Aon launches AI claims platform, starting in Germany
Aon has introduced Aon Claims Copilot, an AI platform that blends the firm's Broker Copilot and risk analysis tools with its global claims advocacy services. The goal: consistent claims handling across markets, sharper benchmarking, and data-led decisions that speed up resolution and improve outcomes.
"Aon Claims Copilot represents a major step forward in Aon's commitment to deliver better information, advice, and solutions to clients through technology," said Joe Raiser, CEO of commercial risk at Aon. "It empowers our professionals to turn insight into action, helping clients achieve faster claims resolutions, maximize recoveries, and make better-informed risk decisions."
Rollout and coverage
The platform goes live in Germany in November 2025, with global deployment across 2026 and 2027. It will support 1,800 Aon claims professionals in more than 50 countries, spanning 20+ product lines.
Core features include analyzers and benchmarking tools for claims handling and portfolio performance, data-driven carrier performance evaluation focused on closure efficiency and outcomes, and a client portal for secure, real-time status tracking.
"Expert advocacy combined with AI-driven analytics gives our clients superior visibility and control over their claims," said Mona Barnes, global chief claims officer for commercial risk at Aon. "Aon Claims Copilot empowers our teams, simplifying our approach and maximizing claim payouts. It also creates a powerful feedback loop with our brokers, ensuring we place business with carriers that consistently deliver the best results."
What changes for carriers, brokers, and claims teams
- Consistent reporting and benchmarking across regions, improving apples-to-apples comparisons of claim performance.
- Portfolio-level views that surface outliers, bottlenecks, and reserve drift faster than manual reviews.
- Carrier scorecards built on closure speed, escalation rates, recoveries, and outcome quality.
- Stronger claim preparation: document analyzers, clearer audit trails, and standardized evidence packs.
- A tighter loop between claims results and placement decisions, shifting share to carriers that deliver.
- Better client transparency through a secure portal that tracks progress and next actions.
How it fits the market
Aon's move sits within a wider push to modernize claims with analytics, automation, and workflow integration. It follows earlier rollouts of Aon Broker Copilot and Risk Analyzers, pointing to a single toolset that connects placement, analytics, and claims operations end to end.
For reference, see Aon's corporate site for broader context on its risk and analytics platforms: Aon.
Who else is pushing on claims AI
- Marsh McLennan: Marsh Digital Labs, Marsh McLennan Advantage, and Blue[i] Claims automate intake, document processing, and predictive outcomes. Analytics support fraud detection, reserve accuracy, and real-time dashboards for clients.
- Willis Towers Watson (WTW): Radar and Radar Live apply machine learning to pricing, risk, and claims analytics. Claims Metrics benchmarks performance using AI, with leaders pointing to double-digit loss ratio gains where adoption sticks.
- Zurich: AI chatbots and automation for intake and service. Its Indicative Quote model cut home quote questions from 19 to 3 and improved quote-to-sale conversion.
- Allianz: Machine learning for triage, fraud, and settlement speed, plus a digital Claims Hub for tracking and analytics. In Australia, its Indicative Quote connects to partner systems for smoother policy completion.
- QBE: Digital Claims uses AI for lodgement, status updates, and document handling, targeting shorter cycle times and better customer satisfaction.
- Chubb: AI-assisted intake, fraud detection, and real-time analytics, with self-service claims tools that plug into broker workflows.
- Sedgwick: Darwin, a cloud claims platform, applies AI and robotics across registration, triage, and reporting, giving clients access to live files and self-serve reports.
Industry trends to watch
- Process automation: faster triage, less data entry, cleaner handoffs across FNOL, adjusting, and recovery.
- Client experience: real-time status, self-service portals, and clear next steps reduce friction and inbound queries.
- Risk and fraud analytics: earlier anomaly detection, better reserve accuracy, and portfolio forecasting.
- Compliance and transparency: dashboards, audit trails, and simplified reporting reduce regulatory lift.
- Broker and agent support: tools for comparison, communications, and workflow automation that mirror how teams actually work.
What to do next
- Audit claims data foundations: sources, quality, deduplication, and consistent taxonomies. AI is only as good as the inputs.
- Map your claims workflow and pinpoint the slowest steps. Target one or two use cases for a 90-day pilot (triage, document analysis, or recovery).
- Define outcome metrics upfront: closure time, leakage, reserve variance, subrogation recovery, and customer effort scores.
- Use claims results to inform placement. Reallocate share to carriers with better closure and lower dispute rates.
- Upskill teams on data literacy and prompt practices so adjusters and brokers can get reliable outputs, fast. Curated learning by job role can help: AI courses by job.
- Establish governance early: model oversight, documentation, human-in-the-loop checkpoints, and clear escalation paths.
Claims is now the fastest path to measurable value in insurance operations. Aon's rollout signals where the market is heading: integrated tools, cleaner feedback loops, and decisions anchored in data-market by market, team by team.
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