SBI Chairman CS Setty urged banks to use Artificial Intelligence for rural and small business lending at the FIBAC 2026 conference. This shift aims to improve credit access for underserved sectors, though it brings new challenges like cybersecurity risks.
State Bank of India (SBI) Chairman CS Setty has outlined a new strategic focus for the Indian banking sector, calling for the use of Artificial Intelligence (AI) to reach beyond traditional retail banking. Speaking at the FIBAC 2026 conference on August 11, 2026, Setty emphasized that AI technology should be more actively used to expand credit access for farmers and micro, small, and medium enterprises (MSMEs).
While banks have already adopted AI to improve customer service and speed up credit decisions for individual retail loans, Setty noted that the next stage of growth must target the rural economy. He stated that using AI to serve these sectors is a critical step for India’s goal of becoming a developed economy by 2047. The bank’s stock was trading at approximately ₹1,064 at the time of the announcement.
To make this possible, Setty highlighted the use of advanced tools like satellite imagery and digital records. These technologies could allow banks to better understand the credit needs of farmers and small business owners, even when they lack a traditional financial history. By using these data points, banks could make more accurate lending decisions, reducing the risk of bad loans while increasing the flow of money to these essential parts of the economy.
However, this rapid shift toward advanced technology comes with significant challenges. Setty warned that as banks adopt more AI, they must also strengthen their cybersecurity. He pointed out that new technology often opens doors to more sophisticated cyber threats and fraud, which could move faster than current security systems can handle. The risk is not just limited to technical breaches; the bank must also manage concerns regarding how AI models make decisions, ensuring they are transparent and responsible.
For investors, this shift indicates that banks will likely need to spend more on digital infrastructure and specialized talent to support these new AI systems. The ability to successfully scale these projects from pilot tests to actual, everyday lending will be a key factor to watch. Success will depend on the bank’s ability to use data efficiently while maintaining strong control over risks, ensuring that the push for technology does not compromise the safety of the financial system.