over $1 Trillion by 2030, according to a BCG report, and most of the loans will be disbursed using AI.“We use AI for multiple use cases, especially in the collection phase, where the algorithm classifies a person according to their borrower behaviour. About 15% of our borrowers are classified in the low, medium, high-risk category, where we can intervene and take the process forward”, said Harshvardhan Lunia, CEO, Lendingkart.Responsible borrowers are important, especially when the nation is young, and regional languages play an important role when it comes to pushing financial literacy contents, said Lunia.

Even the RBI governor Shaktikanta Das on Wednesday said that AI/ML are poised to revolutionise financial services in unprecedented ways. “AI algorithms are already being deployed for fraud detection. Machine learning models are increasingly being employed in credit scoring, leveraging predictive analytics to assess creditworthiness, and expand access to credit,” Das had said. “As AI and ML capabilities continue to evolve, their potential applications in regulatory compliance, investment advisory services, and algorithmic trading are expected to further redefine the financial landscape,” he said.



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