Verify Claims Attachments Instantly: AI Matching of Claims Files with Reinsurance Treaty Layers (Reinsurance, General Liability & Construction)

When an excess liability claim arrives, every hour counts. Excess Liability Reinsurance Specialists must quickly determine whether the loss actually pierces the attachment point and which reinsurance treaty layer, if any, is triggered. Yet verifying attachment often requires reconciling thousands of pages across claims files, layer schedules, excess of loss treaties, and attachment point documentation. The stakes are high: a single misread endorsement or missed defense erosion update can derail recoveries or spark disputes.

Nomad Data’s Doc Chat solves this bottleneck. Doc Chat is a suite of purpose-built, AI-powered agents that automatically read and cross-map underlying claim attachments against treaty layer triggers—instantly validating excess claims and surfacing page-cited evidence. Instead of spending days combing through PDFs and spreadsheets, an Excess Liability Reinsurance Specialist can ask, “Does this claim attach to the 10 xs 5 layer under the 2021 GL tower?” and get an answer—backed by citations—in seconds. Learn more about the product here: Doc Chat for Insurance.

The attachment challenge in Excess Liability Reinsurance for General Liability & Construction

Attachment validation in General Liability (GL) and Construction is uniquely complex. The Excess Liability Reinsurance Specialist must interpret layers and retentions through the lens of dynamic policy structures, jurisdictional case law, and evolving reserves. Real-world GL/Construction losses often straddle multiple policy periods and carriers, involve additional insureds under wrap-up programs (OCIPs/CCIPs), and include defense costs that may or may not erode limits depending on the state and the specific policy wording. Construction defect (CD) and catastrophic bodily injury claims can involve multi-year continuous triggers, horizontal vs. vertical exhaustion debates, and complicated allocation of indemnity and defense across insureds and sites.

Complicating factors include:

Self-insured retentions (SIRs) and deductibles that may be per-occurrence, per-claim, or per-location and can sit outside the primary policy.
Defense inside vs. outside limits treatment, which materially affects erosion and when excess layers are pierced.
Additional insured endorsements, blanket AI clauses, and contractual indemnity/hold-harmless agreements shifting loss between parties.
Wrap-up complexities (OCIP/CCIP) with separate aggregates, project-specific endorsements, and enrollment lists.
Jurisdictional rules on exhaustion (e.g., horizontal vs. vertical) and continuous trigger/stacking nuances across policy years.
Sub-limits (e.g., products-completed operations), aggregates (per project vs. general aggregate), occurrence definitions, and prior-known loss exclusions.
Reinsurance treaty definitions of Ultimate Net Loss (UNL), extra-contractual obligations, ex gratia payments, corridors, and inner-aggregate conditions.

For GL and Construction books, this means attachment is not simply “paid indemnity exceeds X.” It requires reconciling loss runs, reserve/paid transaction logs, coverage letters, policy forms, endorsements, wrap-up manuals, settlement agreements, engineer/incident reports, and the excess of loss treaty wording—then mapping those to the layer schedule in the correct policy year with the correct exhaustion model.

How the manual process works today—and why it’s so slow

Today, Excess Liability Reinsurance Specialists typically receive a loss advice or bordereau entry from the cedent, along with a claims packet. The packet may include FNOL, adjuster notes, defense invoices, medical summaries, indemnity payment history, coverage correspondence, and relevant policy documents. The specialist manually verifies whether the claim attaches to a particular treaty layer by reconciling the cedent’s reported incurred/paid figures against all applicable retentions, primary limits, and exhaustion requirements, then compares the net to the treaty’s attachment point and defined UNL.

The reality of this manual process:

Files are sprawling: a single complex GL/Construction file can exceed 5,000–10,000 pages, with policy documents scattered across years and multiple endorsements arriving post-inception.
Attachment math is dynamic: reserves move, defense invoices trickle in, and settlement structures (e.g., indemnity vs. allocated loss adjustment expense) change how quickly limits erode.
Layer schedules and treaty slips live in separate systems—often Excel and PDF—requiring side-by-side review and rekeying.
Critical evidence—like an endorsement clarifying defense inside limits—may be buried deep in an appendix.
Back-and-forth with cedents is common to obtain missing attachment point documentation, updated loss runs, or copies of excess policies.

Even the most experienced Excess Liability Reinsurance Specialist spends hours or days per file confirming the attachment story, especially when allocations span multiple insurers or policy years. The result is slow triage, delayed recoveries, potential leakage, and documentation that may be hard to defend during audits or arbitrations.

AI for validating claim attaches to reinsurance layers: Doc Chat’s purpose-built automation

Nomad Data’s Doc Chat is designed to do what humans shouldn’t have to: read everything and never miss a page. Doc Chat ingests entire claim files and treaty documentation—claims files, layer schedules, excess of loss treaties, attachment point documentation, bordereaux, loss advices, coverage letters, policy forms, endorsements, and transaction logs—then automatically extracts all fields relevant to attachment. Ask it in plain English: “Does this loss attach to the 25 xs 25 treaty layer for 2022?” and get a page-cited answer with the math explained.

What Doc Chat does, step by step:

Ingest & classify: Reads massive mixed-document sets (thousands of pages per claim file) and classifies by type—policy decks, endorsements, wrap manuals, defense invoices, settlement agreements, loss runs, layer schedules, and treaty slips.
Extract key facts: Pulls SIR/deductible terms; whether defense erodes; primary/umbrella limits and aggregates; occurrence definitions; AI/contractual indemnity provisions; project-specific aggregates; and wrap-up enrollment details.
Map to treaties: Aligns the claim with the correct treaty year(s) and layer schedule entries, handling per-occurrence vs. aggregate, corridors, UNL definitions, inner aggregates, exclusions, and special acceptances.
Compute exhaustion: Reconciles paid vs. reserved indemnity and ALAE, calculates erosion sequence, and applies jurisdictional exhaustion logic if specified by the playbook.
Validate attachment: Determines if and where the claim pierces the attachment point, and which excess treaty layer(s) are triggered.
Provide citations: Every conclusion is linked back to specific pages (policy endorsements, loss run entries, invoices, treaty clauses) so specialists can verify instantly.

This isn’t generic summarization. It’s domain-specific inference that encodes how reinsurance professionals actually work. Doc Chat has been shaped around reinsurance playbooks, layer schedules, and attachment rules so outputs reflect your standards. Learn how this depth differs from “web scraping for PDFs” in Beyond Extraction: Why Document Scraping Isn’t Just Web Scraping for PDFs.

Automate excess claim layer verification with page-cited math

Consider a construction defect loss with disputed dates of occurrence, AI endorsements, and defense inside limits. The cedent reports $18.2M incurred, with $9.0M paid indemnity and $4.6M paid defense to date. Primary GL is $2M per occurrence with defense inside limits; an umbrella sits $5M xs $2M; then a follow-form excess $10M xs $7M; and a top layer of $25M xs $17M. The reinsurance tower is 50% of $10M xs $10M and 100% of $25M xs $25M across different treaty years due to a multi-year trigger.

Doc Chat will:

Confirm defense inside limits from the policy form and endorsements.
Compute erosion across the primary and umbrella, applying SIR and deductibles.
Allocate indemnity and defense across policy years if your playbook requires continuous trigger/horizontal exhaustion assumptions.
Map the net UNL to the treaty layer schedule for each applicable year.
Return an “Attachment Verification Memo” that shows which layer(s) attach, the exact erosion arithmetic, and a list of cited pages supporting each step.

In practice, what used to take an Excess Liability Reinsurance Specialist several days of cross-checking is now completed in minutes—with better documentation and fewer blind spots. That speed isn’t hypothetical; see how claims teams cut review time dramatically in Reimagining Insurance Claims Management: GAIG Accelerates Complex Claims with AI.

“Match claim amount to excess treaty automatically” with real-time Q&A

Doc Chat’s real-time Q&A lets you interrogate the file the way you think:

“What is the attachment point for the 2021 excess treaty and does current paid/indemnity/defense pierce it?”
“Show erosion by policy and policy year with defense allocation assumptions per the Construction playbook.”
“List all references to defense inside limits in the primary and umbrella, with citations.”
“Summarize wrap-up coverage terms relevant to project-specific aggregates and how they affect exhaustion.”
“Create a layer-by-layer waterfall for UNL and highlight where the reinsurance treaty attaches.”

Because Doc Chat ingests the entire record, each answer links directly to the source pages—loss runs, invoices, endorsements, treaty clauses—so the Excess Liability Reinsurance Specialist can verify the math instantly. This is the antidote to slow triage, late notices, and attachment disputes. It’s also how you consistently apply internal rules at scale, a theme explored in The End of Medical File Review Bottlenecks.

“Extract and crosscheck attachment points AI”: 12 high-value validations out of the box

Doc Chat comes with a library of reinsurance-specific checks that Excess Liability Reinsurance Specialists can use from day one and tailor over time:

Attachment Point Confirmation: Extracts attachment points from layer schedules and treaty slips; reconciles against cedent’s bordereaux entries.
Limit & Aggregate Verification: Validates per-occurrence limits, general aggregates, products-completed operations aggregates, and project-specific aggregates in GL/Construction settings.
Defense Erosion Logic: Determines whether defense is inside or outside limits, and recalculates erosion accordingly.
SIR/Deductible Treatment: Applies SIRs/deductibles correctly to occurrence and location, recognizing endorsements that alter default application.
Additional Insured & Contractual Indemnity: Identifies AI endorsements and hold-harmless provisions affecting allocation.
Wrap-Up Adjustments: Accounts for OCIP/CCIP terms, enrollment lists, and project aggregates during exhaustion calculations.
Occurrence Definition & Trigger: Flags conflicting definitions and jurisdictional trigger rules that change stacking/exhaustion.
Ultimate Net Loss (UNL): Maps indemnity and ALAE to UNL per treaty wording, excluding ex gratia or non-covered items where required.
Exclusions & Inner Aggregates: Surfaces endorsements and treaty exclusions (e.g., EIFS, residential, NY Labor Law, subsidence) and applies any inner aggregate caps.
Recoveries, Salvage, Subro: Accounts for offsets and credits that affect UNL presented to reinsurers.
Notice & Reporting: Checks compliance with reporting thresholds and timelines, citing treaty notice provisions.
Year & Layer Mapping: Ensures the right claim components are mapped to the correct treaty year and layer, including reinstatements if applicable.

The result is a repeatable, auditable attachment determination that captures all the moving parts of GL and Construction losses without relying on tribal knowledge sitting in a single expert’s head.

What documents can Doc Chat read for reinsurance attachment validation?

Doc Chat ingests entire claim and treaty files—thousands of pages at a time—and normalizes insights across inconsistent formats. For Excess Liability Reinsurance Specialists, the most common document sets include:

Claims Files (FNOL, adjuster notes, demand letters, medical summaries, defense invoices, settlement agreements, surveillance and investigator reports)
Layer Schedules (program towers, share percentages, reinstatement provisions)
Excess of Loss Treaties (slips, wordings, endorsements, special acceptances, inner-aggregate riders)
Attachment Point Documentation (cedent attestations, loss advices, bordereaux, loss run reports, accrual/transaction logs)
Underlying Policy Forms (primary GL, umbrellas, follow-form excess, wrap-up manuals, AI endorsements, project-specific endorsements)
ISO claim reports and litigation pleadings relevant to occurrence definitions and damages
Engineering reports, OSHA/incident logs, and site records establishing dates of occurrence or project enrollment

These materials rarely look the same from one cedent to another. That’s exactly why the ability to reason across unstructured documents—not just extract fields—is critical. Our approach to this problem is discussed in depth in Beyond Extraction.

The business impact: faster triage, cleaner recoveries, fewer disputes

Reinsurers and reinsurance operations teams feel the pressure of rising volume and complexity. Doc Chat directly addresses the root causes of delay, leakage, and inconsistency in attachment validation.

Expected outcomes for Excess Liability Reinsurance Specialists and their organizations:

Time savings: Move attachment checks from days to minutes. High-volume teams consistently see 70–90% reductions in review time.
Cost reduction: Lower loss adjustment expense by automating rote review and reducing reliance on external consultants for attachment analysis.
Accuracy & defensibility: Page-cited conclusions that stand up to audit, arbitration, reinsurer queries, and regulatory reviews.
Reduced disputes: Standardized logic minimizes interpretive variance across desks and time zones; fewer back-and-forth cycles with cedents.
Scalability: Surge capacity for CAT and large-loss events without adding headcount.
Better reserves & cashflow: Confident, early attachment determinations bring forward recoveries and stabilize financials.

These improvements mirror the broader benefits our clients see when they use AI to eliminate manual document review. For a macro view of speed and quality gains, see Reimagining Claims Processing Through AI Transformation.

Why Nomad Data’s Doc Chat is the best fit for reinsurance attachment validation

Doc Chat is purpose-built for insurance and reinsurance document work, not a generic LLM wrapper. It combines industrial-scale ingestion with rigorous, insurance-specific reasoning and the ability to adapt to each carrier’s and reinsurer’s playbooks.

Key differentiators for Excess Liability Reinsurance Specialists:

Volume at speed: Ingest entire claim and treaty files—thousands of pages per case—without tiring or missing a page.
Complexity mastery: Reads ambiguous policy and treaty language, digs out exclusions/endorsements, and applies your attachment logic consistently.
The Nomad Process: We train Doc Chat on your reinsurance playbooks, attachment rules, GL/Construction standards, and reporting formats to deliver your output, your way.
Real-time Q&A: Ask, “match claim amount to excess treaty automatically,” and get an answer with page citations and a transparent calculation trail.
Thorough & complete: Surfaces every relevant reference to limits, aggregates, erosion entries, and treaty triggers so nothing slips through the cracks.
Your AI partner: We co-create solutions and iterate with your team—this is not one-size-fits-all software.

And you don’t wait months to see value. Our white-glove approach routinely delivers meaningful production use in 1–2 weeks. Secure, compliant, and enterprise-ready, Doc Chat meets strict governance standards and is SOC 2 Type 2 aligned, with page-level traceability on every answer.

Implementation in 1–2 weeks: a playbook for excess reinsurance teams

We’ve streamlined implementation so Excess Liability Reinsurance Specialists can start validating attachments immediately while IT aligns integrations behind the scenes.

Discovery (Days 1–3): Share sample claims files, layer schedules, excess of loss treaties, and attachment point documentation. We review your attachment logic, UNL definitions, and jurisdictional assumptions for GL/Construction.
Preset & Q&A design (Days 3–5): We encode your “Attachment Verification Memo” format and build Q&A prompts that mirror how your specialists work.
Pilot on live files (Days 5–10): Drag-and-drop ingestion; Doc Chat returns attachment determinations with citations. We calibrate edge cases and confirm outputs align with your standards.
Integrations (Weeks 2–3, optional): API connection to claims, reinsurance accounting, and document repositories so Doc Chat retrieves documents and posts memos automatically.

Because Doc Chat works out of the box, teams typically start cutting cycle time the same week they begin testing. See how fast teams build trust in AI when they test on familiar files in our GAIG webinar recap: Reimagining Insurance Claims Management.

From triage to portfolio oversight: expanding value beyond a single claim

Once attachment validation is automated at the claim level, reinsurance organizations unlock portfolio-wide advantages:

Daily bordereaux validation: Re-run attachment checks across every new bordereaux row; auto-flag mismatches for analyst review.
Quarterly treaty audits: Sample or review 100% of recoveries for attachment integrity, exclusions, and UNL compliance—something manual teams rarely have time to do.
Scenario analytics: Simulate alternative exhaustion assumptions (e.g., defense outside limits) to quantify sensitivity in recoveries.
Litigation support: Produce page-cited attachment narratives for arbitration or commutation negotiations.
Change management: Rapidly roll out new attachment rules or jurisdictional updates across the team via updated presets—no lengthy retraining cycles.

In short, the same engine that confirms a single claim attaches also strengthens reinsurance governance and reduces leakage across the entire portfolio.

Security, auditability, and trust

Doc Chat was built for regulated, high-stakes environments like insurance and reinsurance. Every answer includes a transparent audit trail with page-level citations. IT and compliance retain control over data flows, identity management, and retention. Outputs are easy to verify and defensible to auditors, reinsurers, and regulators.

Worried about AI “hallucinations” in document tasks? When questions are constrained to the documents provided, LLMs perform exceptionally well at extracting and reconciling facts—especially when outputs must cite source pages. Read how enterprise-grade controls and auditability turn AI into a trustworthy teammate in AI’s Untapped Goldmine: Automating Data Entry.

FAQ: What Excess Liability Reinsurance Specialists ask us most

Can Doc Chat handle multi-year GL/Construction losses with continuous trigger and horizontal exhaustion assumptions?

Yes. We encode your jurisdictional and playbook rules—continuous trigger, horizontal or vertical exhaustion, stacking assumptions, project-specific aggregates—and Doc Chat allocates indemnity and ALAE accordingly, then maps results to the correct treaty years and layers.

How does Doc Chat treat defense costs?

Doc Chat extracts endorsements and policy language indicating whether defense is inside or outside limits, then recalculates erosion. If your standards require alternative scenarios (e.g., test both), Doc Chat can produce a comparison with separate waterfalls and citations.

Can it distinguish UNL from non-recoverable items under our treaty wording?

Yes. The agent reads the XoL wording and applies your UNL definition, excluding ex gratia, punitive (if excluded), uncovered fees, or non-allocated expenses as per your rules and treaty language.

What about wrap-ups (OCIP/CCIP) and additional insured complexities?

Doc Chat identifies wrap-up participation, project-specific aggregates, and AI endorsements. It adjusts exhaustion and allocation accordingly, citing the wrap manual, enrollment, endorsements, and policy declarations.

How quickly can we be live?

Most teams are using Doc Chat on real claims within 1–2 weeks. Initial use can be drag-and-drop—no integration required. API integrations with claims and reinsurance accounting systems typically follow in 2–3 weeks.

Does it integrate with our reinsurance accounting or claims platforms?

Yes. We support modern APIs and can push the “Attachment Verification Memo,” structured fields (attachment point, layer triggered, UNL, citations), and flags directly into your systems of record.

A day in the life with Doc Chat: from hours to minutes

Before Doc Chat, an Excess Liability Reinsurance Specialist might spend half a day verifying a single GL/Construction loss attachment, combing through policy endorsements, defense invoices, and spreadsheets. After Doc Chat, that flow looks like this:

Drag-and-drop the claims file, layer schedules, excess of loss treaties, and attachment point documentation into Doc Chat.
Ask: “Automate excess claim layer verification: Does this loss attach to 10 xs 10 under the 2020 treaty?”
Review the generated attachment memo, which includes the math, a layer-by-layer waterfall, and citations to the exact pages relied upon.
Follow-up with a Q&A prompt: “Show where defense is stated to be inside limits and list total defense paid by policy year.”
Export the memo and structured fields to your reinsurance accounting system and save the citations for audit.

The specialist spends their time validating conclusions and engaging with higher-value judgment calls—not retyping numbers from PDFs.

Quantifying the upside for reinsurance organizations

Across clients, we consistently see material economic impact when attachment validation is automated:

Cycle time: 80–90% reduction in time-to-attachment decision, accelerating recoveries.
Throughput: 3–5x increase in files per analyst without adding headcount.
Leakage: Fewer missed endorsements, exclusions, or inner aggregates; reduced over/under-recoveries.
Dispute avoidance: Page-cited logic reduces challenges from cedents/reinsurers and streamlines arbitration prep.
Talent utilization: Specialists focus on strategic negotiations, portfolio insights, and complex scenarios.

These gains mirror the broader industry shift we’re driving—moving human experts from rote reading to high-judgment work—outlined in Reimagining Claims Processing Through AI Transformation.

From pilot to standard operating procedure

Adopting Doc Chat often starts with a single reinsurance team piloting attachment checks on live GL/Construction claims. Within weeks, memos become standardized artifacts; reinsurance accounting consumes structured fields; audit teams adopt page-cited outputs as the gold standard; and underwriting analytics taps the same extraction to analyze layer utilization and portfolio risk.

Because Doc Chat “institutionalizes” your best attachment logic, your outcomes stop depending on who handled the file. New hires onboard faster, seasoned specialists avoid burnout, and executives get consistent, defensible answers at scale.

Ready to “AI for validating claim attaches to reinsurance layers” across your portfolio?

If attachment checks eat your calendar—or if you’ve ever struggled to defend a reinsurance recovery—you’re an ideal candidate for Doc Chat. Start by validating a handful of live GL/Construction files and measuring cycle time, accuracy, and dispute rates. Most teams never go back to manual after seeing the first page-cited memo.

See how Doc Chat delivers immediate value to insurance organizations: Doc Chat for Insurance. Then imagine that power applied to every claims file, layer schedule, excess of loss treaty, and attachment point document you touch.

Key takeaways for Excess Liability Reinsurance Specialists

When your mandate includes verifying attachment on complex GL/Construction losses, Doc Chat gives you the speed, depth, and citations to make defensible decisions in minutes:

AI that can match claim amount to excess treaty automatically and explain the math.
Purpose-built logic to automate excess claim layer verification across multi-year triggers and wrap-up complexities.
Out-of-the-box validations to extract and crosscheck attachment points AI—with page-level proof.
White-glove implementation in 1–2 weeks, trained on your reinsurance playbooks.

The result is a step-change in how reinsurance teams operate—fewer bottlenecks, fewer disputes, and more time spent on strategy instead of search.