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

Reinsurance and claims operations teams are under intense pressure to assemble impeccable Proof of Loss packages quickly, completely, and in a format each reinsurer will accept. The challenge isn’t just volume—it’s variability. Supporting documentation for reinsurance recoveries is scattered across claim systems, shared drives, email threads, and vendor portals. File structures are inconsistent. Deadlines are firm. And the reputational stakes are high if submissions arrive late or incomplete.

Nomad Data’s Doc Chat was built to fix this bottleneck. Doc Chat uses purpose-built, AI-powered agents to ingest entire claim files, instantly find supporting docs for reinsurance recoveries, and assemble exactly what each treaty or facultative certificate requires. For an Operations Manager working in Reinsurance and Claims, this means moving from manual hunting and gathering to reinsurance claim submission automation that compiles accurate, defensible Proof of Loss packages in minutes—not days.

Why Proof of Loss Packages Are So Hard in Reinsurance Operations

In Reinsurance and Claims, the Operations Manager is accountable for the orchestration: coordinating data, documents, and deadlines across ceded claims, accounting, legal, and the handling desk. The nuance is that reinsurance Proof of Loss packages are not one-size-fits-all. They differ by treaty (e.g., catastrophe XOL vs. per-risk, quota share) and by reinsurer. A single CAT event can require dozens of recoveries across layers and markets, each with unique documentation checklists, coverage proofs, and payment evidence expectations. Meanwhile, the underlying claim files are dynamic—reserves change, payments post, attachments get updated—and all of it must reconcile to treaty attachment points, participation percentages, and reinstatement terms.

Operationally, that means locating and validating items like the signed Proof of Loss Forms, the latest Adjustment Reports (including addenda), Loss Notices and updates (FNOL through subsequent notices), and complete Correspondence Files with reinsurers and brokers. It also means extracting and reconciling paid-to-date, ALAE/ULAE splits, reserve movements, deductible/retention application, subrogation/salvage status, and per-occurrence vs. per-risk aggregation. The documentation supporting all of that is scattered across:

• Policy and endorsement files impacting coverage triggers and limits
• Claim system notes, payment registers, and reserve logs
• Vendor PDFs: independent adjuster reports, engineering evaluations, medical records, repair estimates
• Broker correspondence and treaty-specific instructions (e.g., cooperation clauses, proof timelines)
• Accounting evidence: check images, EFT advices, bordereaux, and GL extracts to back paid/expense totals

Multiply this by multiple reinsurers (each with their own portal or email protocols), and the burden grows exponentially. When a reinsurer audits or requests clarification, your team needs page-level citations immediately. Manual approaches struggle to keep up with the pace and precision this environment demands.

How Manual Proof of Loss Assembly Works Today (and Why It Hurts)

Most Operations Managers describe a similar manual process for reinsurance submission:

1. Receive a task to prepare a Proof of Loss for a specific claim, layer, or event.
2. Search across the claim system, DMS, SharePoint sites, shared drives, and email threads for the latest versions of the requisite documents.
3. Download PDFs, rename them, and stitch together a binder or zip file with ad hoc bookmarks and an index spreadsheet.
4. Extract key data (paid to date, ALAE/ULAE, indemnity splits, dates of service, adjuster findings) into a submission template or portal form.
5. Reconcile totals to the accounting ledger and to the treaty terms (attachment points, shares, reinstatement premiums).
6. Send the package to the broker or reinsurer; answer follow-up questions with new screenshots, snippets, or recompiled PDFs.

Pain points for Reinsurance and Claims Operations include:

• Version risk: Grabbing an outdated Adjustment Report or missing the latest Loss Notice update leads to queries and delays.
• Hidden evidence: Critical exhibits hide deep in Correspondence Files or in lengthy attachments (e.g., 1,500-page medical or engineering reports).
• Reconciliation churn: Totals must match ledger extracts and treaty math exactly; manual copy-paste is error-prone.
• Time traps: Clicking through thousands of pages or emails to find a single paragraph proving cause, coverage trigger, or payment proof.
• Audit exposure: Inconsistent indexing and weak page-level citations complicate reinsurer audits and compliance reviews.

When a CAT event hits or a litigation-heavy claim grows to tens of thousands of pages, teams drown in document review. That’s why organizations are searching for AI for extracting proof of loss documents that can reliably surface exactly what each treaty requires—fast.

What Typically Belongs in a Reinsurance Proof of Loss Package

Every market and treaty has nuances, but Operations Managers in Reinsurance and Claims usually compile a core set of support:

• Signed Proof of Loss Forms and attestation letters
• Underlying policy deck pages and endorsements relevant to coverage triggers and limits
• Initial FNOL/Loss Notices and subsequent updates
• Independent and internal Adjustment Reports, including addenda and revised valuations
• Vendor reports: engineering, forensic accounting, medical reviews, IMEs, repair/replacement estimates
• Payment evidence: check copies/EFT confirmations, payment registers, bordereaux, GL extracts
• Reserve and incurred summaries (loss + ALAE/ULAE), including movement history
• Coverage determination letters and key excerpts from the Correspondence Files
• Subrogation/salvage documentation and status updates
• Treaty or facultative certificate excerpts (e.g., claims cooperation clause, notice requirements, attachment points, share)
• Layering and allocation exhibits (per occurrence vs. per risk), catastrophe coding, and aggregation support
• If litigated: pleadings, demand letters, deposition summaries, settlement agreements

The real work isn’t merely collecting these items. It’s proving that each requirement has been met, with page-level citations and a consistent, reinsurer-ready index—especially when the same claim supports multiple recoveries across different treaties and layers. This is exactly where streamline proof of loss package assembly AI changes the game.

How Doc Chat Automates Proof of Loss Assembly for Reinsurance

Doc Chat by Nomad Data is a suite of purpose-built, AI-powered agents that automate end-to-end document review, claims summaries, intake and data extraction, and compliance-ready packaging. For the Reinsurance and Claims Operations Manager, Doc Chat delivers a consistent, high-velocity pipeline that transforms messy, unstructured files into defensible Proof of Loss submissions—complete with citations.

1) Ingest entire claim and treaty files at once

Drag-and-drop thousands of pages—policies, endorsements, adjuster reports, medical or engineering files, email exports, and payment evidence—or connect Doc Chat to your DMS and claims system. Doc Chat handles large, mixed-format files without adding headcount. As described in our piece on ending medical file review bottlenecks, Doc Chat processes massive document sets quickly and consistently; see “The End of Medical File Review Bottlenecks.”

2) Auto-classify and normalize documents

Doc Chat identifies and classifies common reinsurance artifacts: Proof of Loss Forms, Adjustment Reports, Loss Notices, Correspondence Files, policy/endorsement excerpts, payment registers, bordereaux, and more—even if each reinsurer’s checklist labels them differently. This eliminates guesswork and creates a structured index from unstructured chaos.

3) Encode reinsurer- and treaty-specific checklists

We train Doc Chat on your reinsurance playbooks and treaty obligations. If Article 15 of your CAT XOL treaty requires specific exhibits for attachment validation, Doc Chat will assemble them automatically and flag gaps. If a fac certificate needs particular ALAE evidence and signed attestations, Doc Chat tracks those requirements and verifies presence—no more manual checklists living in spreadsheets. For a deeper dive into how Doc Chat captures unwritten rules, read “Beyond Extraction: Why Document Scraping Isn’t Just Web Scraping for PDFs.”

4) Extract, reconcile, and cross-check key financials

Doc Chat pulls paid-to-date, reserve details, ALAE/ULAE splits, and incurred totals from registers, bordereaux, and GL extracts. It can reconcile these figures to the submission form and the treaty math (attachment points, share percentages, reinstatement premiums). You get a clean, consistent mapping of financials—with discrepancies flagged for review before the package goes out the door.

5) Real-time Q&A across the file

Ask Doc Chat: “List all signed Proof of Loss documents and their dates,” “Show the latest revision of the IA report,” “Cite where cause of loss was confirmed,” or “Summarize ALAE transactions over $25,000 with page references.” Instead of scrolling, you get instant answers with clickable citations. See how adjusters at GAIG shifted to question-driven workflows in “Reimagining Insurance Claims Management.”

6) Auto-generate reinsurer-ready binders and cover letters

Doc Chat creates a standardized, reinsurer-approved index with bookmarks and page-level cites, then drafts the cover letter that narrates cause, coverage, quantum, and recovery calculation. It populates your Proof of Loss Forms with extracted data, inserts required exhibits in order, and names files per market preference—accelerating submission without sacrificing precision.

7) Page-level traceability and audit readiness

Every fact extracted by Doc Chat is tied to source pages. If a reinsurer asks, “Where did this reserve change?” or “Show payment evidence for the April 14 disbursement,” you click directly to the exact page. This transparent audit trail supports regulators, reinsurers, and internal compliance. It’s one reason teams quickly build trust in the system’s output.

8) Integrate without disruption

Start with drag-and-drop, then integrate to your claim platform, DMS, or broker portal via API. Implementations typically take one to two weeks—without heavy IT lift. For a broader view of how we evolve with your workflows, read “Reimagining Claims Processing Through AI Transformation.”

What the Switch to Automation Feels Like for an Operations Manager

Consider a large bodily injury claim with a facultative certificate and participation across a per-risk treaty. Historically, assembling the Proof of Loss package required chasing down the latest Adjustment Reports, confirming the signed Proof of Loss Forms, extracting reserve and paid history, and marrying all of that to the treaty math. With Doc Chat, your team drags the entire file into the workspace, including emails and PDFs. In minutes, Doc Chat:

• Lists every required document per the fac cert and treaty obligations
• Flags missing or outdated items (e.g., needs the latest loss notice addendum)
• Extracts paid/expense totals and reconciles them to the submission template
• Bookmarks the exact paragraphs where coverage triggers were confirmed
• Builds a reinsurer-ready index with page citations and consistent naming

The Operations Manager ships a complete, audit-ready package faster, with fewer email loops and revisions. When the reinsurer responds with clarifications, Doc Chat answers with citations in seconds, not hours.

Business Impact: Time, Cost, Accuracy, and Defensibility

Shifting from manual document chasing to AI for extracting proof of loss documents produces measurable outcomes for Reinsurance and Claims organizations:

• Cycle time reduction: Move from multi-day assembly to minutes. Doc Chat ingests thousands of pages at a time and extracts what you need immediately.
• Lower loss-adjustment expense: High-cost staff stop doing rote data entry and manual PDF compilation. See our perspective on the ROI of automation in “AI’s Untapped Goldmine: Automating Data Entry.”
• Accuracy that scales: Consistent extraction means fewer errors in paid/ALAE/ULAE totals, fewer back-and-forths with reinsurers, and lower leakage risk.
• Audit-proof transparency: Page-level citations and standardized indices make reinsurer audits more efficient and defensible.
• Surge capacity: During CAT events or litigation spikes, Doc Chat scales instantly—no overtime or temporary staffing required.
• Employee engagement: Teams spend more time on exceptions and negotiation strategy, less on searching and stapling PDFs.

These improvements echo what leading carriers are already experiencing with Doc Chat. In our GAIG case study recap, tasks that once took days now take moments, with page-level citations building trust across claims, legal, and audit stakeholders. See “Reimagining Insurance Claims Management: GAIG Accelerates Complex Claims with AI.”

Why Nomad Data Is the Best Partner for Reinsurance and Claims Operations

Doc Chat is more than a tool; it’s a partner. We bring a white‑glove approach that adapts to your exact reinsurance workflows, treaty obligations, and reinsurer checklists. The differentiators that matter to Operations Managers:

• Trained to your playbooks: We encode your treaty- and reinsurer-specific requirements so Doc Chat assembles packages exactly the way your team does—only faster and more consistently.
• Volume and complexity: Doc Chat ingests entire claim files, identifies exclusions or endorsements hidden in dense policies, and surfaces everything needed for coverage and quantum proofs.
• Real-time Q&A: Ask plain-language questions across thousands of pages and get instant answers with citations.
• 1–2 week implementation: Start with drag-and-drop; integrate later. Minimal IT lift. Rapid time-to-value.
• White‑glove service: Our team co-creates your checklists, templates, and binder formats and iterates until they’re perfect for each reinsurer.
• Enterprise-grade security: Nomad Data maintains SOC 2 Type 2 controls and provides clear document-level traceability for every answer.

For context on why this human‑in‑the‑loop, custom approach succeeds where generic tools fail, explore “Beyond Extraction.”

From Manual to Managed: A Practical Workflow Redesign

Here’s how Reinsurance and Claims Operations Managers typically roll out Doc Chat to achieve reinsurance claim submission automation with minimal disruption:

1. Define the target workflow: Choose one treaty or one reinsurer’s checklist to start (e.g., CAT XOL Proof of Loss).
2. Upload representative files: Include the full claim file: Proof of Loss Forms, Adjustment Reports, Loss Notices, Correspondence Files, policy/endorsements, payment evidence, vendor reports.
3. Codify requirements: We encode your checklist and data mapping (paid to date, ALAE/ULAE, reserves, occurrence aggregation).
4. Auto-assemble a test package: Doc Chat generates the binder, the index, the cover letter, and populates the submission form. Review together and calibrate.
5. Integrate and scale: Connect to your DMS/claim platform; add additional treaties, reinsurers, and lines of business.

This staged approach compresses lift while delivering quick wins that build organizational trust. In our experience, once teams see how fast Doc Chat pulls the exact pages a reinsurer asks about, adoption accelerates naturally.

What Doc Chat Finds That Humans Often Miss

Because Doc Chat maintains the same level of attention from page 1 to page 10,000, it surfaces details that manual teams commonly overlook under deadline pressure:

• Quiet reserve adjustments buried in claim notes or ledger exports that must reconcile to the Proof of Loss totals
• Coverage trigger language inside obscure endorsements that strengthen the submission narrative
• Payment evidence mismatches (e.g., EFT advice date vs. ledger post date) that would otherwise trigger reinsurer queries
• Updated adjuster valuations contained in an addendum not yet filed in the conventional folder path
• Correspondence threads confirming cooperation and notice compliance that bolster audit defensibility

This is the advantage of a system designed, as our team emphasizes, to automate cognitive document work—not just extract fields. You can learn more about this philosophy in “Beyond Extraction.”

Security, Governance, and Explainability

Reinsurance submissions move sensitive data. Doc Chat is built with enterprise-grade security, governance, and explainability at its core:

• Security: SOC 2 Type 2 controls, role-based access, and options aligned to your data residency requirements
• Explainability: Every extraction is paired with a page citation; the reasoning is visible and verifiable
• Governance: Time-stamped activity trails support internal and external audits

For Operations Managers concerned about model reliability, our experience mirrors industry findings: when asked to pull facts from provided documents, modern AI systems perform with extremely high fidelity. The risk of “hallucinations” is mitigated by keeping the AI grounded in your actual files and by requiring page-level citations. For more on the business case and reliability of document automation, see “AI’s Untapped Goldmine.”

FAQs for Reinsurance and Claims Operations Managers

Will Doc Chat work with reinsurer portal templates and broker-specific checklists?

Yes. We train Doc Chat on the precise document sets, naming conventions, and field mappings your reinsurers and brokers request. It can generate binders and cover letters that align with each market’s expectations and populate submission forms where supported.

Can Doc Chat ensure treaty compliance for notice and proof timelines?

Doc Chat can be trained to flag time-sensitive obligations (e.g., notice within X days, proof within Y days) and surface correspondence or notes demonstrating compliance, with citations. It also flags gaps so your team can remediate before submitting.

How does Doc Chat handle mixed evidence such as emails, PDFs, and spreadsheets?

Doc Chat ingests diverse formats, indexes them, and unifies the search experience. Ask a question once, and it looks across attachments, emails, PDFs, and exports, returning answers with document and page references.

What about complex allocations—per occurrence vs. per risk, ALAE loading, reinstatements?

We encode your calculation logic and data sources so the package reflects the correct math and exhibits. Doc Chat highlights any discrepancies between extracted values and expected formulas so you can resolve issues proactively.

Is the setup heavy on our IT team?

No. You can start with drag-and-drop immediately. Typical integrations into claims or document management systems complete in 1–2 weeks using modern APIs. This mirrors our broader experience accelerating claims organizations without core-system overhauls.

Operational Metrics You Can Expect to Improve

For an Operations Manager in Reinsurance and Claims, Doc Chat targets the KPIs that matter most:

• Average Proof of Loss assembly time: Reduced from days to minutes for standard packages
• First-pass acceptance rate with reinsurers: Increased through complete, consistent evidence and reconciled totals
• Reinsurer query cycle time: Cut by providing instant, page-cited responses
• Staff productivity: More submissions handled per FTE without additional headcount
• Audit and compliance findings: Fewer gaps due to standardized indices and traceability
• Employee engagement: Less time on rote hunting, more time on exceptions and strategic work

These gains echo the broader claims transformation we’ve documented across customers. Doc Chat frees experts to focus on high-value work while AI handles the reading, extracting, and compiling at industrial scale. See “Reimagining Claims Processing Through AI Transformation.”

Where the AI Fits in the End-to-End Reinsurance Submission Flow

Doc Chat can automate and assist at every step:

1. Intake: Pull documents from claims, DMS, shared drives, email, and vendor portals
2. Classification: Identify Proof of Loss Forms, Adjustment Reports, Loss Notices, Correspondence Files, policy excerpts, payment evidence, and vendor reports
3. Checklist validation: Compare present documents to reinsurer/treaty requirements; flag gaps
4. Extraction & reconciliation: Pull paid/ALAE/ULAE totals, reserves, dates, and reconcile to ledger and treaty math
5. Drafting & packaging: Assemble binder/index, draft cover letter, populate submission template
6. Q&A & audit: Support reinsurer queries with instant citations and consistent exhibits

Because the entire flow is traceable and standardized, your team gains both speed and confidence. Rather than reinventing the wheel for each submission, you scale a repeatable, reinsurer-aligned process.

Real Examples of What You Can Ask Doc Chat

Operations Managers, Claims Managers, and ceded teams use Doc Chat to run the play in seconds:

• “Show all signed Proof of Loss forms and their signatures, with dates.”
• “List the latest independent Adjustment Reports and summarize the valuation changes, with page cites.”
• “Extract paid to date for indemnity and ALAE/ULAE; reconcile to the ledger and flag any variances > $1,000.”
• “Find the correspondence proving timely notice per treaty Article 12.”
• “Build an index for Reinsurer X with their preferred naming convention and insert bookmarks.”
• “Summarize all Loss Notices and produce a timeline of material developments.”

This is the essence of find supporting docs for reinsurance recoveries: instead of scrolling, you ask. Instead of hoping someone remembers where an email thread lives, you get a precise answer with a link to the exact page.

Implementation: White-Glove, Fast, and Focused on Your Playbook

Doc Chat implementations are intentionally fast and collaborative:

1. Discovery: We review your target treaties, reinsurer checklists, and current packaging standards.
2. Configuration: We encode your requirements and build your binder/index templates and cover letter formats.
3. Pilot: You upload live files; Doc Chat assembles packages. We calibrate together.
4. Rollout: We connect to your systems and scale to additional treaties and reinsurer workflows.
5. Continuous improvement: We iterate as your obligations and markets evolve.

Most organizations see value within 1–2 weeks, beginning with drag-and-drop and expanding into integrated automation. Because Doc Chat is trained to your playbooks, you get a tailored solution that fits like a glove rather than a generic tool you must bend your process around.

Why This Works: The New Discipline of Document Intelligence

As we discuss in “Beyond Extraction,” modern document automation isn’t about scraping fixed fields. It’s about teaching machines to apply your unwritten rules across messy, real-world files—policies, endorsements, reports, and correspondence—so they can assemble evidence the way your best experts do. That’s why Doc Chat succeeds where field-based OCR and brittle templates fail. It captures both the content and the institutional logic.

For Operations Managers: A Checklist to Get Started

If you want to prove value fast, start here:

• Pick one treaty or reinsurer with a well-defined checklist and decent submission volume.
• Collect 5–10 representative claim files with full document variety (emails, PDFs, spreadsheets, vendor reports).
• Define the target outputs: binder structure, index, cover letter, and populated Proof of Loss form.
• Partner with Nomad to encode the checklist and extraction targets (paid/ALAE/ULAE, reserves, coverage proof cites).
• Run a live pilot; compare Doc Chat’s outputs to a recently submitted package.

In most cases, the improvement is immediate: packages assemble faster, totals reconcile sooner, and citations replace guesswork. Teams can then scale to more treaties and reinsurers with confidence.

Put It All Together: Streamline Proof of Loss Package Assembly with AI

Reinsurance and Claims Operations Managers are measured on speed, completeness, and defensibility. With Doc Chat, you get all three—on every submission. You’ll compress cycle times, standardize output quality, and reduce the burden on high-cost staff, while giving reinsurers exactly what they need the first time. It’s a durable advantage in an environment where late or incomplete submissions translate directly into delayed recoveries and strained market relationships.

If your team is searching for AI for extracting proof of loss documents or looking to streamline proof of loss package assembly AI-style across treaties and facultative placements, now is the moment to pilot Doc Chat. Start small, prove the win, and scale quickly with our white-glove support and 1–2 week implementation timeline.

Explore Doc Chat for insurance at Nomad Data: Doc Chat for Insurance.