MoreYeahs built an AI Builder model and automated claims workflow on the Power Platform to modernize invoice review for an Australian insurer.
The client is an Australian insurance organization processing a high volume of claims and invoices, with a claims team managing complex, repetitive validations that consumed significant time and resources.
Facing growing backlogs and compliance risk from its entirely manual review process, the organization partnered with MoreYeahs to modernize claims operations with AI-powered invoice review and end-to-end workflow automation.
Manual invoice review was the primary bottleneck in the claims process, increasing turnaround times and the risk of human error in validations.
Slow, Error-Prone Reviews — Manual invoice review increased both turnaround times and the risk of human error in validations.
Repetitive Manual Effort — High operational effort was spent on predictable, rule-based claim validations that still required full manual intervention.
Inconsistent Compliance Checks — The team needed automation to improve the consistency of compliance checks across all claim types.
Limited Visibility — A lack of visibility into claim status and exception handling created further delays and reduced confidence in the process.
MoreYeahs developed an AI model on the Power Platform using AI Builder to perform automated invoice review and flag anomalies or compliance issues.
AI-Powered Invoice Review — An AI Builder model automatically reviewed invoices and flagged anomalies or compliance issues.
Automated Claim Orchestration — Claim workflow automation covered validations, approvals, and escalation pathways to reduce manual touchpoints.
Exception Handling — Non-standard or flagged claims were routed to the appropriate reviewers with full audit-ready context.
End-to-End Visibility — The claims team gained visibility into every stage of the claim and invoice lifecycle.
The program began with a detailed analysis of the existing claims workflow to identify which validation steps were rule-based and suitable for automation versus those requiring human judgment.
Workflow Analysis — Existing claims validation steps were assessed to separate automatable, rule-based checks from those requiring human judgment.
Model Training — AI Builder models were trained on historical invoice data to recognize key fields, compliance flags, and exception patterns.
Workflow Orchestration — Power Automate routed invoices through AI review before passing to human approvers only where necessary.
Structured Data & Audit Logging — Dataverse was configured to store all claim and invoice entities with full tracking and audit logging from day one.
The solution was built on the Microsoft Power Platform, combining Power Apps and Power Automate for the interface and workflow automation layer.
Manual review effort was significantly reduced, with the AI model handling a large proportion of routine invoice validations automatically.
Reduced Manual Effort — The AI model handled a large proportion of routine invoice validations automatically, freeing the claims team for higher-value work.
Consistent Validation — AI-driven checks applied compliance rules uniformly across all claims, producing traceable outcomes.
Improved Visibility — Dashboards and structured workflow data gave the claims team better visibility into status, bottlenecks, and exception volumes.
Stronger Compliance Traceability — Every decision and exception was fully logged and available for audit review.
The engagement gave the organization a scalable foundation for AI-assisted claims processing, with model performance monitored continuously as invoice patterns and compliance requirements evolve.
Faster, More Reliable Claims Processing — Reduced backlogs and consistent validation improved overall claims turnaround and reliability.
Audit-Ready Operations — Full logging of AI decisions and exceptions gives compliance teams confidence in every claim outcome.
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