Banks are investing heavily in AI, but many programs still struggle to show a measurable financial impact. The problem is not always technology. It is the value frame.
Most banking AI initiatives are still judged through a narrow productivity lens: hours saved, licenses deployed, headcount reduced. But in financial services, AI value often shows up elsewhere — fraud prevented, regulatory resilience strengthened, customer trust protected, revenue capacity unlocked, and data foundations built for long-term advantage.
Join Sabarish Muthumperumal, Head of Solutions, BFS Digital Engineering at Sutherland, for a webinar that challenges the way banks measure AI ROI. In this session, he introduces a practical six-lever framework designed to help banking leaders match AI use cases to the right value narrative, measurement model, and board-level KPI.
What you’ll learn
- Why productivity-only ROI fails to capture the real value of banking AI
- The four common failure modes behind stalled AI pilots: the Activity Trap, Productivity Mirage, Two-Speed Collision, and Single-Lever Trap
- How leading banks think about AI value across six levers: Run, Grow, Protect, Comply, Experience, and Future
- How to build a stronger AI portfolio narrative for CFOs, CROs, regulators, business leaders, and boards
- A practical four-step discipline to diagnose, select, sequence, and narrate AI investments
- How Sutherland’s AiRI diagnostic, supported by BFS Digital Engineering, can help banks identify the right value levers and prioritize AI initiatives
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