State Bank of India has achieved a significant milestone in AI adoption, underwriting nearly ₹1 trillion in MSME loans of up to ₹5 crore each during FY26. As reported by Business Standard, SBI Managing Director Rama Mohan Rao Amara announced at the FICCI-IBA conference that the bank successfully processed these loans within 12 months, covering both new-to-bank customers and existing customers. The bank combines GST network (GSTN), GST filings, account information, credit bureau scores, and other unstructured data to underwrite loans through its Business Rule Engine (BRE). The AI system has automated processing of cheques up to ₹10,000 through a straight-through processing (STP) system, with cheques of ₹10,000 value or less accounting for around 25% of SBI's cheque volumes. The AI model can read cheques and verify mandatory fields and compliance requirements with practically no human intervention, though SBI has retained a control mechanism where a dedicated control risk unit reviews samples to identify errors and determine whether models require further training.
SBI is now using AI-based early warning signals to identify vulnerable exposures before delinquencies emerge, by analysing sector-specific, market and other publicly available information. According to Business Standard, the bank's early warning systems ingest market and sector-specific information, along with other available information in the public domain, to identify potential risks. SBI is also using AI in fraud risk management and its security operations centre to process the large volume of logs generated by its IT infrastructure. At its resiliency operations centre, AI is being used to identify and predict possible breakdowns. The bank is also piloting an agentic AI-based digital assistant for corporate banking, embedded in YONO Business, which can pull data, collect and read documents including unstructured documents, and populate loan lifecycle management systems with risk analysis. Anjani Rathor, Group Head, Digital Banking & Customer Experience at HDFC Bank, highlighted the critical role of data quality in enabling effective AI adoption, emphasizing that banks must strengthen transaction monitoring systems to ensure that AI models are trained on accurate, relevant, and contextual data.
SBI has moved some of its generative AI experiments into full-fledged use cases, with significant improvements in customer service. As reported by Business Standard, at its customer care centre, an AI bot can now handle customer calls end-to-end, with only complex calls being transferred to human agents. The bank has seen reduced time and enhanced customer satisfaction. The deployment of AI has freed up relationship managers' time for other important tasks, as reported by The Hindu BusinessLine. The official noted that relationship managers earlier spent considerable time collecting data and carrying out preliminary analysis, which is now handled by the AI system. While quantifying the impact in terms of a defined reduction in the cost-to-income ratio would take time, the bank is already seeing benefits in terms of customer satisfaction and release of employee bandwidth. This efficiency gain allows relationship managers to focus on higher-value customer interactions and relationship building, supporting the bank's overall service quality and customer experience initiatives.
Senior executives from India's largest banks have identified Agentic AI integration as a medium-to-high strategic priority for the coming year, highlighting its potential to transform decision-making, security and innovation across the banking sector. Speaking at a session on the growing role of Agentic AI in autonomous decision execution during a Banking and Financial Services conference, leaders from Bank of India, Canara Bank, Bank of Baroda, HDFC Bank, and IndusInd Bank highlighted the importance of responsible AI adoption. The discussion reflected a broader industry consensus that while Agentic AI offers significant opportunities to improve operational efficiency and customer service, its adoption must be supported by strong governance, high-quality data, and effective risk management frameworks.
State Bank of India reported robust financial results for the June quarter, with consolidated net profit rising 13.73% year-on-year to ₹24,113 crore. According to The Economic Times, standalone net profit increased 10.23% to ₹21,121.22 crore, while core net interest income grew nearly 15% to ₹46,992 crore. The bank's gross advances grew 18.63%, though domestic net interest margin narrowed to 3%. Chairman CS Setty raised the bank's credit growth guidance to 14-15% for FY27, up from the earlier 13-15% range, while deposit growth stood at 9.73%. Setty indicated that 10-11% deposit growth would be sufficient to fund advances, with the credit-deposit ratio currently at 74% expected to rise to around 80%.
