Verify Claims Attachments Instantly: AI Matching of Claims Files with Reinsurance Treaty Layers for Claims Handlers

For Claims Handlers and Excess Liability Reinsurance Specialists working across Reinsurance and General Liability & Construction, one of the most time-consuming and error-prone steps in excess claims triage is validating whether a loss actually attaches to a specific treaty layer. You must reconcile thousands of pages of claims files against layer schedules, read dense excess of loss treaties, and confirm attachment point documentation—often under tight settlement clocks and cash-flow pressure. The cost of getting it wrong is high: delayed recoveries, leakage, disputes, and strained reinsurer relationships.

Nomad Data's Doc Chat solves this verification bottleneck by instantly cross-mapping underlying payments, retentions, and erosion against treaty layer triggers with page-level evidence. Instead of days of manual spreadsheeting, Claims Handlers can ask in plain language: "Does this loss attach to the 10x10 excess treaty? Show the proof of exhaustion and the calculations," and get a fully-cited answer in minutes. This article explains how Doc Chat reduces triage time, automates excess claim layer verification, and gives Claims Handlers in Reinsurance and GL & Construction a defensible, auditable path to faster, more accurate recoveries.

The core challenge: validating layer attachment in Reinsurance and GL & Construction is uniquely complex

Layer attachment sounds simple—confirm the loss amount exceeds the attachment point and that underlying layers are exhausted. In practice, Claims Handlers face a thicket of real-world nuances that make validation anything but straightforward:

• Horizontal vs. vertical exhaustion: Depending on jurisdictions and wording, the loss may need to exhaust all underlying insurers horizontally (e.g., all participating carriers in a layer) or vertically (per policy). Construction defect and products-completed operations claims often span multiple policy periods with complicated allocation.
• Defense costs inside vs. outside limits (DIL vs. DOL): In GL & Construction, defense costs may erode limits, directly affecting when a treaty attaches. You must track which policies include defense within limits and how that erosion interacts with attachment points.
• Self-insured retentions (SIR) and deductibles: Proof that the insured satisfied an SIR can be scattered across invoices, ACH confirmations, and adjuster notes. Without validated SIR payment, attachment timing may be incorrect.
• Related/Batch/Series claims: Construction defect, premises liability, and product liability claims can collapse into a single occurrence via batch language or be split across occurrences by project or claimant—materially changing when a layer attaches.
• Coverage triggers & allocation across years: Occurrence vs. claims-made, continuous trigger doctrines, and per-project aggregates (OCIP/CCIP) complicate attachment. Allocation across policy years changes which treaties and treaty years are implicated.
• Wrap-up complexities (OCIP/CCIP): Additional insured endorsements, contractual indemnity, and risk transfer shift payment burdens among parties. Claims Handlers must ensure underlying recovery is properly recognized before attributing erosion towards an attachment point.
• Endorsements and exclusions: Endorsements buried in policy files (e.g., per-project aggregate endorsements, products-completed operations, subcontractor warranties) affect whether and when a loss erodes underlying limits toward attachment.
• Follow the Fortunes/Settlements, Claims Cooperation, and Late Notice: Reinsurance treaty clauses determine what proof is needed for the reinsurer to pay and whether any notice or cooperation issues threaten recovery.
• Facultative vs. treaty interplay: Facultative certificates may sit alongside treaty reinsurance. The handler must match the correct instrument and terms to the loss.

Each of these items depends on meticulous review and reconciliation of claims files, layer schedules, excess of loss treaties, and attachment point documentation, as well as related forms such as loss run reports, FNOL forms, ISO claim reports, underlying policy declarations, endorsements, settlement agreements, defense invoices, and reinsurance bordereaux. The workload and risk of human error make this the perfect use case for AI for validating claim attaches to reinsurance layers.

How Claims Handlers manage layer verification manually today

Across Reinsurance and GL & Construction, the current process is manual and fragmented. A typical day looks like this:

• Download or receive a claims file—often a patchwork of PDFs: adjuster notes, reserves history, payment ledgers, defense invoices, medical reports, demand letters, settlement agreements, and correspondence.
• Open the layer schedule for the insured's tower—primary, excess layers (e.g., 4x1, 5x5, 10x10), aggregates, and per-project specifics.
• Pull the applicable excess of loss treaty wording and endorsements for the relevant treaty year(s) and line(s) of business; identify key clauses: follow the settlements, follow the fortunes, claims cooperation, ex gratia limitations, late notice, and reporting obligations.
• Gather attachment point documentation: proof of underlying exhaustion (EOBs, payment advices, ledger screenshots), proof of SIR, defense cost erosion evidence when inside limits, and any commutations affecting erosion.
• Construct a spreadsheet to reconcile all underlying payments and erosion against the treaty attachment point; attempt to tie each figure back to a source page for audit.
• Determine whether batch/series or related claims language applies; if so, rationalize the occurrence count and its impact on limits and attachment.
• Verify allocation across years and policies, especially for long-tail GL or construction defect claims. Confirm vertical/horizontal exhaustion per governing law and policy/treaty wording.
• Write a memo summarizing findings with citations and forward for approval, reserving time to respond to queries from reinsurers, actuaries, auditors, or counsel.

Even for seasoned Claims Handlers, the cycle can span days or weeks, particularly when claims exceed 5,000 pages or when towers include multiple carriers with different defense-in-limit treatments. During surge events or heavy construction defect seasons, backlogs are inevitable. The result: slow cash, inconsistent determinations, and higher loss adjustment expense (LAE).

Documents and forms that drive layer decisions

Layer verification relies on complete, consistent documentation. Doc Chat is purpose-built to read and reason across the documents and forms Claims Handlers use every day, including:

• Claims Files: adjuster notes, reserve change logs, payment ledger exports, correspondence, subrogation and contribution tracking, demand letters, settlement agreements, deposition transcripts.
• Layer Schedules: tower charts by year and project, per-occurrence and aggregate limits, per-project aggregate endorsements, OCIP/CCIP specifics, schedules of participating markets and shares.
• Excess of Loss Treaties: treaty wordings, endorsements, claims cooperation and notice provisions, follow-the-settlements language, ex gratia provisions, reporting templates.
• Attachment Point Documentation: proof of SIR payment, underlying insurer payment confirmations, bordereau extracts, defense invoices (when inside limits), EOBs, coverage counsel analyses.
• Related Forms: FNOL forms, ISO claim reports, loss run reports, policy endorsements, additional insured endorsements, certificates of insurance, reinsurance bordereaux, Notice of Loss (NOL) letters to reinsurers.

For Reinsurance and GL & Construction Claims Handlers, the volume and heterogeneity of these sources create the perfect storm of manual complexity. This is precisely where AI can extract and crosscheck attachment points end-to-end, with full explainability.

What Claims Handlers actually need to answer in triage

Every hour counts. Fast, defensible answers to these questions define a superior triage process:

• Does the loss attach to the treaty layer? If yes, which layer and how much is recoverable net of underlying?
• Is underlying exhaustion proven and consistent with the applicable exhaustion doctrine (horizontal vs. vertical)?
• Do defense costs erode limits for the applicable policies? Is there clear documentation proving erosion to the attachment point?
• Has the SIR been satisfied in full? Where is the proof?
• Is the loss a single occurrence or part of a batch/series affecting limits and attachment?
• Which endorsements and exclusions impact erosion, occurrence count, or allocation?
• Are there any notice or claims cooperation issues under the treaty that could affect recovery?
• What is the recommended reserve and provisional recovery given current information, and what additional documents are needed to finalize?

Doc Chat is designed to provide these answers instantly, with an auditable chain back to the exact pages in your claims files, layer schedules, excess of loss treaties, and attachment point documentation.

How Doc Chat automates layer verification for Claims Handlers

Doc Chat by Nomad Data is a suite of AI-powered agents built specifically for high-volume, high-complexity insurance document workflows. For reinsurance and GL & Construction claims, it delivers end-to-end automation for verifying whether an excess claim attaches to a specific treaty layer.

AI for validating claim attaches to reinsurance layers

Doc Chat ingests entire claim files and treaty materials—thousands of pages at once—and answers targeted questions in real time. Ask: "Show all payments that erode the primary $1M occurrence limit and indicate the remaining headroom." Receive an itemized list with citations to the ledger pages, defense invoices, and policy language that dictates whether costs erode limits. Then follow up: "Given the 5x1 and 10x6 layers, has the loss reached the 10x6? Provide calculations and note vertical vs. horizontal exhaustion requirements."

Match claim amount to excess treaty automatically

Doc Chat automatically reconciles paid indemnity and defense with retentions, deductibles, and underlying limits. It references the layer schedule to determine the correct sequence, reads the treaty wording to understand exhaustion doctrine, and compiles a math-ready table showing when each layer is pierced. Calculations are linked to source pages in the claim file or policy/treaty documents, eliminating manual spreadsheeting and rework.

Automate excess claim layer verification

Using your organization's playbooks, Doc Chat runs a standardized attachment checklist across every file: SIR proof, defense-in-limits evidence, batch/series evaluation, occurrence definition mapping, related claims/linkage analysis, endorsements affecting allocation, and treaty conditions (notice, cooperation). It flags missing documents, drafts a document request list, and stores a fully-cited audit report that can be shared with reinsurers, auditors, or counsel.

Extract and crosscheck attachment points AI

Doc Chat extracts the numeric attachment points and limits from the layer schedule and treaty, crosschecks them against payments, and verifies erosion paths according to policy/treaty terms. It disambiguates defense cost treatment and notes any jurisdictional rules that impact exhaustion. The output: a single, consistent view of whether—and where—the claim attaches, plus the precise evidence you need to defend the determination.

Example: Construction defect claim with multi-year allocation and per-project aggregate

Consider a GL & Construction defect claim spanning two policy years with a per-project aggregate endorsement for a wrap-up (OCIP). The tower includes:

• Primary: $1M per occurrence/$2M aggregate, defense inside limits.
• Excess A: $4M xs $1M (defense inside underlying; outside on this layer).
• Excess B: $5M xs $5M (defense outside limits).
• Treaty: 10x10 XOL for the reinsurer, attaching at insurer's layer point with vertical exhaustion.

The claim file contains 6,800 pages of invoices, expert reports, mediation briefs, and settlement statements, plus two years of policy endorsements and the reinsurance treaty wording. Manually, a Claims Handler might spend days tying invoices to erosion and verifying which year's aggregate was triggered by project coding, then reconciling defense costs that erode the primary but not the excess layers.

With Doc Chat, the Claims Handler drags and drops all materials and asks: "Allocate defense and indemnity by project and policy year. Show whether Year 1's per-project aggregate is hit. Then calculate erosion toward $1M primary; determine when $4M xs $1M attaches; and show whether $5M xs $5M is pierced. Finally, state whether the 10x10 treaty attaches and produce an attachment proof memo."

Doc Chat returns:

• A table allocating costs by project and year, citing how the project codes in invoices map to policy endorsements.
• Evidence that defense costs erode the primary but not the $5M xs $5M layer, with citations to the policy DIL/DOL language.
• Confirmation that Year 1's per-project aggregate is exhausted and Year 2 is partially eroded but not exhausted.
• Layer-by-layer calculations showing attachment for the $4M xs $1M layer and that the $5M xs $5M layer is pierced late in the claim lifecycle.
• A treaty attachment memo citing the vertical exhaustion requirement and summarizing notice and cooperation compliance.

The Claims Handler reviews the memo, asks a follow-up: "List any missing documents needed for reinsurer proof," receives a checklist (e.g., underlying insurer payment confirmations for two indemnity entries), and triggers a request. What took days now takes minutes.

Business impact: speed, accuracy, and recoveries with audit-ready proof

Doc Chat materially improves outcomes for Claims Handlers and their leadership teams:

• Cycle time reduction: From days/week-long manual reconciliation to minutes. As described in The End of Medical File Review Bottlenecks, Doc Chat summarizes and interrogates massive files in minutes, not weeks. Similar gains appear in the GAIG case study: GAIG Accelerates Complex Claims with AI.
• Accuracy and consistency: Machines never tire. They read page 1 and page 6,800 with equal rigor, standardizing attachment proofs per your playbook. See Reimagining Claims Processing Through AI Transformation for precision gains on large files.
• Reduced leakage and disputes: Attachment proofs with citations reduce back-and-forth with reinsurers and auditors. Fewer errors in defense-in-limit treatment and underlying exhaustion mapping mean fewer write-offs and faster cash.
• Scalability without headcount: Surge-ready. When a construction defect wave hits or a portfolio of litigated GL claims arrives, Doc Chat keeps pace by processing entire towers and treaty years in parallel.
• Employee engagement: Claims Handlers move from spreadsheeting to strategic questions. As noted in AI's Untapped Goldmine, offloading rote work improves morale and retention.

For leadership, the math is compelling: faster recoveries, lower LAE, improved reserve accuracy, better reinsurer relations, and an audit-ready process that stands up to scrutiny.

Designed for explainability, controls, and compliance

In Reinsurance and GL & Construction, attachment proofs must be defensible. Doc Chat records a page-level audit trail for every calculation and assertion, with clickable citations to the exact lines in ledgers, invoices, policy endorsements, and treaty clauses. This evidence model is central to trust, as highlighted in the GAIG experience: page-cited answers accelerated adoption and satisfied compliance and legal stakeholders.

Doc Chat fits within enterprise governance: SOC 2 Type II controls, role-based access, retention rules, and export options that preserve chain-of-custody for auditors and reinsurers. When your Claims Handler says, "The 10x10 attaches," Doc Chat shows exactly why—and where the proof lives.

From manual to automated: what changes for the Claims Handler

Doc Chat standardizes a best-practice flow that mirrors how top Claims Handlers already work, but at machine speed:

1. Ingest & classify: Drag-and-drop claims files, layer schedules, excess of loss treaties, and attachment point documentation. Doc Chat classifies by type and project/year.
2. Preset checklists: Your playbook is encoded as a checklist—SIR proof, DIL/DOL mapping, exhaustion model, batch/series analysis, notice/cooperation review, facultative/treaty interplay.
3. Real-time Q&A: Ask targeted questions: "Provide the vertical exhaustion path for Layer B," or "List missing documents to finalize attachment." See instant answers with citations.
4. Attachment memo: Export a formatted attachment memo (PDF/Word) with calculations, tables, and footnoted citations fit for reinsurer submission.
5. Integrate: Push results to the claim system or reinsurance accounting via API or SFTP for bordereau updates and recovery booking.

The result is a repeatable, defensible process that transforms attachment verification from an artisanal, person-dependent art into a consistent, auditable workflow.

Why Nomad Data: beyond basic extraction to true inference

Most tools can scrape numbers. Very few can infer how those numbers interact with complex policy and treaty language at scale. Doc Chat was engineered for this exact cognitive workload. As we explain in Beyond Extraction, document intelligence for insurance isn't about locating fields—it's about inferring outcomes from scattered, often implicit signals across thousands of pages.

Doc Chat differentiators for Claims Handlers in Reinsurance and GL & Construction:

• Volume: Ingest whole claim files and policy/treaty sets—thousands of pages per file—without added headcount.
• Complexity: Reads endorsements, exclusions, and trigger language to resolve defense-in-limits, batch/series, and exhaustion doctrine—so layer attachment decisions are accurate and defensible.
• The Nomad Process: We train Doc Chat on your playbooks, checklists, and standards for attachment proofs, ensuring alignment with your reinsurance accounting and legal teams.
• Real-time Q&A: "List all payments allocated to Project ABC in Year 1 that erode the per-project aggregate"—answered in seconds, across massive files.
• Thorough & complete: Surfaces every reference to coverage, liability, damages, and erosion across documents to avoid leakage and blind spots.
• Strategic partnership: White-glove service and co-creation ensure we evolve with your needs, from OCIP nuances to multi-year allocation models.

For Claims Handlers, that means less time wrestling with documents and more time driving outcomes.

Implementation: white glove onboarding in 1–2 weeks

We deploy Doc Chat fast, with minimal IT lift:

• Week 1: We review your attachment verification playbooks, sample claim files, layer schedules, treaties, and reporting formats. You receive a working environment where you can drag and drop files for immediate results.
• Week 2: We tune presets for your DIL/DOL rules, SIR evidence requirements, vertical/horizontal exhaustion logic, and attachment memo templates. Optional API integration to your claim or reinsurance systems follows shortly after.

As seen in our client stories, teams often start same-day using the drag-and-drop interface, then integrate via API/SFTP for automated exports. Learn more at Doc Chat for Insurance.

SEO spotlight: incorporate your high-intent needs directly

Because the pain is so specific, we've tuned Doc Chat's language and presets to match how Claims Handlers search for solutions:

• AI for validating claim attaches to reinsurance layers: Configure preset prompts that mirror your verification checklist and jurisdictional rules.
• Match claim amount to excess treaty automatically: Auto-calculate erosion and attachment using policy/treaty logic with clean, exportable tables.
• Automate excess claim layer verification: One-click generation of attachment proof memos with page-level citations.
• Extract and crosscheck attachment points AI: Pull attachment points and limits from layer schedules and treaties, validate against ledger and invoices, and flag inconsistencies.

These phrases aren't just marketing—Doc Chat operationalizes them inside the workflow Claims Handlers already use in Reinsurance and GL & Construction.

Frequently asked questions from Claims Handlers

How does Doc Chat handle multi-year allocation and batch/series language?

Doc Chat reads occurrence definitions, related claims/batch provisions, and any per-project aggregate endorsements. It then aligns invoices, payments, or injuries with project and time markers to produce an allocation table and occurrence mapping, citing sources for each decision point.

What if defense costs are sometimes inside and sometimes outside limits?

Doc Chat parses each policy's DIL/DOL terms and applies the correct erosion treatment by year and layer. It highlights mismatches between how costs were recorded and how they should impact erosion.

Can it spot missing proof for attachment?

Yes. Doc Chat checks for SIR proof, underlying insurer payment confirmations, and settlement statements. It generates a tailored missing-doc list and a standard request email for the adjuster, insured, or underlying carrier.

How defensible are the outputs with reinsurers?

Every assertion includes citations—down to the page and paragraph—making reinsurer Q&A faster and less contentious. This aligns with best practices highlighted in GAIG's webinar on page-level explainability.

Does it integrate with reinsurance accounting and bordereaux?

Yes. Export attachment memos, calculations, and recovery amounts in your preferred formats; push to reinsurance accounting and update bordereaux automatically via API or SFTP.

How fast does it process large files?

Doc Chat ingests and analyzes thousands of pages in minutes. As described in The End of Medical File Review Bottlenecks, clients routinely move from weeks to minutes on 10k–15k page sets.

Operational best practices for Reinsurance and GL & Construction teams

To maximize impact, Claims Managers and Layering Analysts can deploy a few proven tactics:

• Standardize your attachment memo format and let Doc Chat populate it. Consistency accelerates reinsurer review.
• Encode your exhaustion doctrine by jurisdiction and treaty wording so Doc Chat applies the right vertical/horizontal model every time.
• Prescribe evidence rules (what counts as SIR proof, how to treat defense invoices without clear coding) to reduce exceptions.
• Centralize endorsements and teach Doc Chat where to find per-project aggregates, AI endorsements, and products-completed ops language.
• Use real-time Q&A for investigations: Ask, "List all references to additional insured endorsements and how they impact risk transfer on Project 27."

These steps convert your institutional knowledge into a scalable system that every Claims Handler can leverage on day one.

Evidence from the field: what peers are experiencing

Carriers using Doc Chat for complex claims report:

• 70–95% reduction in time to produce an attachment proof memo for excess GL and construction-defect claims.
• Fewer re-submissions to reinsurers due to missing or inconsistent evidence; cleaner page-level citation trails reduce escalations.
• Improved reserving—earlier clarity on attachment informs more precise reinsurance recoverables and net exposure.
• Higher staff satisfaction; Claims Handlers spend more time on negotiations and strategy, less on document wrangling.

These outcomes mirror the broader improvements seen across claims automation initiatives described in AI for Insurance: Real-World Use Cases.

Where Doc Chat fits in your stack

Doc Chat meets you where you are. Start by uploading files through the secure UI for immediate value. When ready, integrate:

• Inbound: Automated ingest from claim systems, DMS, or SFTP. Pre-classify by line of business (GL, Construction), project, and policy year.
• Outbound: Push attachment memos, calculations, and recovery fields to your claim platform, reinsurance accounting, and BI dashboards.
• Security: SOC 2 Type II, role-based controls, PII safeguards, and options for private model routing to satisfy enterprise IT.

Because Doc Chat is purpose-built for insurance, there's no need for your team to become AI engineers. As we note in AI's Untapped Goldmine, the technical heavy lifting is handled for you—your team simply defines the outputs and rules.

From search intent to operational impact

If you've searched for any of the following, Doc Chat is likely the answer:

• "AI for validating claim attaches to reinsurance layers"
• "match claim amount to excess treaty automatically"
• "automate excess claim layer verification"
• "extract and crosscheck attachment points AI"

What distinguishes Doc Chat is that it not only finds and extracts information—it reasons across policies and treaties to produce the attachment determination, along with the citations you need to defend it to reinsurers, auditors, and counsel.

Next steps: see Doc Chat on your own files

The fastest way to build trust with Claims Handlers is to load a claim they know cold and ask Doc Chat the hard questions. That's how GAIG moved from skepticism to adoption—by watching the system find answers, with citations, in seconds on familiar cases. In less than two weeks, you can go from proof-of-concept to live workflow with white-glove support, presets aligned to your playbooks, and optional integrations to your claim and reinsurance systems.

Ready to turn days of manual verification into minutes of confident, auditable decisions? Learn more and request a tailored demo at Doc Chat for Insurance.

Conclusion

Verifying whether a loss attaches to a reinsurance treaty layer shouldn't require a multi-day hunt through sprawling claims files and dense treaties. For Claims Handlers in Reinsurance and General Liability & Construction, Doc Chat transforms attachment verification into a fast, transparent, and standardized process. It automates excess claim layer verification, matches claim amounts to excess treaties automatically, and extracts and crosschecks attachment points with the rigor and citations your stakeholders demand. The result is faster recoveries, lower LAE, fewer disputes, and happier teams who can focus on strategy rather than spreadsheets. That's what modern claims excellence looks like—and it's available today.