(Bloomberg) --
Indian financial institutions must guard against relying on algorithms and artificial intelligence to assess customers for loans, central bank Governor Shaktikanta Das said.
Model based, algorithm lending can “lead to a potential crisis,” Das said in a speech at an annual banking event hosted by Mint newspaper in Mumbai on Thursday. Banks and non-bank financial companies “must appraise robustness of models used for lending,” he said.
The Reserve Bank of India has tightened restrictions on risky lending in recent months to improve financial stability. In November, it raised the capital cost of unsecured lending by banks, and followed that up by instructing lenders to offload investments in alternate investment funds, or bear hefty provisioning costs against those assets.
Das said that some banks and non-bank financial companies didn't have the bandwidth to manage surge in loans approved by algorithm.
“It was very clear to us that this kind of growth would not be sustainable going forward if it is not slightly moderated,” the governor said. “We clearly anticipated some problems ahead of us down the road. Therefore, we acted preemptively.”
While the nation's banking system remains robust and secured, the central bank will remain cautious against any sense of complacency, Das said Thursday.
Read More: India's Central Bank Governor Warns of Credit ‘Exuberance'
The RBI said last month the bad-debt ratio for Indian banks will likely ease to 3.1% of total loans by September from the current level of 3.2%.
FX Intervention
The governor also pushed back against the International Monetary Fund exchange rate regime reclassification. “Some people read it wrongly and call it a stabilized arrangement. But it is not justified, it is market determined.,” Das said.
The Washington-based lender last month in its Article IV consultation report said the RBI's intervention in the foreign-exchange market was excessive, implying that the country was trying to influence the level of the rupee.
The rupee weakened 0.6% last year, and traded in the narrowest range since 2002.
(Updates with additional details in the fifth paragraph.)
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