ClaimsPilot: Agentic AI in Claims Management
Why End-to-End Automation Is Becoming Reality Now
Claims handling is one of the most complex and cost-intensive core processes in the insurance industry. High claim volumes, rising loss costs, increasing regulatory pressure, and ever-higher customer expectations collide with limited staffing resources. Traditional automation has been hitting clear limits for years.
Agentic AI now introduces a new approach that fundamentally changes the claims process. It moves away from rigid rule sets and predefined process paths toward a system that understands objectives, prepares decisions, and autonomously controls processes. End to end.
From Process Logic to Goal-Oriented Control
Traditional automation solutions follow a simple principle. Every process step is modeled in advance, including all variants and exceptions. In practice, this leads to high complexity, limited flexibility, and significant maintenance effort.
Agentic AI reverses this principle. Instead of prescribing every step, the company defines clear operational objectives, regulatory guardrails, and available tools. AI agents independently plan and control the path to those goals. Depending on claim type, context, and data availability, workflows can vary without losing governance, compliance, or transparency.
The result is a dynamic claims process that adapts to each individual case instead of forcing cases into a rigid framework.
What Sets Agentic AI Apart from Traditional AI
Traditional AI and machine learning are primarily analytical. They classify data, identify patterns, and support decisions at specific points. Generative AI expands this by creating content such as text, speech, or images.
Agentic AI goes one step further. It combines analysis, generation, and the ability to act. AI agents independently pursue defined goals, access internal and external systems, evaluate intermediate results, and trigger concrete actions. Examples include repair shop coordination, payment approvals, or targeted requests for additional information.
Human involvement is ensured wherever regulatory or quality requirements demand it. Decisions are transparent, documented, and auditable.
End-to-End Claims Handling with the ClaimsPilot
The ClaimsPilot is designed exactly for this purpose. As an Agentic AI platform, it orchestrates the entire claims lifecycle from first notice of loss to case closure.
A central orchestrator agent translates corporate objectives into operational tasks. Domain agents then make expert decisions, for example on coverage, liability, reserves, or fraud indicators. Action agents execute these decisions through payment instructions, repair assignments, or customer communication.
An integrated learning layer ensures continuous improvement. Feedback from real claims flows directly into process optimization.
Automation by Levels of Complexity
Implementation follows the established levels of claims complexity.
Simple claims such as glass damage, parking damage, or minor comprehensive claims are handled fully automatically. The focus is on fast settlement, automatic repair booking, and immediate payment initiation.
For medium-complexity claims, Agentic AI manages orchestration, for example standard collisions without bodily injury. Final approval is provided by experienced claims handlers.
Highly complex claims such as multi-party accidents, bodily injury cases, or international claims initially remain outside full automation. Even here, the system supports structured preparation, data collection, and decision support.
Measurable Value for Insurers
The benefits are clearly quantifiable:
- Productivity gains of 20 to 40 percent
- Improvement in loss ratio of up to 4 percent
- Significantly higher customer satisfaction through faster decisions
- Reduced workload for service centers and claims departments
- High scalability, even during peak claim events
At the same time, the system remains robust against regulatory requirements and emerging risks.
Risk, Compliance, and Governance
Explainability and control are core design principles. Critical decisions are secured through approval levels. Human-in-the-loop is implemented wherever regulatory sensitivity applies.
Company policies, BaFin requirements, and compliance standards are embedded as fixed guardrails within the system. Audit trails fully document every decision and action.
The ClaimsPilot meets the requirements of the EU AI Act, BSI guidelines, and relevant ISO standards, while remaining flexible enough to adapt to future regulatory developments.
Conclusion: The Operating System for the Claims World
Agentic AI marks the shift from process-driven automation to goal-oriented claims control. Insurers define what needs to be achieved. The system determines the optimal path.
The ClaimsPilot combines speed, efficiency, and customer focus in an integrated end-to-end solution. Those who act now gain not only efficiency, but a structural advantage in a market increasingly shaped by adaptive systems.
The traditional claims process is not further optimized. It is reimagined.
More details can be found in the February 2026 issue of Versicherungswirtschaft in the article “Agentic AI in Claims Management” by Andreas Decker and Roy Heiderich.
