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Insurance and warranty companies process hundreds of claims spanning both structured datasets and unstructured documents — repair invoices, warranty contracts, inspection reports, and damage photographs. Adjusters routinely wrestle with fragmented data asking questions like "Is the alternator covered?", "What's the claim balance?", "Any prior claims on this vehicle?"
Warranty and insurance companies receive a huge number of claims every day, but manual adjudication often delays approvals, raises operational expenses, and ultimately results in differences in financial decisions. To tackle such difficulties, Augmantis, sponsored by eComStreet, created an AI Claim Adjudicator that integrates deterministic business logic with cognitive AI to automate claim reviews while maintaining financial accuracy and regulatory compliance. The platform instantly approves eligible claims, flags high-risk cases for human review, validates repair costs, and maintains complete auditability."
The warranty and insurance companies often get FNOL submissions through long and cumbersome forms which annoy customers and result in missing, erroneous, and inconsistent data. Missing car details, faulty VIN numbers, invalid miles, and data entry are common issues which result in inefficiency in the claims process.
Warranty and insurance organizations process thousands of claims every day, each requiring different levels of expertise, financial approval, and fraud investigation. While routine claims can be handled autonomously, complex cases involving high repair costs, suspicious activity, customer disputes, or policy exceptions still require experienced human adjusters. Determining the right resource for every claim often becomes a manual process, leading to inconsistent routing, delayed approvals, operational bottlenecks, and increased costs.