Streamlining Reinsurance Claims Submission: Quickly Extracting Support Docs for Proof of Loss — Reinsurance Claims

Reinsurance claims handlers shoulder a unique burden: assembling airtight proof-of-loss packages under tight deadlines, across complex treaties, and from sprawling claim files. When recoveries are delayed, cash flow tightens and ceded results suffer. The challenge is simple to describe but notoriously hard to fix—finding every required document, citation, and treaty reference across thousands of pages, then packaging it to match each reinsurer’s checklist. Nomad Data’s Doc Chat eliminates that grind. Our AI-powered agents automatically identify and extract the supporting documentation needed for reinsurance proof-of-loss submissions, so your team can move from intake to recovery in minutes, not weeks.

Doc Chat is purpose-built for insurance and reinsurance workflows. It ingests entire claim files—proof of loss forms, adjustment reports, loss notices, and correspondence files—as well as treaty contracts, slips, and endorsements. It then cross-references what’s required by treaty conditions, follows reinsurer-specific submission rules, compiles a citation-backed packet, and answers real-time questions like “Show all pages documenting quantum” or “Where is the first notice date relative to the treaty’s reporting threshold?” If your mandate is faster, cleaner reinsurance recoveries, this is the missing engine in your process. Learn more about Doc Chat for insurance teams here.

The Reinsurance Claims Handler’s Reality: Volume, Variability, and Verification

In reinsurance, the proof-of-loss standard is exacting. Reinsurers expect complete, verifiable documentation that supports coverage attachment, aggregation, quantum, and payment. For a Reinsurance Claims Handler working across property, casualty, and specialty lines, that means harmonizing three sources of complexity:

First, the volume. Large losses and catastrophe events often produce claim files that span thousands—sometimes tens of thousands—of pages. Supporting materials for a single ceded recovery can include policy declarations and endorsements, underwriting files, bordereaux, field and desk adjustment reports, engineer evaluations, police reports, medical records, demand letters, payment logs, and lengthy correspondence threads between the cedent, insured, brokers, counsel, TPAs, and vendors. Those documents arrive in inconsistent formats and naming conventions across multiple systems and shared drives.

Second, the variability. Reinsurance contracts are not standardized. A handler may juggle quota share treaties, excess-of-loss treaties with hours clauses, facultative certificates with bespoke exclusions, follow-the-fortunes/follow-the-settlements language, and reinsurer-specific reporting thresholds. Aggregation standards, definition of ultimate net loss, attachment points, occurrence definitions, and reinstatement provisions vary by treaty, year, and program. Each counterparty may also require a different proof-of-loss form, different version of the adjustment report, or a specific reconciliation tying paid loss, ALAE, and salvage/subrogation back to accounting statements. Even the order and labels in the submission package can differ.

Third, verification under scrutiny. Reinsurers increasingly expect page-level substantiation. If a treaty requires prompt notice, the handler must show the first loss notice date and all follow-on notices within contractual timeframes. If an exclusion is in play (for example, communicable disease, cyber, war, mold, or wear-and-tear), the handler must surface all relevant references—both supporting and adverse—and demonstrate why coverage still attaches or how losses were aggregated. In litigation-prone scenarios, incomplete documentation invites dispute, reserve uncertainty, and delayed cash.

Within this landscape, a Reinsurance Claims Handler’s core value is judgment, negotiation, and strategy. Yet much of their day is consumed by the hunt: finding the right pages, validating timelines, checking the treaty language, and assembling a proof-of-loss package that stands up to audit and arbitration. That is exactly where Doc Chat delivers leverage.

How the Process Is Handled Manually Today

Most ceded claims teams still rely on manual workflows to assemble reinsurance submissions. The core steps are familiar but painstaking:

Handlers or operations staff export the claim file from a claims system and shared repositories. They search for first notice of loss (FNOL), coverage letters, field and desk adjustment reports, payments and reserve logs, invoices, engineering reports, and key correspondence. Treaty contracts and endorsements are pulled from the reinsurance program files, while facultative certificates and slips are retrieved separately. If there is a catastrophe event, they gather catastrophe coding, hours clause analysis, and allocation memos. This document hunt alone can take hours or days for complex losses.

Then comes reconciliation. Teams compare what the treaty requires at proof of loss against what the file actually contains: proof of loss forms, adjustment reports, loss notices, correspondence files, payment histories, and a clear calculation of ultimate net loss. They attempt to reconcile paid loss and ALAE to the ceded billing, tie allocation methodologies back to occurrence definitions or hours clauses, and confirm that notice obligations were met. Missing items generate emails to TPAs, brokers, adjusters, or defense counsel. The cycle repeats.

Finally, assembly and QA. Every reinurer might want a different order of documents, bespoke summaries, or cross-references. Handlers compile PDFs, insert bookmarks and tables of contents, annotate key pages, and draft memos explaining aggregation and attachment. QA reviewers verify completeness and accuracy, but with human fatigue and time pressure, even experienced teams can miss a critical endorsement, late notice, or contradictory statement hidden deep in the correspondence. When reinsurers ask follow-up questions, the team re-opens files, re-runs searches, and re-traces citations.

This manual cycle is slow, inconsistent, and difficult to scale during surge events. It drives up loss-adjustment expense, delays recoveries, and increases the risk of disputes or denials that could have been prevented with a more systematic approach.

AI for Extracting Proof of Loss Documents: What Changes with Doc Chat

Doc Chat replaces the hunt-and-peck with automated, audit-ready extraction across entire claim and treaty files. The agents are trained on your reinsurance playbooks and submission standards so they know exactly what a complete proof-of-loss package should look like for each treaty and reinsurer.

Doc Chat ingests the full corpus—proof of loss forms, adjustment reports, loss notices, correspondence files, payment registers, reserve histories, tender/coverage letters, underwriting files, treaty wordings, endorsements, slips, facultative certificates, and bordereaux. It automatically classifies every document type, identifies what is required by the applicable treaty, and gaps-checks the file. If something is missing, it flags it instantly so you can request it before submission—no more back-and-forth after the fact.

Once complete, Doc Chat auto-assembles a reinsurer-specific proof-of-loss package with page-level citations. If your counterparty wants the adjustment report first, followed by payment history, correspondence extracts, and then coverage memos, Doc Chat generates that order. If the treaty requires you to demonstrate timeliness of notice, Doc Chat builds a timeline and cites the exact pages showing the initial loss notice and subsequent updates. If you must evidence aggregation under an hours clause, Doc Chat extracts all event timing references and creates an hours analysis with linked sources—all in minutes.

Reinsurance Claim Submission Automation, Step by Step

Under the hood, Doc Chat performs functions a human team cannot do at scale or speed:

Document-type detection and normalization: Automatically identifies evidence such as FNOL letters, email threads, adjustment summaries, engineer/IME reports, police reports, medical records, invoices, bordereaux entries, policy endorsements, treaty clauses, and facultative certificates.
Condition-driven checklists: Interprets treaty conditions and reinsurer preferences to generate a dynamic, case-specific proof-of-loss checklist—no more static templates that miss nuance.
Cross-referencing and reconciliation: Reconciles paid and reserved amounts to the proof-of-loss schedule and to ceded accounting, highlights discrepancies, and ties quantum to source pages.
Timeline construction: Builds a regulatory and treaty timeline for notice, coverage triggers, event hours (if applicable), and payment milestones with citations to the underlying documents.
Coverage trigger and exclusion surfacing: Surfaces all mentions of potentially relevant clauses and endorsements (e.g., occurrence definitions, anti-concurrent causation, disease or cyber exclusions).
Follow-the-fortunes awareness: Extracts settlement rationale and defense strategy from correspondence, tying it to treaty obligations and settlement standards when applicable.
Reinsurer-specific packaging: Produces a submission packet organized to match counterparty preferences, including labeled bookmarks, tables of contents, and structured summaries.
Real-time Q&A: Answer questions like “Where is the hours clause satisfied?” or “List all versions of the adjustment report and their key differences,” returning answers with links to the exact page.

Because Doc Chat is trained on your playbooks, it follows your approaches to aggregation, allocation, and documentation. It does not replace your judgment—it accelerates and standardizes the work you already do while eliminating blind spots and rework.

Find Supporting Docs for Reinsurance Recoveries: The Specifics That Matter

Different lines and programs demand different evidence. For a Reinsurance Claims Handler, Doc Chat targets the core document set required for timely and defensible recoveries across reinsurance and claims:

Proof of Loss Forms: Identifies the correct PoL form, verifies all fields, reconciles totals to paid loss and ALAE, and attaches source pages.
Adjustment Reports: Collects field and desk adjuster reports, engineer evaluations, photos, and revisions; highlights changes and rationales.
Loss Notices: Surfaces first and subsequent notices, logs all milestones, and tests timeliness against treaty thresholds.
Correspondence Files: Extracts coverage letters, tender/denial letters, reservation-of-rights, demand letters, negotiation threads, and counsel memos; links each to impact on coverage or quantum.
Treaty and Fac Wordings: Pulls relevant clauses, endorsements, definitions (occurrence, ultimate net loss, follow-the-settlements), exclusions, and hours clauses; creates a clause compendium with citations.
Payments and Reserves: Ties transactions to proof-of-loss schedules and any bordereaux entries; flags inconsistencies and includes ledger screenshots or exports.
Salvage and Subrogation: Identifies recoveries and offsets; documents how they affect ultimate net loss.
Aggregation Support: Builds an occurrence or hours clause timeline; includes meteorological reports, incident logs, or event memos as required.
Accounting and Reinsurance Billing: Connects proof-of-loss totals to ceded accounting statements and reinstatement premiums where applicable.

From there, Doc Chat assembles everything into a reinsurer-ready package, with the ability to export structured fields for your accounting team or bordereaux updates. That includes optional exports and checklists to feed downstream systems without manual keying.

How Doc Chat Reads Like Your Best Handler—At Scale

Reinsurance and claims documentation rarely state answers cleanly on a single page. Often, what a handler needs is scattered across hundreds of pages, or it’s implicit in context (for example, the combination of payment logs, adjustment entries, and an email confirming allocation). As described in Nomad Data’s perspective on document intelligence Beyond Extraction: Why Document Scraping Isn’t Just Web Scraping for PDFs, the work is not about location—it’s about inference. Doc Chat captures unwritten rules, learns your team’s heuristics, and encodes them so the system can reason across the entire file the way your senior handlers do.

Real-time Q&A is a force multiplier. As you review a draft PoL packet, you can ask, “List all references to communicable disease and the pages where they appear,” or “Show where the occurrence definition is cited in the settlement rationale,” and Doc Chat will respond with answers linked to exact source pages. This page-level explainability builds trust and simplifies internal QA and external audits—an approach mirrored in Great American Insurance Group’s experience with Nomad, where instant page citations improved speed and oversight (read the case insights).

Where the Time Goes Today—And How to Win It Back

Ask any Reinsurance Claims Handler where time disappears, and the answers repeat: searching for the first true notice, locating the final signed adjustment, reconstructing hours clause analysis, retracing the settlement rationale, and tying ledger entries to proof-of-loss totals. The administrative layer often matches or exceeds the analytical layer. During catastrophe surge, manual processes break down entirely.

Doc Chat removes this friction. It ingests all documents in one pass, applies your treaty and reinsurer playbooks, and produces a complete, reinsurer-specific package. Instead of spending days compiling and reconciling, handlers spend minutes validating the packet and applying judgment on coverage and negotiation strategy. In high-volume environments, this frees up enormous capacity without adding headcount, reducing cycle times and loss-adjustment expense while accelerating cash collections.

Examples of Reinsurance Claim Submission Automation in Action

Consider a property XoL treaty with an hours clause across a wind event producing hundreds of claims. The cedent aggregates claims by location and event timing and prepares a single proof-of-loss to the program. Doc Chat scans adjustment reports and correspondence to build an hours timeline, links meteorological data and site logs, reconciles payments and ALAE across contributing claims, and surfaces any exclusions raised during coverage analysis. It then produces a treaty-specific package with clear aggregation and a citation index. Finance receives a structured export to support ceded accounting and reinstatement premium calculations.

Now shift to a casualty facultative certificate with bespoke exclusions and a complex bodily injury case. The reinsurer wants complete defense correspondence and rationale for settlement strategy. Doc Chat extracts the coverage letters and reservations-of-rights, compiles counsel memos, links defense invoices and timesheets, and identifies all references to potential exclusions (e.g., abuse/molestation, punitive damages). It builds a settlement rationale summary tied to the certificate’s follow-the-settlements language, with page citations to support each point.

In both scenarios, what used to take days of searching, bookmarking, and bundling becomes a few targeted reviews and approvals—without compromising quality or defensibility.

Streamline Proof of Loss Package Assembly AI: A Playbook-Driven Approach

Every ceded program and reinsurer is different. Doc Chat’s advantage is customization via the Nomad Process: we train the agents on your treaty portfolio, template language, house style, and reinsurer preferences. The result is a playbook-driven automation that reflects your organization’s standards—not a one-size-fits-all tool.

During onboarding, we align on:

Document sources: Claims systems, DMS/ECM, shared drives, email archives, broker portals, and SFTP feeds.
Treaty and fac portfolio: Wordings, endorsements, schedules, slips, and historical addenda.
Submission standards: Reinsurer-specific checklists, preferred order of documents, required summaries, and citation formats.
QA expectations: Internal review steps, sign-offs, and audit trails for regulators, reinsurers, and reinsurance intermediaries.

Doc Chat then encodes these preferences and continuously improves with use. As your treaties evolve or reinsurer requirements shift, the agents adapt quickly—no need to re-engineer the entire workflow.

The Business Impact: Faster Recoveries, Lower LAE, Fewer Disputes

Reinsurance is as much about cash management as it is about risk transfer. The speed and quality of your proof-of-loss process directly affect liquidity and earnings. With Doc Chat, reinsurance claims and claims teams consistently see four categories of impact:

1) Time savings. Reviews that took days are reduced to minutes. For large files, what historically required weeks collapses into a same-day exercise. Handlers start with a complete, citation-backed packet rather than a blank slate.

2) Cost reduction. Lower loss-adjustment expense comes from fewer manual touchpoints, less overtime, and reduced reliance on external vendors for file summaries and aggregation analyses. Automation also limits iterative rework when reinsurers ask follow-up questions—answers are already linked to pages.

3) Accuracy and defensibility. Page-level citations eliminate ambiguity. Consistent, playbook-driven extraction means fewer missed exclusions, better hours clause documentation, and more reliable reconciliation of payments and ALAE to proof-of-loss totals and ceded accounting.

4) Financial outcomes. Faster, cleaner submissions accelerate cash collections and reduce reserve volatility. Strong documentation lowers the risk of denials or arbitrations and improves negotiating leverage. The net effect is reduced leakage and more predictable ceded results.

Sample Prompts Your Team Can Use on Day One

Doc Chat’s real-time Q&A gives handlers superpowers. Here are examples used by reinsurance and claims teams to speed up proof-of-loss assembly and review:

“List everything we must include for a valid proof-of-loss submission under Treaty 2022-01 and show which items are missing.”
“Extract all versions of the adjustment report and summarize the differences in valuation.”
“Build an hours clause timeline from event references; include start/end timestamps with page citations.”
“Show where notice obligations are satisfied; flag any potential late notice exposure.”
“Identify any exclusion references (communicable disease, cyber, war) and the context for each.”
“Reconcile paid loss + ALAE to the proof-of-loss schedule; show variances over $10,000.”
“Generate a reinsurer-ready package ordered for Partner X with a table of contents and bookmarks.”

Because answers come with clickable references back to the exact page, internal reviewers and reinsurers can verify facts instantly—no more scrolling through thousand-page PDFs to find a single date or clause.

Security, Auditability, and Governance Built for Insurance

Reinsurance submissions often contain highly sensitive personal and corporate information. Nomad Data is built for this environment. We maintain enterprise-grade security and governance, support strict access controls, and provide document-level traceability for every answer. Outputs are always defensible: each fact links back to a specific page and document instance, making oversight straightforward for compliance, regulators, reinsurers, and auditors. The design aligns with best practices highlighted in our client stories, where page-level citations became central to trust and adoption.

Why Nomad Data’s Doc Chat Is the Best Solution for Reinsurance Claims Teams

Doc Chat is not generic AI. It is a suite of purpose-built, insurance-native agents trained on your documents and rules. Five differentiators ensure rapid, lasting value for Reinsurance Claims Handlers and operations teams:

1) Volume without headcount. Doc Chat ingests entire claim and treaty files—thousands of pages at a time—so proofs of loss move from days to minutes. Surge volumes from catastrophe events no longer require overtime or new hires.

2) Mastery of complexity. Exclusions, endorsements, definitions of occurrence and ultimate net loss, hours clauses, and aggregation logic are often buried in dense, inconsistent wordings. Doc Chat finds and connects them so your coverage positions are both accurate and defensible.

3) The Nomad Process. We train Doc Chat on your playbooks, documents, reinsurer standards, and internal QA expectations. This white glove approach yields a solution that fits your workflows from day one.

4) Real-time Q&A, page-linked. Ask, “Where is the coverage trigger documented?” and get the answer with source citations. Verification and training become effortless.

5) A strategic partner. You are not just buying software. You gain a partner who co-creates with you, updates agents as treaties evolve, and helps expand automation beyond proof-of-loss into intake, fraud detection, policy audits, litigation support, and due diligence.

Implementation is simple and fast—typically one to two weeks to an initial production-ready deployment. Teams can start with a drag-and-drop interface for immediate results, then integrate with claims handling systems, DMS/ECM, and reinsurance accounting platforms when ready. Learn more about the product and onboarding approach on the Doc Chat page here.

From Manual to Modern: A Short Case Scenario

A ceded claims team needed to assemble a proof-of-loss for a large casualty matter under a quota share treaty and a facultative certificate. The file spanned over 6,000 pages of correspondence, counsel memos, defense invoices, and adjustment materials. Historically, the team took one to two weeks to gather documents, build a timeline, tie paid loss and ALAE to a PoL schedule, and draft the package—then fielded follow-up questions from the reinsurer that required another week of rework.

With Doc Chat, the handler uploaded the full file plus the treaty and fac wording. In minutes, Doc Chat produced a reinsurer-specific proof-of-loss packet with:

A complete document checklist cross-referenced to the treaty.
A notice timeline with page citations demonstrating contract compliance.
Coverage and exclusion references extracted from legal correspondence and linked to the wordings.
A reconciliation of paid loss and ALAE to the PoL schedule with variance flags.
A settlement rationale summary aligned to follow-the-settlements language.

Questions from the reinsurer were answered the same day by asking Doc Chat to surface precise citations. The result: a faster recovery, lower LAE, and a cleaner audit trail.

Beyond Proof-of-Loss: End-to-End Automation Opportunities

Once teams see the speed and accuracy gains on proof-of-loss assembly, they quickly expand to adjacent workflows:

Intake and triage. Auto-organize incoming claim packages and treaty documentation; flag which reinsurance programs may attach based on loss characteristics and policy/treaty mapping.

Fraud and anomaly detection. Surface inconsistent statements, duplicative invoices, or deviations from typical damage patterns. This is especially useful when building settlement rationales and defending coverage positions.

Portfolio analytics. Scan treaty portfolios for unwanted exposures and out-of-date clauses, then surface candidates for mid-term endorsements or renewal strategy—consistent with our broader AI for insurance perspective on proactive policy audits and risk mitigation.

Litigation support. Build discovery-ready sets with page citations, summarize depositions, and identify key testimony or expert opinions with links—mirroring capabilities described in our industry guide on AI for claims and litigation.

These extensions are possible because Doc Chat does more than summarize; it encodes your institutional knowledge and turns document piles into structured, defensible intelligence. For context on why this matters, see Nomad’s viewpoint on the transformation of medical and complex file review, where summaries that took weeks now take minutes, with better consistency and fewer blind spots—The End of Medical File Review Bottlenecks.

Change Management: Building Trust and Uplifting the Role

Adopting AI should elevate your handlers, not replace them. We recommend the same approach that accelerated adoption at industry peers: start by testing Doc Chat on claim files your team knows intimately. When handlers watch the system return page-linked answers to questions they’ve already resolved—often in seconds—skepticism turns to confidence. Our experience, echoed in carrier stories, is that trust grows quickly when teams see consistent, defensible results on their own data.

As your team’s confidence grows, you can formalize new workflows. Handlers focus on judgment and negotiation while Doc Chat handles reading, extraction, and packaging. Managers gain standardized outputs that simplify QA and training. New hires onboard faster because best practices are now encoded, not tribal knowledge. Over time, the reinsurance function spends more time on strategy and less on search, assembly, and rework.

Getting Started: A Practical Path to Value in 1–2 Weeks

We keep onboarding simple:

Step one: upload a representative set of claim files, treaty documents, and a sample reinsurer checklist. Step two: we configure Doc Chat to your playbook and submission standards. Step three: your team runs side-by-side comparisons against recent proofs of loss to calibrate extraction and packaging. From there, you can roll out to broader classes or programs. Integrations to claims and DMS/ECM platforms follow when you’re ready, but they aren’t prerequisites for immediate value.

Nomad’s white glove service ensures a smooth start. Our specialists—experienced in both insurance domain work and AI systems—bridge the gap between how your team thinks and how machines process. That hybrid skillset is essential to capture the nuanced rules that govern real-world reinsurance submissions, as we discuss in our article on the new discipline of document intelligence (read more).

Key Takeaways for Reinsurance Claims Handlers

If you’re evaluating AI for extracting proof of loss documents or piloting reinsurance claim submission automation, focus on these essentials:

Start with a treaty and reinsurer where time-to-cash is critical; baseline current cycle times and rework rates.
Codify your playbook—what must be included, in what order, and how it should be labeled.
Demand page-level explainability: every answer must link to a verified source page.
Measure impact in four buckets: cycle time, LAE, dispute rates/denials, and collected cash vs. expected.
Plan for scale: catastrophe surge and complex losses should be the standard, not the exception.

With Doc Chat, the proof-of-loss package becomes a byproduct of normal handling rather than a separate project. Your team can finally spend their time on the parts of the job that require expertise—coverage judgment, negotiation, and strategy—rather than document wrangling.

Conclusion: Turn Documentation into Cash, Faster

Reinsurance claims handling has always been about precision and speed. The burden of proof sits with the cedent, and the quality of your documentation directly drives recoveries. Doc Chat transforms that burden into an advantage. By automatically finding and extracting the supporting documents—proof of loss forms, adjustment reports, loss notices, correspondence files—and aligning them to treaty conditions, Doc Chat accelerates proof-of-loss submissions and lifts the entire reinsurance function.

The result is faster recoveries, reduced loss-adjustment expense, fewer disputes, and a happier, more strategic team. In a market that rewards speed and defensibility, that’s a material edge. Explore how our insurance-native agents can power your reinsurance submissions—and much more—on the Doc Chat product page here. For broader context on how claims organizations are reimagining complex file review with AI, we recommend this client perspective: Reimagining Insurance Claims Management with AI.

About Nomad Data’s Doc Chat

For insurance organizations who wrestle with mountains of claim forms, coverage documents, medical records, intake forms, applications, demand packages, treaties, and certificates, Doc Chat by Nomad Data is a suite of purpose‑built, AI‑powered agents that automate end‑to‑end document review, claims summaries, legal/demand review, intake and data extraction, policy and treaty audits, proactive fraud detection, and much more. It ingests entire claim files without adding headcount, finds hidden coverage and trigger language, answers real-time questions with page citations, and standardizes outputs according to your playbooks—so nothing important slips through the cracks.