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Credit scoring: How AI and machine learning can help Posted on Oct 10 - 2017

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Disruption has finally come for the lending industry in India Fintech companies are beginning to use machine learning to evaluate the credit-worthiness of Indian SMEs and millennials.

The banking industry in India has traditionally funded corporate loans to those corporations who could navigate their labyrinthine processes. This paradigm, however, is beginning to get disrupted, thanks to the advent of consumer lending startups, armed with complex algorithms and machine learning software to replace antiquated credit rating systems.

RBI has identified 12 accounts with 25 percent (Rs 1.75 lakh crore) of bank NPAs for insolvency; now, corporates are selling their assets which never happened earlier; these are amongst the top 500 exposures in the banking system. The NPAs have been attributed to cyclicality of industry sectors and that entrepreneurs shouldn’t be hounded.

However, siphoning of funds and CBI investigations like the one being done for Vijay Mallya’s Kingfisher Airlines paves the way for banks to shift focus to retail lending. Banks having a big problem with NPAs on their balance sheet, and inability to find new players to lend to as their traditional model favours high-value secured loans to enterprises as they have easily accessible financial information and credit ratings, as well as substantial collateral. This has meant that their investment portfolios were dominated by large business houses and enterprises.

Banks have tended to look upon individuals and SMEs as lower-priority customers because of their lack of credit history and collateral. Without the information or the tools with which to evaluate the risk involved in lending to them, banks would offer individuals and SMEs credit cards and personal loans; however, the high risk involved makes it an unattractive section of the market for banks, and the high interest rates, inflexibility in payment options, and the reams of red tape make it an expensive and inaccessible option for potential customers. Only wealthier individuals and others with long and consistent credit histories and ratings could typically get personal loans, even for smaller amounts. View More

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