Use case 02 · Risk

Insurance claims and fraud triage

Organize claim evidence, detect suspicious patterns, and prepare explainable investigator briefs without delegating claim decisions.

Executive ownerChief Claims Officer
Business valueShorter investigations with accountable decisions
Real-world evidence

Shift Technology

Published by Microsoft

Shift Technology helps hundreds of insurers fight claims fraud using Azure OpenAI Service

The case describes artificial intelligence used to sort and classify policy, claim, and supporting documents for faster fraud investigation.

  • The company reports reducing weeks of sorting, classification, and decision support to days.
  • The platform supports insurers across the policy life cycle.
Read the original source Results are reported by the named organization or publisher. They are evidence of feasibility, not a forecast or guarantee for another business.

The business problem

Orchestration redesigns the whole operating loop.

Claims teams must connect policies, forms, images, correspondence, prior activity, external signals, and fraud indicators under time pressure. The burden is not one prediction; it is the disciplined assembly of evidence.

AI orchestration can classify the incoming material, surface inconsistencies, build a chronology, and recommend the next investigative step. The claim decision and any adverse action remain with authorized professionals.

Infographic 01

Orchestration corridor

How the work moves from signal to accountable outcome.

Every step has a defined input, intelligence task, action, and handoff. This is what separates an operating system from an isolated prompt.

Infographic 02

Ecosystem command map

The capability lives between systems, not inside one model.

The four quadrants show the assets that must be coordinated. Select any quadrant to emphasize its role in the operating system.

Infographic 03

Value and control instrument panel

Measure the business result and the integrity of the route.

The bars are not performance claims. They show the measurement sequence: establish the current baseline, agree a pilot threshold, and verify the observed result.

90-day implementation route

Move from reconnaissance to controlled scale.

Select a phase to inspect its executive decision gate.

Phase 1

Recon

Study one claim type, evidence map, fraud typology, and current investigator queue.

Executive owner
Chief Claims Officer
Decision gate
Problem and baseline confirmed

Source and governance discipline

Evidence first. Claims qualified. Accountability designed in.

This operating play is an independent synthesis by Dr. Alejandro Canonero, DBA. It translates a documented implementation into a vendor-neutral business design and applies the War of the Ecosystems perspective. It does not imply endorsement by the source organization.

Deployment evidenceShift Technology helps hundreds of insurers fight claims fraud using Azure OpenAI Service NIST AI Risk Management FrameworkA voluntary framework for governing, mapping, measuring, and managing artificial intelligence risk.ISO/IEC 42001 artificial intelligence management systemsAn international management-system standard for responsible development and use of artificial intelligence.

Adjacent operating plays

Compare how orchestration changes across the ecosystem.

03 · Finance Accounts payable invoice processing

Extract invoice data, match purchase evidence, route exceptions, and prepare an auditable payment queue.

 09 · Operations Procurement and supplier diligence

Coordinate requirements, market intelligence, supplier evidence, evaluation, and compliant contracting.

 15 · Technology Cybersecurity incident triage

Correlate alerts, enrich threat context, prepare incident timelines, and guide analysts through response playbooks.

Executive working session

Apply this pattern to your risk workflow.

A focused diagnosis will map the current work, quantify the opportunity, define human command, and shape the first controlled pilot.

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