Fighting Fraud with Intelligence: Agentic AI in Insurance

Over the last few months, there’s been a lot of buzz about agentic AI. These terms can get confusing, but at its core, agentic AI simply means AI that can act autonomously. 

Instead of answering a question when prompted, it can recognize when it’s missing information, pull data from another system, and take action, all without a human needing to intervene.

This has huge potential to transform almost every industry. For example, Gartner predicts that by 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention, leading to a 30% reduction in operational costs.

But what about outside customer service, in functions that are more technical and critical, like fraud detection?

Fraud is one of the biggest challenges the insurance industry faces today. Billions are lost each year to increasingly sophisticated schemes. 

Traditional fraud detection methods (rule-based systems, manual checks) are often slow, limited, and easy for bad actors to outsmart. According to Forbes, AI has already improved accuracy in detecting fraud by over 50% compared to traditional methods. That’s impressive. But agentic AI could take it even further.

Instead of flagging potential issues for human review, an agentic AI system could independently investigate suspicious patterns across multiple systems, request additional data if needed, and even escalate or shut down accounts if the evidence is strong enough. 

In other words, it doesn't just raise a red flag; it conducts a full internal investigation before most people realize there’s a problem.

How Agentic AI Detects and Fights Fraud

Like with any sufficiently advanced AI, the exact way the system will work depends on how you design it and what guardrails you implement. 

Still, here’s a simple breakdown of how agentic AI could work in insurance fraud detection:

• Continuous Monitoring: It watches transactions, claims, customer behavior, and communication patterns in real time.
• Anomaly Detection: When something looks off (like a sudden spike in claims from a new area), the AI notices it immediately.
• Data Gathering: Instead of waiting for human input, it pulls relevant data from internal databases, external sources, and third-party systems to fill in gaps. For example, it might notice a claim tied to a new repair shop and automatically check business licensing databases to verify its legitimacy before approving the payout.
• Decision Making: Based on the patterns and evidence, it decides whether to flag, escalate, or auto-reject a claim.
• Action: If a high-risk activity is confirmed, it can launch investigations, freeze payouts, or alert a human fraud team.

Essentially, it’s a closed loop that can respond to threats in seconds, instead of days or weeks.

Keeping It Secure

Of course, giving AI the power to act autonomously comes with serious responsibility. You need tight safeguards if you're letting software make real decisions about people’s money and policies.

Key strategies include:

• Human-in-the-Loop for High-Risk Cases: Even with agentic AI, final decisions on major payouts or account terminations should have human oversight.
• Transparent Decision Pathways: The AI must leave an audit trail, showing exactly how it reached each decision.
• Continuous Learning but Controlled Updates: AI models should be regularly updated to adapt to new fraud tactics, but changes need strict testing and approval workflows.
• Robust Data Security: Agentic systems must comply with strict AI-driven security standards to protect sensitive insurance data.

The Bigger Picture

Insurance companies already know that AI can dramatically boost efficiency. We’ve seen it in underwriting, claims processing, and customer service. Agentic AI is simply the next step. It's faster, smarter, and capable of freeing humans from tedious monitoring so they can focus on strategy and high-touch service.

And it’s not just theory. Real-world use cases show how AI-powered efficiency is driving down costs and increasing fraud prevention rates. 

The challenge now is building systems that use agentic AI carefully, so companies can trust it without losing the critical human touch that insurance customers still expect when something important is on the line.

If you’re exploring how to apply AI (safely and practically) in your insurance operations, that's where we come in. 

At BP3, we specialize in consulting and enhancing business operations with AI. Our team knows how to build smart, secure systems that actually work in the real world, not just in theory. 

Talk to us if you're ready to see what agentic AI could do for your fraud prevention strategy. We'd love to help you get started.