The report discloses that the Indian banking sector bodies have to invest deeply in data analytics and should enhance the existing technology in a much-improved version to figure out the right model for large corporate lending which would, in turn, spur the investment and help the economy grow into a $5 trillion one, said by country’s chief economic advisor Krishnamurthy V Subramanian.
In India especially two-third of the loan assets category is withheld and dominated by public sector banks. They have turned the risk-averse following a spate of large defaults by private sector promoters and entrepreneurs. Thus, this policy has inversely impacted the growth of the economy as well as it has affected the rate of investment which was delivered by Mr. Subramanian on Sunday at Bandhan bank’s anniversary lecture.
He also said that to bounce back or leapfrogging the public sector banks via fintech is essential. He also says that private sector banks also should invest in data analytics to improve their business and services as well as to improve their large corporate lending models which would help the banking sector to seize the opportunity which would lead to being a support in the growth of Indian economy.
The report conveys the message that banks internationally nowadays are moreover like fintech companies than ever using data science and artificial intelligence in the dealings with their customers.
The report also tries to quote that the Indian banks should use data analytics in times of corporate lending, which would help in avoiding many defaults as it an essential tool nowadays to improve easy accessibility as well as more satisfaction to customers with high-quality privacy and security to them to do transactions.
The credit growth of the banking sector has considerably weakened during the first half of 2019-20, which has further reduced to 5.9% by March 2020 and remained muted up to early June 2020 due to the disruptions caused by COVID-19 pandemic. Hence, to overcome the situation the banking sector should invest in data analytics.