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Study Shows Asset Size, CRAR Of Banks Influencing AI Adoption Rate: RBI

The Reserve Bank of India’s October Bulletin highlights that both asset size and financial health are critical factors driving the increased focus on artificial intelligence among banks.

<div class="paragraphs"><p>The Reserve Bank of India's analysis shows that while both private and public-sector banks are adopting artificial intelligence, private banks are leading the charge, driven by larger asset sizes and better capital ratios. The focus areas include automation, data analytics, and emerging technologies, presenting significant opportunities alongside potential ethical challenges. (Photo source: rawpixel.com/Freepik)</p></div>
The Reserve Bank of India's analysis shows that while both private and public-sector banks are adopting artificial intelligence, private banks are leading the charge, driven by larger asset sizes and better capital ratios. The focus areas include automation, data analytics, and emerging technologies, presenting significant opportunities alongside potential ethical challenges. (Photo source: rawpixel.com/Freepik)

Results of a study showed that the adoption of artificial intelligence is gaining momentum led by private sector banks, with asset size and capital to risk-weighted asset ratio influencing the rate of adoption, the Reserve Bank of India said in its October Bulletin on Monday.

"Among different banking indicators, size and financial health of a bank are found to positively influence the bank’s focus on AI, reflecting the impact of economies of scale and the availability of investment on the technological advancement," the RBI paper titled How Indian Banks are Adopting Artificial Intelligence? said.

According to a text mining of annual reports of Indian banks during 2015-16 to 2022-23, both private and public-sector banks are increasingly emphasising AI and related technologies, but the pace of increase is higher for private banks, RBI's bulletin for October said and does not necessarily reflect the views of the central bank.

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"Automation, data analytics, cloud computing, and big data are the major thrust areas, with increasing consideration for robotic process automation, the Internet of Things, and natural language processing-like technologies by banks, especially in recent years," it said.

While the integration of artificial intelligence into banking and finance offers immense opportunities, it also poses challenges such as the possibility of bias, lack of transparency, and issues around the ethical use of data, it said.

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