ClaimsPilot - Autonomous End-to-End Claims & Repair Platform Qorus-NTT DATA Innovation in Insurance Awards 2026

The ClaimsPilot is an agentic AI platform for autonomous Claims & Repair in motor insurance, designed to transform how insurers and fleet operators manage the entire claims lifecycle.

Concept and objectives:

The concept is to replace rigid, rule-based workflows with goal-driven AI agents that dynamically orchestrate the entire claims lifecycle.

Instead of predefined process chains, the ClaimsPilot continuously evaluates each claim and determines the optimal next action across FNOL, validation, assessment, settlement, and payment.

The objective is to enable end-to-end automated claims handling, improving productivity, reducing loss ratios, and creating a scalable claims operation that can handle growing claim volumes without proportional increases in workforce.

Reasons behind:

Traditional claims processes rely on fragmented systems, manual coordination, and static rule engines. This leads to slow processing times, operational bottlenecks, and limited scalability.

Insurers are under increasing pressure to reduce operating costs, manage rising claim volumes, and deliver faster service to customers. A more autonomous, data-driven claims operation is required to address these challenges.

State of competition:

Most existing market solutions focus on individual automation components, such as FNOL intake, fraud detection, or repair estimation.

Traditional TPAs and service providers still rely heavily on manual processes and predefined workflows.

The ClaimsPilot differs by orchestrating the entire Claims & Repair lifecycle dynamically, enabling full end-to-end automation instead of isolated automation steps.

Sources of inspiration:

The development of the ClaimsPilot was driven by three factors:

• the operational challenges insurers face in scaling claims operations efficiently

• increasing customer expectations for faster and more transparent claims handling

• technological advances in agent-based AI architectures and large language models

These developments created the opportunity to rethink claims handling as an autonomous, AI-orchestrated process rather than a sequence of predefined workflows.

Departments involved:
AI engineering, claims operations, product management, compliance, IT architecture, and pilot insurance partners.

Pilot implementations demonstrate strong operational impact:

• over 20% productivity increase, with a target of up to 40%

• loss ratio improvement of up to 4 percentage points

• significant increase in straight-through processing rates

• fully automated handling of simple claims including payment initiation