Top AI use cases in financial services

Banks and financial institutions are rapidly adopting AI and changing how they operate—they’re making decisions faster, personalizing service at scale, and cutting costs across the institution. These shifts aren’t inconsequential; they have the potential to be real game changers for the sector.

Why the sense of urgency? The data reveals:

Below are four priority AI use cases that are currently driving the biggest impacts in financial services: enhanced account holder experience, fraud detection, risk and compliance management, and operational efficiency. Click each tab to get a quick read on what each use case can do, a concrete example, and the business value.

Enhanced account holder experience


Deliver highly personalized, contextual interactions that make every account holder feel known and served faster.

Key ways it delivers:

  • Pull real-time account holder history, wallet share, and prior interactions into agent workflows.
  • Power chatbots and virtual assistants that deliver contextually relevant responses and personalized offers to account holders.
  • Use retrieval augmented generation (RAG) to combine institution data with models for tailored, privacy-aware recommendations. (Learn how to secure RAG with the right solutions.)

Example: A customer summary is delivered—within seconds—to a call center agent, including account holder credit usage, support history, and next-best action.

Value: Faster resolution, higher NPS, and increased cross-sell/upsell conversion

Learn more about enhancing account holder experiences with AI and its associated technology challenges in this new eBook.

Source: KPMG
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Top AI Use Cases in Financial Services | F5