Actuarial Document Analysis
The loss runs, treaties, and valuation reports actuaries mine by hand — read by models instead.
Actuarial document analysis is the application of document AI to the paperwork that feeds actuarial work: loss runs and claims bordereaux, exposure schedules, reinsurance treaties and endorsements, valuation reports, policy wordings, and regulatory filings. Actuaries price risk and set reserves from data — but a surprising share of that data arrives as PDFs and spreadsheets in inconsistent formats from brokers, cedents, and third-party administrators, and analysts traditionally re-key or hand-wrangle it before any modeling can begin.
The core tasks are table-heavy: extracting multi-page loss run tables with carrier-specific column conventions, normalizing claim status codes and development periods across sources, pulling limits, attachments, and exclusions from treaty language, and reconciling exposure schedules against policy records. This is document AI at its most demanding — nested and merged tables, footnotes that change the meaning of columns, and terminology that varies by market. Layout-aware extraction and schema-based normalization turn these into consistent datasets; language models increasingly handle the interpretive parts, like reading a sanctions exclusion clause or flagging non-standard treaty terms.
The value shows up as speed and completeness in pricing and reserving cycles. A submission's loss history can be structured within minutes of arrival instead of days, letting actuaries and underwriters spend their time on judgment — trend selection, credibility, terms — rather than transcription. Because these numbers flow into reserves and regulatory returns, traceability is essential: every extracted figure should link back to its source page, and low-confidence values should be reviewed before they enter a model that a signing actuary must stand behind.
Risk assessment at the speed documents can be read — automating the reading, not the judgment.
The insurance policy as it was actually issued — schedule, wording, and endorsements, structured together.
Balance sheet, P&L, cash flow — parsed from PDF into numbers that reconcile, with the footnotes attached.
Proof Perimeter runs document AI inside your own perimeter — with a provenance record on every field.
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