[Webinar] Learn how Assurant is scaling AI in the contact center
Watch on-demand

Stay up to date

Sign up for the latest news & content.

Published on
July 8, 2025

How financial services are using AI agents: 6 use cases that drive value

Theresa Liao
Director of Content and Design
4 minutes

Customer service teams in financial services cover a broad spectrum of support, from simple transaction help to situations that are sensitive and call for extra care. Regardless of the situation, customers want the interaction to be fast and the issue resolved.

Basic contact center automation no longer suffices. Instead, today’s most advanced generative AI agents go beyond to handle complex questions, integrate with internal systems, and work collaboratively with human teams to provide better service without long wait times. The wide range of use cases and the scalability of AI agents make them a great fit to support contact centers in financial services.

Below are six impactful use cases for AI agents that financial services companies can deploy to improve customer service, reduce costs, and scale operations more effectively.

1. Help customers regain access when accounts are locked or compromised

Few things trigger more customer anxiety than being locked out of an account, especially during moments that matter. Whether it’s caused by suspicious activity, forgotten credentials, or fraud protection, customers want quick reassurance and fast access.

With enterprise-level data protection and access to the right systems, AI agents can help customers verify their identity, unlock their account, and restore access quickly and independently without compromising sensitive data.

2. Report and resolve fraud faster

When customers see a suspicious charge, they want to find out immediately what leads to the charge and stop any further transactions. Any delay can lead to frustration and chip away at their trust.

AI agents can immediately help customers report fraud, freeze a card, or file a dispute without long hold times or multiple handoffs. With the right (and secure) access to transaction history, they can review recent activity, flag unusual behavior, and take steps to resolve issues independently.

3. Automate funds transfers and recurring payments

Transferring money is one of the most common things customers need, but it’s not always straightforward for customers.

AI agents with secure access to transaction systems can help customers move money between accounts, set up recurring payments, or resolve transfer issues on their own. And when things get more complex, AI agents with strong human-AI collaboration features can either loop in a human advisor with full context or get approval behind the scenes without disrupting the customer’s experience.

4. Resolve fee disputes with transparency and accuracy

When a customer sees a charge they don’t recognize—like a foreign transaction fee or a monthly maintenance fee—they want a clear, straightforward explanation. In some cases, they may also be eligible for a fee reversal.

An advanced AI agent can walk the customer through the reason for the charge based on company policy, review their account history, and sort through the details. If a decision requires human judgment, like approving a fee reversal, the AI agent can bring in a human in the loop without interrupting the conversation. The result is a faster, smoother experience even in situations that require a closer look.

5. Provide investment account support and policy clarification

When it comes to personal investments, customers can have questions about fund performance, risk levels, or product policies. They would want to understand how an investment works, what fees they will pay, or how to adjust their contribution.

AI agents can provide this support around the clock, offering clear, up-to-date answers based on current policies and real-time account data. When a question requires a specialist’s expertise or approval, the AI can involve them according to the financial organization’s policies to ensure they provide customers the right support at the right time.

6. Streamline policy changes and account updates

Updating contact details, adding authorized users, or modifying account settings often involves multiple steps across different systems or teams. Because AI agents can be integrated with various internal systems, it makes them ideal for handling these issues quickly and securely. Customers can get guided, personalized support without being passed around or going through repeated verification.

What to look for in an AI agent for financial services

There is a lot of marketing hype about AI agents, but not all generative AI solutions are created the same. If you’re exploring AI agents for your organization, here are some things you should look for that go beyond the general capabilities of an AI agent:

  • Strong safety and compliance foundations: Choose solutions with built-in safety and security layers like input evaluators, output guardrails, and redaction tools to meet enterprise security and compliance standards.
  • Human-in-the-loop collaboration: Escalation isn’t just a handoff. The best AI agents work alongside humans to get judgment calls or approvals and can then continue the interaction themselves. When needed, they hand off conversations with full context so human agents can pick up quickly.
  • Secure integration with legacy systems: Many financial institutions have complex or legacy infrastructure. Select an AI agent that fits into your existing technology ecosystem, works with your APIs, and does not require costly infrastructure rework.
  • Proven deployment in regulated environments: Risk teams want assurance. Look for vendors with strong security practices and governance frameworks built for regulated industries.
  • Ability to test safely before rollout: Make sure the AI solution offers a controlled environment to test and train AI agents without affecting live systems or customers.
  • Robust monitoring and quality assurance: Choose tools that allow your team to understand how AI agents behave, continuously monitor AI performance, review interactions, and maintain high-quality service.

It’s AI agents’ moment in financial services

Generative AI isn’t just full of potential anymore. It’s ready. Leading financial institutions are already starting to incorporate AI agents across key parts of the customer journey to improve customer satisfaction and make operations more efficient.

But not all solutions are created equal. As you evaluate your options, focus on what matters most: safe automation, smooth collaboration with human teams, easy integration with your existing systems, and strong support for regulatory requirements.

The right AI agent won’t just help you cut costs. It will help you deliver better service, respond more quickly, and scale with confidence. In a space where trust is everything, that’s an advantage worth moving on.

Stay up to date

Sign up for the latest news & content.

Loved this blog post?

About the author

Theresa Liao
Director of Content and Design

Theresa Liao leads initiatives to shape content and design at ASAPP. With over 15 years of experience managing digital marketing and design projects, she works closely with cross-functional teams to create content that helps enterprise clients transform their customer experience using generative AI. Theresa is committed to bridging the gap between complex knowledge and accessible digital information, drawing on her experience collaborating with researchers to make technical concepts clear and actionable.