Design an AI system to process insurance claims with photos, forms and documents, with human adjusters in the loop.

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Ingest claim submissions (forms, photos, invoices, police reports, medical documents), classify and extract structured data (OCR + LLM/vision models), and assess with specialised components (damage detection from photos, policy coverage checks via rules + RAG over the policy wording, fraud signals from ML). Assemble a claim summary with a recommendation and evidence, then route by complexity and risk: straight-through for simple low-value claims within strict rules, adjuster review otherwise. Full audit trails, explainability and fairness monitoring are mandatory.

A claim submission is classified and extracted, then assessed by damage-detection vision, a rules-plus-RAG coverage check and fraud signals into a summary; routing sends simple low-value claims straight through and the rest to an adjuster, whose decision is logged for audit and model improvement.

Key points

Separation of judgement: deterministic rules decide eligibility where policy terms are clear; ML and LLMs assist with extraction, summarisation and anomaly detection; humans own complex or adverse decisions (denials).
Evidence-linked outputs: every claim in the summary links to a document page or photo region.
Consistency checks: dates across documents, invoice amounts vs damage severity, location vs police report. LLMs are good at spotting textual inconsistencies; flag them, don't decide.
Policy RAG: retrieve the specific clauses that apply; show them to the adjuster.
Regulation and fairness: explainable reasons for denials, no use of protected attributes, monitoring outcomes across groups, document retention rules.
Fraud and adversarial inputs: manipulated photos (detection models), injected text in documents.
Metrics: cycle time, straight-through rate, adjuster productivity, leakage (overpayment), accuracy against QA audits, customer satisfaction, complaint rates.

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Design an AI system to process insurance claims with photos, forms and documents, with human adjusters in the loop.

Key points

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