AI with empathy: insurers tackle extreme weather claim surges and fraud

AI plus empathy: the claims response insurers need now

Extreme weather is no longer a seasonal headline-it's an operational constant. Maurice Zicman, vice president of CX strategy at TP in Australia, says weather now sits at the center of claims demand. In the first half of 2025, the Insurance Council of Australia reported more than $1.8 billion in extreme-weather claims across 148,000 incidents, driven by events like Ex-Tropical Cyclone Alfred and flooding in North Queensland and the NSW Mid North Coast and Hunter.

The takeaway: surge is predictable. The question is how fast you can scale while staying fair, transparent, and human.

Surge pressure: scale fast, stay fair

Every major event pushes claim volumes up sharply. Policyholders are stressed, and they judge carriers on speed, clarity, and empathy. The operational challenge is expanding capacity without compromising decision quality or trust.

As Zicman puts it, the win is "technology that augments, not replaces, human empathy" during crises. That means clear communication, consistent triage, and process transparency at every touchpoint.

Where AI fits right now

Insurers are using AI to triage, prioritise urgent cases, and automate straightforward claims from FNOL through settlement. Predictive analytics help anticipate spikes using weather forecasts, so teams can stage resources ahead of impact. A recent Gallagher Bassett white paper notes that nearly 90% of Australian insurers now use AI in claims-a 38% lift year over year-signalling broad adoption.

The operating model is shifting to high-tech, high-touch: digital tools handle volume and consistency, while humans handle judgment, exception calls, and empathy.

Fraud spikes after disasters-don't lose trust while you fight it

Disaster periods attract inflated bills, staged losses, and false claims. The Insurance Fraud Bureau of Australia pegs annual fraud costs at up to $2.2 billion. AI-driven fraud detection, image checks, and behavioural analytics can surface risk early.

But over-triggering creates false positives that erode trust and slow genuine claims. Zicman's caution is clear: strike the balance. Many carriers partner with specialist CX providers for surge scale, quality controls, and stronger self-service without sacrificing empathy.

Resilience is built before landfall

Preparedness beats heroics. Invest in surge capacity, mutual-aid agreements, and partnerships with government, emergency services, and communities. Operational flexibility-redeploying staff, leveraging AI for volume management, and pre-positioning assessors in high-risk areas-shortens recovery time.

Treat this as a living playbook. Update after every event and feed lessons into your data, models, and comms templates.

Keep the human element front and center

Technology accelerates decisions; empathy earns loyalty. Clear status updates, proactive outreach to vulnerable customers, and fair explanations matter more during crisis. The goal is simple: high-tech for scale, high-touch for trust.

A practical playbook for the next event

• Forecast and plan: use weather intelligence to stage capacity and inventory. Align staffing, assessors, and suppliers to forecasted impact zones. Reference guidance from the Insurance Council of Australia and local warnings from the Bureau of Meteorology.
• Triage rules: define severity bands, vulnerability flags, and auto-approve thresholds for low-risk claims. Route complex or sensitive cases to senior handlers.
• Automation with guardrails: straight-through processing for simple claims; human review for high-value, high-ambiguity, or vulnerable-customer cases.
• Fraud controls: combine image analysis, behavioural signals, and supplier risk scores. Set human-in-the-loop checkpoints to prevent false positives.
• Surge staffing: cross-train staff, stand up on-demand pools, and keep vendor rosters pre-negotiated with clear SLAs.
• Customer comms: short, plain-language messages; status pages; SMS and email updates; clear "what's next" timelines.
• Data feedback loop: capture outcomes to refine triage thresholds, model features, and supplier performance.
• Governance: document model use, monitor bias and error rates, and run post-event audits with corrective actions.

Metrics that keep you honest

• Time to first contact, cycle time by segment, and backlog aging
• Straight-through rate vs. rework rate
• Fraud hit rate and false-positive rate
• Claims leakage and supplier variance
• CSAT/NPS for impacted customers and vulnerable-customer outcomes

Tech essentials to support the model

• AI triage that integrates policy data, location, and event severity
• Automation for low-complexity claims from lodgement to payment
• Image and behavioural analytics for early fraud signals
• Self-service portals and two-way SMS for updates and document capture
• Real-time dashboards for surge visibility and decisioning

Looking ahead

Zicman's message is direct: integrate climate data into operations, let automation clear routine work, and focus human expertise where it matters. Collaborate across the industry to strengthen fraud prevention without punishing genuine claimants. Build resilience frameworks that connect insurers, government, and communities so recovery is faster next time.

If your teams need to level up on AI skills for claims, operations, or CX, explore practical training options here: AI courses by job.