August 19, 2026, (Inside AI) — The Reserve Bank of India’s Deputy Governor Shirish Chandra Murmu said on Wednesday that artificial intelligence is essential for banking, but human judgment remains indispensable for implementation and spotting loopholes.
Speaking at an event in Mumbai, Murmu outlined a framework where AI assists but does not replace governance. He warned that models performing well overall can still fail vulnerable groups, making human oversight critical.
“A model that performs well overall can still fail a small but already vulnerable group. Intelligence, therefore, demands clarity — about what a technology delivers, what it leaves out, and whether its output fits the decision at hand,” Murmu said, Deputy Governor, Reserve Bank of India
Murmu stressed that intelligence in banking must extend beyond AI. He listed analytical intelligence, human intelligence, governance intelligence, and collective intelligence as necessary components.
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Credit access and the danger of data gaps
Murmu said banks should use AI to reach and understand new borrowers. He cautioned against treating missing borrower information as negative information.
“Where a lender genuinely lacks reliable information about a borrower, the absence of information should not, by itself, be mistaken for adverse information,” Murmu said, Deputy Governor, Reserve Bank of India
“Treating ‘we don’t know’ as though it meant ‘we know it’s bad’ leads to credit being denied where it need not be. This is precisely where banks must put their technological capabilities to work,” he added.
The deputy governor’s remarks come as Indian regulators push for financial inclusion while managing emerging risks. The RBI has previously cautioned that algorithmic lending models can embed bias if trained on incomplete data.
Collective risk demands collective intelligence
Murmu warned that uniform adoption of technology across banks creates efficiency but also raises systemic fraud risk. Digital fraud can move through multiple accounts and institutions quickly.
“When risk becomes collective, the intelligence marshalled against it must become collective too. MuleHunter.ai and the Digital Payments Intelligence Platform are the Reserve Bank’s answer to exactly this challenge — drawing together dispersed signals, with the help of AI, so that detection comes earlier and the response is better coordinated,” Murmu said, Deputy Governor, Reserve Bank of India
He said AI’s pattern recognition should identify emerging weaknesses in fraud, conduct, operations, and cyber risk before they become disruptions.
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Murmu also redefined productivity for AI in banking. He said it is not just output per employee or cost-to-income ratio.
“Productivity in banking is not merely output per employee or the cost-to-income ratio; it is whether the same institution, with the same resources, reaches a borrower it could not reach before, resolves a grievance that would earlier have remained pending, prices risk more accurately,” Murmu said, Deputy Governor, Reserve Bank of India
“If AI compresses costs without widening reach or improving the customer’s experience, we shall have automated the existing system rather than improved it,” he added.
Murmu’s comments align with a broader regulatory shift in India. The RBI has been pushing banks to adopt AI for fraud detection and credit scoring, but with guardrails around explainability and fairness. Earlier this year, the central bank released draft guidelines on responsible AI use in financial services, requiring model risk management frameworks.
Industry analysts note that Indian banks are investing heavily in AI, but talent gaps and legacy systems slow deployment. The deputy governor’s emphasis on human judgment signals that the RBI will not accept fully automated decision-making in high-stakes lending or fraud response.
