Brisc reads claims laundry lists, thousands of rows in any cedent layout, and tells you which claims deserve attention. It scores each claim against your own hazard vocabulary and problem jurisdictions, and shows exactly why every flag fired.
| Clm No | DOL | Description | Sts | Incurred |
|---|---|---|---|---|
| 24-0117 | 03/11/21 | Slip on wet floor, wrist fracture | C | 12,400 |
| Page 14 subtotal | 1,284,300 | |||
| 24-0391 | 2.6.19 | Reopened. term A alleged, suit filed | R | 480,000 |
| 24-0402 | 14-Feb-20 | Rear-end collision, soft tissue | O | 8,250 |
| 24-1102 | Feb-22 | Clmt reports term B, misspelt in source | O | 95,000 |
| 24-1150 | 2022/07/19 | Water ingress, contents | 3,900 | |
| Your term | Hits | Open | Closed | Reop. | NA |
|---|---|---|---|---|---|
| Term A | 23 | 9 | 12 | 2 | 0 |
| Term B | 18 | 7 | 10 | 1 | 0 |
| Term C | 11 | 4 | 6 | 1 | 0 |
| Term D | 9 | 2 | 5 | 0 | 2 |
| Term E | 0 | 0 | 0 | 0 | 0 |
| Term F kept at zero | 0 | 0 | 0 | 0 | 0 |
4,180 rows screened, 61 flagged with the reason each one fired. The roll-up is ready to paste into the claim file, with the detail one click down.
The Analyst tracks each insured’s total incurred loss against their layer attachment point and bands it below, approaching, or reached.
The Analyst resolves which insured a file belongs to, sums values across files with per-claim dedupe, and routes genuinely ambiguous cases to review rather than forcing them into a band.
Every cedent lays the document out differently. The Analyst works out what it’s looking at before it counts anything, so nothing fake enters the queue.
Claim register, event log, or placement matrix, identified first, so policy wording never becomes a fake claim.
Finds claim number, loss date, claimant, narrative and venue whatever the columns are called.
Totals, preambles and repeated headers are recognised as report artifacts and never counted as claims.
Twelve date formats to ISO, occurrence ranges detected, merged-cell contamination flagged, the original always kept verbatim.
Three-tier keyword matching, exact, synonym and fuzzy, runs against your hazard list behind a two-threshold gate: confident hits auto-accept, borderline hits queue for review, weak ones are ignored.
Plaintiff-friendly venues from your own jurisdiction list. A specific court always counts; a bare state only counts in a venue column.
Keyword severity, confidence, and jurisdiction weights combine into a per-claim score, banded critical to none.
Rows scanned, flags by band, keyword hits by category, jurisdiction hits, pending exceptions. Every row stamped.
Misspelling of a term on your hazard list. Narrative context supports an electrocution injury. Flagged for review with reasoning attached.
Superficially close to “deceased” but the narrative describes a change in incurred value, not a fatality. Not flagged, and the decision is recorded.
The screening engine is deterministic and explainable. Three AI enhancements sit on top, and all fail open: if a model is unavailable, the run degrades to deterministic behaviour and never blocks ingestion.
Borderline near-misses are accepted or rejected with written reasoning. Ambiguous cases are tagged as needing review, never guessed.
A plain-language summary of any claim: injury and loss type, parties, venue signal, and a recommended next action.
Originals are kept verbatim. Every AI decision is labelled as such, with the reasoning stored beside the row it touched.
Keywords, jurisdictions, thresholds and bands tuned to your book, no deployment required.
Change the list and re-score an ingested run instantly, with no re-extraction.
A multi-sheet Excel export carrying every flag, every decision, and the exact config snapshot that scored the run.
Laundry-list review is job two. Job one reads first notices of loss and opens the claim record.
Yes, that’s the point. Your hazard vocabulary and your problem jurisdictions are configured per tenant, with no deployment work, and a guard prevents a run against an empty dictionary. The lists stay yours; we never publish or share them.
It stops and asks. Borderline near-misses are adjudicated with written reasoning; genuinely ambiguous cases are tagged as needing review and wait for a human. Nothing ambiguous is forced into a band.
Yes. Extraction preserves the link between each value and the row it came from, so text a reader would miss, hidden, truncated or spilling across merged cells, still lands on the correct claim, and the original is kept verbatim.
Yes, instantly. A configuration change retriages an already-ingested run with no re-extraction, and the export carries the exact config snapshot that scored it, so you always know which list produced which flags.
The laundry-list job screens claims for attention: which rows in a bulk listing deserve a handler’s eyes, and why. The Bordereaux Analyst reconciles premium and claims bordereaux as financial documents, including version comparison across runs. Different questions, different Analysts.
30 minutes, no slide deck. We run a real cedent file, against your vocabulary if you bring it, and show every flag with its reasoning.
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