SBI uses AI to underwrite nearly US$ 11.32 billion in MSME loans in FY26
- IBEF
- August 13, 2026
State Bank of India (SBI), the country’s largest lender, used artificial intelligence to underwrite nearly Rs. 1 lakh crore (US$ 11.32 billion) in MSME loans of up to Rs. 5 crore (US$ 0.57 million) each during FY26, covering both new-to-bank and existing customers. The development highlights the increasing use of AI in India’s banking sector to streamline credit assessment and improve operational efficiency. SBI Managing Director Mr. Rama Mohan Rao Amara said the bank was also deploying AI, including Large Language Models (LLMs), to automate the processing of cheques of up to Rs. 10,000 (US$ 113.16). Such cheques account for around 25% of SBI’s cheque volumes. The AI system can read cheques, verify mandatory fields and check compliance requirements, enabling straight-through processing with practically no human intervention.
SBI is deploying AI across multiple stages of the customer lifecycle, including credit underwriting, portfolio management, fraud risk management and customer service. The bank is also using AI-based early warning signals to identify vulnerable exposures before delinquencies emerge by analysing sector-specific, market and other publicly available information. The adoption of AI has helped free relationship managers from data collection and preliminary analysis, allowing them to focus on other customer-facing activities. While the bank is yet to quantify the impact in terms of a defined reduction in its cost-to-income ratio, it is already seeing benefits in customer satisfaction and employee productivity. SBI has also retained a control mechanism for AI-based cheque processing, with a dedicated control risk unit reviewing a sample of transactions to identify errors and determine whether the models require further training. The wider deployment of AI across banking functions reflects the sector’s increasing focus on technology-led lending, risk management and customer service.
Disclaimer: This information has been collected through secondary research and IBEF is not responsible for any errors in the same.
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