Improve claims service: give people a clearer file sooner

A practical AI workflow paper for Melbourne insurance operations.

Executive takeaway

If your team is already experimenting with AI, the next question may be which uses deserve confidence and further investment. We help make that decision clearer. You can start with what your people are trying and what concerns you; we can identify a suitable workflow together.

A claims colleague can receive a file containing the relevant information and still spend time reconstructing what happened: which document arrived when, what was already requested and which question remains unresolved. That preparation can crowd out the attention a customer needs.

AI may help organise an authorised file into a source-linked chronology and draft a factual status summary. The intended outcome is a clearer handover and less repeated administration. Coverage, settlement, underwriting and adverse decisions remain with authorised people. Preparation can influence judgement, so human checking must be substantive rather than a final click.

Our team helps design and implement bounded workflow changes, then test whether they improve the whole job. Start with staff support and evidence, not an unattended decision system. This paper offers a planning method; it reports no insurer results or guaranteed savings.

Find friction in the handover

Investigate a specific handover. Does a handler reopen correspondence to establish what was received? Does the next colleague ask a customer for information already supplied? Are supplier updates copied between systems? Does a manager have to rebuild the record before understanding why a file is waiting?

These are possible questions for discovery, not findings about all insurers or Melbourne teams. Follow the work with handlers, service staff and the people responsible for quality and conduct. Separate missing information from information that exists but is hard to find. Look for unclear ownership or inconsistent naming before deciding a model is needed.

Choose a narrow preparation task with an authorised reviewer. An easier handover should support customer service without classifying people as risky, inferring dishonesty or creating reasons to refuse a claim. A better document index or simpler status process may be sufficient.

A fictional running example

Fictional example, not a client case study: A Melbourne-based insurance operations team prepares an internal handover for a property claim. The file includes incoming documents, prior requests and supplier status updates. A handler checks a draft chronology against the original records and confirms the next administrative step.

The proposed tool lists received documents, source-linked dates and unresolved factual questions. It does not interpret coverage, infer fraud, recommend refusal, assess vulnerability, choose a settlement amount or contact the customer. It has no authority to change the claims record or trigger a payment. Questions that could affect a financial decision go to the authorised handler.

Testing begins with synthetic files. Real information requires the organisation's approved environment, access and use decisions. The example has no measured outcome and supplies no evidence of compliance.

What would make this worth continuing?

The following is a decision aid for the fictional trial, not an observed result. Agree the limits with the people responsible before testing.

• Accepted result: A handler-accepted factual chronology and handover with dates tied to original records.
• Who judges it: The receiving handler and the operational quality owner.
• Hold and return to the manual route when: A receipt is invented, a contradiction disappears or the draft makes an adverse or financial recommendation.
• Evidence for another step: Compare total preparer and receiving-handler effort for files of similar complexity; include repeated requests and missing facts.

A fictional chronology might show “Supplier email: proposed inspection Friday” beside “Handler note: inspection date not confirmed.” Keep both dated references and flag the conflict. The assistant must not silently turn the proposal into a confirmed booking.

Use the one-workflow worksheet to record the agreed question, evidence and next decision.

Five stages with proof before expansion

Understand. Enter with one handover task, its outcome owner and the people receiving the file. Map receipt, indexing, preparation, checking and next-step ownership. The benefit hypothesis is less reconstruction and fewer repeated information requests. Exit with a baseline, authoritative source hierarchy, permission boundaries and a clear definition of an acceptable handover. If staff disagree about what a source means, resolve it through the existing process rather than asking AI to decide.

Try. Enter after scope, reviewers, permitted data and stop conditions are agreed. Use synthetic files with duplicate documents, conflicting dates and a supplier update that contradicts an earlier note. The hypothesis is quicker factual preparation without losing uncertainty. Exit with reviewed observations, correction effort and the owner's decision. Stop if the draft invents a receipt, suppresses a contradiction or recommends an adverse decision. Restore the manual handover.

Repeat. Enter when the trial provides a reason to continue. Standardise references, event labels and how gaps are recorded. Have a second colleague follow the process and compare each draft with its sources. The hypothesis is more consistent handovers between people. Exit with reproducible instructions, exception records, a manual fallback and comparison against the baseline. Include awkward files; excluding them can conceal the burden the process creates.

Operate. Enter only after bounded routine use is approved. Name the owner and backup, control record access and make failed preparation visible. A handler must know when a chronology is incomplete and how to reconstruct it. The hypothesis is steadier service and fewer internal chases. Exit with operating guidance, change controls, visible exceptions, exercised recovery and an owner review. Pause when permissions, source reliability or the ability to recover changes.

Improve. Enter with enough observations to evaluate usefulness. Compare total handling effort, handover quality and customer-facing consequences. The hypothesis is keeping helpful preparation while preventing inappropriate expansion. Exit each review with a recorded retain, revise, reduce or retire decision and next trigger. If a structured event log proves better than generated prose, reduce AI use. New financial or customer actions require a separately authorised design and evidence decision.

This Understand → Try → Repeat → Operate → Improve framework is Alongside People's original per-workflow discussion aid. It is not an official insurance standard, certification or validated readiness test. Greater autonomy is not a requirement for progress.

Respect the regulatory and authority boundaries

ASIC's claims-handling information sheet, INFO 253 explains the AFS licensing regime and obligations for claims handling and settling services involving insurance products regulated by ASIC. The relevant licensee and authorised specialists must determine how a proposed workflow fits those obligations.

For APRA-regulated entities within its scope, the current CPS 230 Operational Risk Management, whose current revision commenced on 1 July 2026, addresses operational risk, critical-operation continuity and service-provider risk. Do not assume every intermediary is an APRA-regulated entity or that a supplier arrangement has a particular classification without review.

OAIC's commercial AI privacy guidance addresses personal-information risks and product due diligence. Insurance files may require careful handling; determine actual obligations and approved controls with the organisation's specialists. This paper gives no legal assurance, licence coverage or compliance sign-off.

A proposed 30-day pilot

This schedule is a planning example, not our service promise. Begin after the sponsor has approved the people, scope and environment. A calendar target does not bypass information, conduct or procurement review.

Days 1–7: Follow existing handovers and record preparation, review and rework. Agree a synthetic example set, source hierarchy and acceptance criteria. Explicitly exclude coverage, fraud, underwriting, settlement and other adverse recommendations.

Days 8–14: Build a draft chronology and factual status summary. Handlers check each event against its source. Test contradictions, absent documents and poor document quality. Record whether checking effort offsets any preparation benefit.

Days 15–23: Repeat in shadow mode with authorised examples. Existing records remain authoritative. Test a second handler's use, an unavailable tool and recovery through the manual route. Nothing is sent externally or used to automate a financial decision.

Days 24–30: Review outcomes and exceptions with the operational owner and appropriate risk/conduct stakeholders. Deliver the evidence, limitations and operating proposal. Choose further testing, a separately approved next step, revision or stopping. Routine-use readiness is an explicit decision.

Measure service, not just generated output

The primary outcome could be staff effort to prepare an accepted handover. Count indexing, drafting, source checking, correction and the receiving handler's reconstruction. Record elapsed handover turnaround separately. Pair these with repeated information requests, unresolved discrepancies and usefulness to the next colleague.

Guardrails include incorrect dates, missing contradictions, unsupported assertions, unauthorised access and adverse recommendations. Review whether the process adds work for customers or suppliers. Any escalation related to customer needs stays with the existing authorised process; the pilot does not classify vulnerability or treat a model's inference as fact.

Keep criteria fixed, compare similar file complexity and document sample limits. A shorter internal task does not automatically establish faster settlement or better customer outcomes. Verify amounts through established records and controls; fluent text is not financial validation.

Before implementation, record supplier data access, retention, processing locations, subcontractors and exit arrangements. Limit access to necessary information and preserve authoritative records. Test what happens when the tool is unavailable, so a preparation aid does not become a hidden dependency that obstructs service.

How our team helps

Alongside People provides practical AI advice and hands-on implementation. Paul Volpato, our founder and CEO, connects the purpose of the work with the people, systems and checks it needs. Our team can map the handover, design the pilot, implement an agreed preparation workflow and develop operating instructions, review checks and handover material.

Your authorised professionals retain financial and customer decisions. We agree scope, responsibilities and support arrangements rather than imply insurance credentials or indefinite operation. Bring a recurring handover, the person receiving it and a clear service problem. We can help make the next change concrete enough to assess.

Official references

Accessed 3 October 2026. Recheck before consequential application.

• ASIC INFO 253: regulator information sheet, scoped to ASIC-regulated insurance claims handling.
• APRA CPS 230, current revision commenced 1 July 2026: prudential standard for its defined APRA-regulated entities; supersedes the previous version.
• OAIC commercial AI privacy guidance: privacy guidance; does not cover every applicable regime.

If you are already trying AI and are unsure what deserves further investment, tell us what you have tried and what you want to improve. We can help find the starting point together.