A recent Boston Consulting Group report indicates that adopting 'agentic' AI could reduce Indian banking operational costs by up to 40% and open credit access to 400 million unserved customers. While this tech shift promises to boost stagnating productivity, investors should monitor the significant implementation risks, including data readiness, fraud prevention, and workforce reskilling.
The Indian banking sector, currently enjoying a healthy return on equity of 14.9%—well above the global average of 10.3%—is facing a hidden challenge. While profitability remains strong, productivity growth has stagnated at roughly 1% for over a decade. A recent report titled 'Winning in the AI Era: The New Playbook for Indian Banks,' presented at the FIBAC 2026 conference, suggests that the solution may lie in transitioning to 'agentic' AI systems. Unlike standard AI that simply answers queries, these systems can perform tasks autonomously, potentially slashing operational costs by 40% to 60%.
Expanding Credit to New Customers
Beyond just cutting costs, AI-native banking is expected to act as a growth engine by expanding the total addressable market. The report highlights the potential to bring 400 million previously unserved or under-served individuals into the formal credit system. By utilizing alternative data, such as GST filings and behavioral transaction history, banks can assess borrowers who lack traditional credit files. This allows lenders to reach small-ticket customers in remote areas while maintaining economic viability. AI-led underwriting and collections processes are projected to improve cross-selling opportunities by 10% to 20%, potentially unlocking new revenue streams for the industry.
Implementation Hurdles and Investor Risks
While the promise of efficiency is high, the path to implementation is complex. The report notes that although 90% of financial leaders have initiated AI strategies, only 10% have successfully embedded these initiatives across their entire organizational structure. For investors, this gap between strategy and execution represents a key risk.
The sector faces several material challenges that could pressure margins or disrupt operations if not managed carefully. Data readiness and infrastructure remain significant barriers to scaling. Furthermore, 60% of executives have identified fraud and operational risk as primary concerns. As banks invest heavily in these platforms, the cost of technology implementation may rise, and any failure in governance or cybersecurity could lead to regulatory scrutiny or financial loss. Success will ultimately depend on how effectively banks balance rapid innovation with long-term safety, talent reskilling, and maintaining the quality of credit portfolios as they enter these new, data-reliant customer segments.