Speeding Up Subrogation: Automated Extraction from Police Accident Reports for SIU Investigators

Every day, Special Investigations Unit (SIU) investigators and subrogation teams are handed police accident reports, state crash forms, and witness statements that can span dozens of pages and vary wildly by jurisdiction. Hidden in those documents are the facts that make or break recovery: who was at fault, which statute was cited, whether a commercial vehicle driver was on the clock, and what the independent witnesses actually saw. The challenge is that this critical information is often scattered across the officer narrative, coded checkboxes, diagrams, and attachments that do not follow a standardized layout. Manually piecing it together is slow, error-prone, and expensive—especially when the team is under pressure to move quickly on recoveries and fraud investigations across Auto, Commercial Auto, and General Liability & Construction claims.

Nomad Data’s Doc Chat changes this equation. Doc Chat is a suite of AI-powered agents purpose-built for insurance documents that ingest entire claim files, instantly extract the facts that matter, and answer investigator questions in real time. From police accident reports and state crash forms to witness statements and supplemental correspondence, Doc Chat consolidates and cross-checks details so SIU investigators can rapidly identify liability, find adverse carriers, and prioritize subrogation. Learn more about Doc Chat for insurance at nomad-data.com/doc-chat-insurance.

The SIU Investigator’s Reality: Why Police Accident Reports Are So Hard to Work With

In Auto, Commercial Auto, and General Liability & Construction, the police accident report (PAR) is both foundational and frustrating. PARs are not one document type; they are hundreds. Each state and many municipalities use unique formats with their own codes, diagrams, and numbering systems. An SIU investigator may see Texas CR-3 one hour, a California CHP 555 the next, and then a Florida HSMV 90010S or a New Jersey NJTR-1. Some reports arrive as crisp digital PDFs, while others are multi-generation scans with handwritten notes, faded ink, and coffee stains. Narratives may stretch pages; diagrams may include directional arrows, reference points, and legends that only make sense when viewed alongside checkboxes several sections away. For Commercial Auto and construction-adjacent claims, the complexity grows with references to hazmat boxes, vehicle configuration codes, USDOT numbers, and citations that trigger additional regulatory context.

For SIU investigators, speed is everything. Early identification of recovery potential influences reserve strategy, negotiations, and whether to dispatch a field investigation. Yet the documents are designed for public safety and statistical reporting first, not for civil liability, comparative negligence, or subrogation strategy. Key facts relevant to fault often hide in the margins: an officer’s remark that the left-turning driver admitted not seeing oncoming traffic, a witness noting the light sequence, or the presence of a commercial vehicle’s dashcam. In General Liability & Construction, jobsite incidents can involve mixed responsibilities—GC, subcontractors, and delivery trucks—where PARs are only one piece of a broader paper trail that may include incident reports, safety logs, hold-harmless agreements, and COIs. The cognitive load of reconciling all of this across forms and attachments is enormous.

Manual Processing Today: Slow, Repetitive, and Risky

Manual review is still the norm. SIU investigators or subrogation specialists typically print or screen-split the police accident report, then copy the essential fields into a subrogation worksheet or case management system. They translate state-specific codes, interpret diagrams, and cross-reference officer narratives with witness statements and photos. For a thorough review, many teams also compare the PAR to the FNOL form, ISO claim reports, medical bills, and any demand letters received. When a case involves a commercial vehicle, they verify the motor carrier’s USDOT and MCS-90 context, check loss runs, and look for evidence of contractual transfer of risk in GL & Construction matters.

This manual approach has predictable downsides: it is slow and costly; it introduces variability between reviewers; and it creates opportunities for miss. Under deadline pressure, an investigator can skim over a key checkbox indicating contributing circumstances, overlook a line that the striking vehicle was backing, or miss a secondary harmful event. Because state crash forms bury information across multiple sections, the investigator must constantly page-jump and mentally stitch facts together. Meanwhile, backlogs grow, the window to contact adverse carriers shrinks, and settlement negotiations proceed without the strongest liability footing.

AI to extract info from police reports for subrogation: What Doc Chat Delivers

Doc Chat is engineered for the complexity and variability that define police accident reports. Rather than relying on brittle templates, Doc Chat reads like a domain expert. It handles clean PDFs and messy scans, interprets checkboxes and narratives, and assembles a complete liability picture—citing the exact pages where each fact was found. It then allows SIU investigators to ask questions in plain language and get instant, defensible answers with page-level citations. This means you can ask for a liability summary, request all citations issued, identify the adverse carrier, extract all witness contact details, and verify roadway conditions in seconds—even across hundreds or thousands of pages of combined reports and supplements.

Across Auto, Commercial Auto, and General Liability & Construction, Doc Chat ingests entire claim files, including police accident reports, state crash forms, witness statements, FNOL forms, ISO claim reports, medical records, demand letters, and correspondence. It standardizes output into your preferred subrogation worksheet or case note format and updates those summaries as more documents arrive. Because Doc Chat was designed for enterprise insurance workflows, it not only extracts facts but also cross-checks them, flags contradictions, and spotlights red flags that matter to SIU.

What Gets Extracted Automatically—Structured, Searchable, and Cited

Doc Chat compiles a structured subrogation profile directly from police accident reports, state crash forms, and witness statements. Investigators can configure presets so every claim gets the same consistent review. Typical extractions include:

• Identifiers: crash ID, agency case number, officer badge and name, report date/time, GPS coordinates, intersection/roadway, mile markers
• Parties and vehicles: driver and owner names, contact details, VINs, plates, vehicle type/configuration, USDOT numbers for Commercial Auto
• Insurance data: adverse carrier name and policy number if listed, proof-of-insurance indicators, hit-and-run flags
• Conditions: weather, light, roadway surface, work zone indicators, traffic control devices, speed limit
• Pre-crash and crash dynamics: pre-accident maneuvers, sequence of events, first harmful event, manner of collision, point of impact, diagram interpretation
• Contributing circumstances: alcohol/drug involvement flags, failure to yield, speed, distraction, improper backing or lane change, vehicle defects
• Citations and statutes: statute numbers, offense descriptions, who was cited, arrested, or warned
• Injuries and EMS: KABCO injury severity, EMS run numbers, hospitals, transport times
• Witnesses: names, contact info, statements, contradictions across multiple versions
• Property damage: owner details, location, estimated damage, tow company and lot
• Attachments: photos, supplemental narratives, amended diagrams, addenda and continuation sheets

Because Doc Chat links each extracted fact to the original page, SIU investigators can click straight to the source before picking up the phone to call a witness or the adverse carrier. This maintains defensibility and auditability for subrogation and litigation.

Automate subrogation with police report processing: From Intake to Demand

Most subrogation teams have a repeatable path from first notice to demand. Doc Chat automates that path. It triages incoming police accident reports and state crash forms, immediately identifies adverse parties and carriers, and populates a subrogation worksheet or demand letter template with verified facts. If the police report includes a citation for failure to yield during a left turn or a rear-end collision with clear contributing circumstances, Doc Chat highlights the likely theory of liability and the supporting statute reference. For Commercial Auto, it extracts the carrier’s USDOT number, verifies the operating name, and notes whether the crash occurred in the course and scope of employment. In construction-adjacent GL scenarios, it links the crash location to a jobsite, flags a work zone, and prompts review of hold-harmless language and certificates of insurance.

As additional documents arrive—witness statements, supplemental reports, medical summaries, or a demand letter—Doc Chat updates the subrogation file dynamically. You can ask Doc Chat to list all discrepancies between the witness statements and the officer narrative, inventory all injuries with dates of service and providers, or compile a timeline of events from first contact to current demand. With real-time answers and consistent formatting, teams move from document collection to recovery strategy without the bottlenecks of manual extraction.

Best tool to automate accident report analysis: Why SIU Investigators Prefer Doc Chat

Doc Chat is built for the insurance document universe—not generic PDFs. Where traditional optical character recognition or template-based tools break down, Doc Chat’s agents read and reason through messy structure, dense narratives, and multi-state variability. It brings together several differentiators that SIU investigators and subrogation specialists value most:

• Volume without headcount: Ingest entire claim files—thousands of pages—in minutes, not days. Large crash packets with supplemental narratives and images are processed at scale, eliminating backlogs.
• Complexity handled: Doc Chat digs out exclusions, endorsements, and trigger language across policy files, and it interprets crash codes and officer narratives that influence coverage decisions for Auto, Commercial Auto, and GL & Construction.
• Real-time Q&A: Ask questions like summarize the police accident report for liability, list all citations issued to Unit 2, or extract every witness phone number and receive instant answers with page citations.
• The Nomad process: We train Doc Chat on your playbooks, state-by-state subrogation rules, and internal templates, so the system mirrors how your SIU and subro teams already work.
• Thorough and complete: Doc Chat surfaces every reference to coverage, liability, or damages across the file so hidden recovery opportunities don’t slip through the cracks.

For a real-world view of how claims organizations transform complex document review, see Great American Insurance Group’s story: Reimagining Insurance Claims Management. Their team cut review time from days to minutes while improving confidence through page-level citations.

SIU-Focused: Fraud Indicators and Pattern Matching, Built In

Subrogation and SIU often intersect. Not every police accident report is created equal, and Doc Chat helps SIU investigators find what others miss. By reading every page consistently, Doc Chat flags inconsistencies between the officer narrative and witness statements, surfaces recycled language that appears across unrelated claims, and notes when a clinic, tow yard, or vendor shows up repeatedly across losses. It also correlates reported injuries and treatment timelines with crash dynamics. When paired with ISO claim reports and internal historical data, these insights help investigators spot staged accidents, soft tissue mills, or organized tow-and-repair patterns earlier.

Common SIU red flags that Doc Chat can highlight automatically include:

• Contradictory statements across witnesses or between driver and witness accounts, including subtle shifts in the ordering of events
• Repeat providers, tow companies, or law firms appearing across multiple claims for the same parties or vehicles
• Injury patterns inconsistent with crash mechanics (e.g., severe injury claims in low-speed backing impacts) and treatment that begins unusually late or accelerates ahead of a demand
• Hit-and-run claims where later supplements contradict an initial report or contain new, uncorroborated details
• Unsupported weather or roadway condition claims relative to official observations in the police report

These are not one-off detections. They emerge because Doc Chat reads everything every time, without fatigue—an approach described in Nomad’s perspective on the limits of template-based extraction and the rise of inference. For more on why document intelligence is about reasoning, not just scraping, see Beyond Extraction: Why Document Scraping Isn’t Just Web Scraping for PDFs.

Cross-Line Coverage: Auto, Commercial Auto, and General Liability & Construction

In Auto, the subrogation work often focuses on driver behavior, traffic control, vehicle movements, and injuries. In Commercial Auto, additional facts matter to SIU and subro teams: the USDOT and MC numbers, carrier operating names, route and duty status, and whether the driver acted within the scope of employment. Doc Chat extracts those details and links them to potential coverage triggers, such as the presence of an MCS-90 endorsement or a leased-operator arrangement that may influence recovery paths. In General Liability & Construction, Doc Chat connects the police accident report to jobsite context by recognizing work zone flags, construction-related contributing circumstances, and contractor names, then prompting review of incident reports, subcontractor agreements, and hold-harmless provisions that might alter who ultimately pays.

The result is a unified view of liability that respects line-of-business nuances. Whether it is an Auto rear-end in stop-and-go traffic, a Commercial Auto left-turn across path near a distribution center, or a GL claim involving a delivery vehicle inside a construction zone, Doc Chat pulls the right facts forward, fast.

How Doc Chat Automates the End-to-End Subrogation Workflow

Doc Chat does more than extract fields. It orchestrates the subrogation document journey from intake to action, so SIU investigators and subrogation specialists spend less time reading and more time recovering.

Here is what the flow looks like in practice:

1. Intake and classification: Doc Chat ingests police accident reports, state crash forms, and witness statements from email, portals, or claim folders. It detects the state, form type, and version (e.g., CHP 555 vs. CHP 555-03) and routes the file to the appropriate preset workflow for Auto, Commercial Auto, or GL & Construction.

2. Extraction and normalization: The agent extracts core identifiers, parties, vehicle data, crash dynamics, citations, and injuries. It normalizes codes into plain language and maps state-specific fields into a standard subrogation schema that your team already uses.

3. Cross-check and contradiction analysis: It compares the police report to witness statements, FNOL, ISO claim reports, medical summaries, and demand letters to spot mismatches and potential SIU flags.

4. Liability narrative and theory: Doc Chat generates a concise, cited liability narrative anchored in statutes/violations noted in the report, keys in on contributory or comparative negligence where relevant, and summarizes evidence for demand or negotiation.

5. Adverse carrier and outreach prep: The agent identifies the adverse carrier if listed, compiles contact-ready data, and populates your demand letter template, subrogation worksheet, and internal case note format.

6. Real-time Q&A and updates: As more documents arrive, Doc Chat updates the summary instantly. SIU investigators can query new findings, ask follow-ups, and request timelines or discrepancy lists, all with page citations.

Business Impact: Faster Recoveries, Lower LAE, Fewer Misses

Automating police accident report processing produces measurable gains across SIU and subrogation operations.

Time savings: Teams report moving from hours of manual review per report to minutes. Instead of paging through multi-page narratives and supplementary forms, investigators jump directly to cited facts. This accelerates early outreach to adverse carriers and shortens the road from crash to demand. For medical-heavy files, Nomad’s experience shows that even enormous documents can be synthesized in minutes—a shift explored in The End of Medical File Review Bottlenecks.

Cost reduction: By trimming manual touchpoints, organizations reduce loss-adjustment expense and overtime while avoiding costly overflow to external vendors for routine extraction. One of Nomad’s core theses is that a surprising amount of complex claims work boils down to high-quality, reliable data entry and normalization at scale. See AI's Untapped Goldmine: Automating Data Entry for the economics.

Accuracy and consistency: Humans are excellent at the first few pages but fatigue as files grow. Doc Chat reads the tenth supplemental with the same precision as page one and enforces a consistent output format across every claim. Page-level citations let SIU investigators verify instantly, improving confidence and audit readiness.

More recoveries and reduced leakage: When every report is combed fully and consistently—across Auto, Commercial Auto, and GL & Construction—fewer recovery opportunities get missed. Contradictions and enabling facts surface earlier, strengthening negotiation positions and reducing claims leakage.

Why Nomad Data Is the Right Partner for SIU and Subrogation

Nomad Data brings purpose-built technology and a partnership model that matches the realities of insurance claims work:

White glove service: We do not hand you a toolkit and walk away. We sit with your SIU investigators and subrogation specialists to encode your playbooks: jurisdictional nuances, statute preferences, red flag checklists, and demand letter templates. We refine outputs until they read exactly like your best investigator’s notes.

1–2 week implementation: Because Doc Chat is delivered as a managed solution with modern APIs, deployments typically land in one to two weeks. You can start with drag-and-drop pilots and move to system integration when you are ready—without a long change-management slog.

Insurance-grade security and auditability: Nomad is SOC 2 Type 2, supports strict data governance, and provides document-level traceability for every answer. Regulators, reinsurers, and internal audit teams get the transparency they need.

Proof through performance: Adjusters and investigators consistently report aha moments when they see Doc Chat answer complex questions in seconds with pinpoint citations, an experience described in Reimagining Claims Processing Through AI Transformation and the Great American Insurance Group webinar.

Comparative Negligence and Statute-Aware Summaries

Many police accident reports contain coded contributing circumstances and citations that hint at liability but do not tell the full story. Doc Chat interprets these in context and frames a liability narrative aligned to your jurisdiction. For example, a left-turn-across-path scenario may be captured as a combination of a coded turning movement, an officer narrative about a protected phase, and a citation to a failure-to-yield statute. Doc Chat brings those together into a coherent, cited paragraph—then allows you to ask follow-ups like identify any facts that suggest comparative negligence for our insured or list all environmental factors that might dilute liability. This shifts counsel preparation and negotiation from open-ended reading to targeted analysis.

Tying Police Reports to the Rest of the File

Police accident reports rarely live alone. SIU investigators need to reconcile them with telematics or EDR downloads, dashcam transcripts, FNOL information, ISO claim reports, medical records, and demand letters. Doc Chat was designed to act as the connective tissue across the file, building a timeline that includes date and time of loss, EMS dispatch and transport, ER admissions, diagnostic imaging, and subsequent treatment. It then highlights misalignments—like when the medical narrative asserts a mechanism of injury that conflicts with crash forces or when a demand letter adds new facts not present in the police report or witness statements.

Because Doc Chat supports real-time Q&A, investigators can ask context-rich questions: show me all references to braking prior to impact; list every mention of speed estimation; extract every time the claimant described how the crash occurred; or compare the first and second witness statements for contradictions. The answers come back in seconds with citations, enabling immediate follow-up and outreach.

Template-Resistant Variability Is the Norm—And That Is Exactly Where Doc Chat Excels

Traditional automation attempts often fail because they expect predictability. Police accident reports defy that expectation: handwriting varies, diagrams get annotated, continuation sheets shift key details pages away, and checkbox labels change by state and revision. Doc Chat’s agents were built for this world. They do not rely on a fixed location for a field; they reason about meaning and context. As described in Nomad’s article Beyond Extraction, document intelligence at this level is about inference—not just pulling a value from a box. That is why the system remains reliable even when reports come in from new jurisdictions or when states revise their forms.

From Backlog to Blueprint: Standardizing SIU Best Practices

In many organizations, the most effective SIU workflows live in people’s heads. Doc Chat helps institutionalize that expertise. We turn your unwritten rules into repeatable steps. The output becomes the blueprint that new investigators follow on day one: the same liability summary layout, the same witness contact table, the same checklist for comparative negligence, and the same placement of statute references. This standardization reduces variance, accelerates onboarding, and safeguards knowledge as teams grow or transition.

Implementation Without Disruption

Adopting Doc Chat does not require a core system overhaul. Many teams start by dragging and dropping police accident reports and witness statements into a secure workspace to see live results in minutes. Once you are comfortable, Nomad’s team integrates Doc Chat into your claim platform, document management system, or SIU case system via modern APIs—typically within one to two weeks. From there, we tune the output to your subrogation and SIU templates and wire in queues so that every incoming police report is analyzed automatically and routed to the right team.

Security, Compliance, and Defensibility

SIU and subrogation work often precedes litigation. Doc Chat was designed with auditability at its core. Every answer includes a link back to the page and section where the information came from. That traceability strengthens the defensibility of your investigative work and helps ensure that regulatory, reinsurance, and internal compliance reviews go smoothly. Nomad maintains SOC 2 Type 2 certification and follows strict data governance controls so you retain custody and control of sensitive claim information.

Putting It All Together: A Day in the Life With Doc Chat

Consider a Commercial Auto rear-end crash outside a distribution center with competing narratives. The police accident report arrives alongside two witness statements and a supplemental diagram. Within moments of ingestion, Doc Chat:

1. Extracts identifiers, parties, vehicle data, and the officer narrative, and compiles a liability summary with citations to the report pages.

2. Interprets the diagram to confirm vehicle positions and the point of impact and aligns these with the narrative.

3. Flags a contradiction between the driver’s statement and a witness who notes the truck’s brake lights were not illuminated.

4. Identifies a citation issued to the claimant for following too closely and surfaces the statutory language reference from the report.

5. Compiles witness contact details and prompts the investigator to obtain nearby surveillance or dashcam footage given the commercial setting.

6. Populates the subrogation worksheet and a draft demand letter paragraph, including the adverse carrier name captured in the report.

With that foundation, the SIU investigator spends their time on outreach, verification, and strategy—not on manual reading and transcription. Multiply that by a daily volume of cases, and the operational impact becomes obvious.

The Competitive Edge: Faster Answers, Better Files, Stronger Recoveries

Claims organizations that deploy Doc Chat for police accident report processing see an immediate shift in how work gets done. Backlogs shrink, and investigators start their day with case files that are already summarized, cited, and interrogable. Instead of waiting on manual extraction, they move straight to decisive action: calling witnesses, contacting adverse carriers, lining up surveillance, or coordinating with counsel. This speed compounds; faster early actions often lead to cleaner negotiations and more confident positioning. As one claims leader put it, when every answer links to the page it came from, it is easier to be both fast and right.

How to Evaluate AI Tools for Police Accident Reports

Many SIU leaders are actively searching for AI to extract info from police reports for subrogation, but not all tools are created equal. When evaluating solutions, we recommend verifying:

- Scale: Can it ingest and analyze thousands of pages per file quickly without manual babysitting? Is performance consistent for large, multi-document packets?

- Variability tolerance: Does it handle multiple state forms, messy scans, and hand-annotated diagrams without brittle templates?

- Explainability: Are all outputs tied to page-level citations so investigators can trust and verify? Does it produce consistent, repeatable summaries?

- Workflow fit: Can the system populate your subrogation worksheet, demand letter templates, and SIU notes automatically? Does it support live Q&A?

- Implementation and support: Does the vendor provide white glove onboarding and a short time-to-value? Can you go from pilot to production in one to two weeks?

Doc Chat was built to check all of these boxes for Auto, Commercial Auto, and GL & Construction. It is why SIU investigators describe it as the best tool to automate accident report analysis and why subrogation teams call it a force multiplier.

Getting Started

You can start small: pick a representative batch of police accident reports, state crash forms, and witness statements; define the subrogation summary format you prefer; and let Doc Chat process the set. Most teams are live within two weeks, and many are productive on day one using a drag-and-drop workspace. When you are ready, integrate into your claim and SIU systems to automate triage and routing. See how quickly your team can automate subrogation with police report processing at Nomad Data Doc Chat for Insurance.

Conclusion

For SIU investigators and subrogation specialists working Auto, Commercial Auto, and General Liability & Construction claims, police accident reports represent both a necessity and a bottleneck. They are rich with the facts needed to recover—but extracting those facts manually is slow, inconsistent, and risky. Doc Chat by Nomad Data turns that bottleneck into a breakthrough by reading everything, summarizing consistently, and answering questions instantly with citations. The result is faster, more accurate liability analysis, earlier and stronger subrogation positioning, and fewer missed opportunities. With white glove service and a one-to-two-week implementation timeline, your team can move from backlog to blueprint and start converting police report complexity into recoveries—today.