Agentic AI for Banking: Key Use Cases and Implementations
Summary
Banks are entering an era of agentic AI, deploying autonomous agents across AML, credit, operations, and client experience. When grounded in modern data infrastructure, these agents reduce cost, improve compliance, and enable scalable growth — transforming banks into more resilient, efficient, and trusted institutions.
Ted O’Connor
Ted is a Senior Vice President focused on Business Development at Arcesium. In this role, Ted works with leading financial institutions in the capital markets to optimize data, technology, and operational needs.
Sources:
[i] Yahoo Finance, January 5, 2025. https://finance.yahoo.com/quote/%5EBKX/
[ii] Fenergo, July 24, 2025. https://resources.fenergo.com/newsroom/fenergo-survey-over-25-of-financial-services-firms-forecast-4m-in-annual-compliance-operations-savings-through-agentic-ai
[iii] DOT, December 2024. https://home.treasury.gov/system/files/136/Artificial-Intelligence-in-Financial-Services.pdf
[iv] FinCEN, 2025. https://www.fincen.gov/system/files/shared/FinCEN-Infographic-Public-2025-508.pdf
[v] McKinsey, December 11, 2025. https://www.mckinsey.com/industries/financial-services/our-insights/cib-in-an-era-of-volatility-ai-and-nonbank-challengers
[vi] IBCA, December 6, 2024. https://www.investmentbankingcouncil.org/blog/how-investment-banks-are-adapting-to-client-centric-trends
