Banks need artificial intelligence for corporate lending: CEA Krishnamurthy Subramanian

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October 15, 2020 9:38 PM

The CEA said lending to MSMEs (Micro, Small and Medium Enterprises) in the country has remained stagnant for the last 15 years indicating that banks have not developed models to actively lend to the sector.

Chief Economic Advisor Krishnamurthy Subramanian

 

Indian banking sector needs to use emerging technologies such as Artificial Intelligence (AI) and machine learning for corporate loans for quality lending, Chief Economic Advisor Krishnamurthy Subramanian said on Thursday.

Speaking at a virtual summit organised by Intel and Indian School of Business, he said lending to MSMEs (Micro, Small and Medium Enterprises) in the country has remained stagnant for the last 15 years indicating that banks have not developed models to actively lend to the sector.

“So, the Indian banking sector can really benefit from implementing this (AI and machine learning) especially in the context of corporate lending…And evidence shows that when the better models are employed, banks that employ such models are able to grow their balance-sheets in a very robust manner without suffering quality issues. This is a very important opportunity,” he said.

According to him, banks, including private ones, are using these analytical models primarily in the context of retail lending and have not used much in corporate lending. Subramanian said the use of AI and machine learning in the agriculture sector can enable better crop choice and crop diversification which are one of the key issues that exist in the country.

Stating that credit penetration is low in the country at 52 per cent to the GDP, he said even if India grows it by three-fold it would be at the average of the OECD (Organisation for Economic Co-operation and Development) countries, the average of which is pegged at 160 per cent. Speaking in the summit, Telangana Principal Secretary Jayesh Ranjan said the state aims to train 30,000 people in AI in the next three years to cater to the demand.

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