What Is a Loss Run Report?
A loss run report is a document produced by an insurance company that details the history of claims made on a specific insurance policy or group of policies. This report summarizes each claim, including the date of the incident, the type of loss, the amount paid out, and any reserves that remain outstanding. By providing a historical account, loss run reports allow stakeholders to track how claims and losses have accumulated over the policy period or across multiple renewals.
These reports are most commonly used in commercial insurance lines such as general liability, workers’ compensation, property, and commercial auto. Insurers, policyholders, and brokers use loss run reports to assess risk exposure, evaluate coverage adequacy, and determine appropriate premium levels. In the context of policy renewal or when seeking new coverage, an accurate loss run report is essential for demonstrating loss history and influencing negotiation outcomes.
This is part of a series of articles about insurance claims processing
Importance of Loss Run Reports.
For Policyholders
For policyholders, loss run reports are valuable for demonstrating their risk profile to current or prospective insurers. These documents offer a transparent summary of claim activity, which can help in negotiations for better rates or improved policy terms. A favorable report showing low frequency or low severity of losses can build trust with insurers, streamline the renewal process, and support requests for policy modifications.
Additionally, reviewing a loss run report provides policyholders with insights into their operational risks. Identifying recurring types or causes of claims allows businesses to implement targeted risk management initiatives, improve workplace safety, or refine operational practices. Regularly assessing loss run data can translate into cost savings through fewer claims, reduced premiums, and enhanced insurability in competitive markets.
For Underwriters
For underwriters, loss run reports provide a clear picture of a potential or current client’s loss experience, enabling accurate risk assessment and sound underwriting decisions. Reviewing a loss run reveals trends in claim frequency, severity, and the policyholder's risk mitigation practices. Underwriters use this data to determine the likelihood of future claims and decide whether to issue, renew, or decline coverage.
Beyond policy acceptance, these reports also shape pricing decisions. Underwriters analyze open versus closed claims, large or frequent losses, and patterns that may indicate emerging exposures. This information informs both the selection of appropriate coverage limits and the application of exclusions or risk management requirements. Loss run reports thus serve as a critical risk evaluation and pricing input in every underwriting workflow.
For Brokers
Brokers use loss run reports extensively in their role as intermediaries between clients and insurers. Access to detailed claims history allows brokers to represent their clients’ risk profiles accurately when marketing policies, negotiating terms, or performing due diligence with new insurers. A thorough loss run helps brokers anticipate insurer concerns and address them, improving the likelihood of favorable placements and renewals.
Brokers also use loss run reports to advise clients on risk management and claims best practices. By identifying loss trends or problematic claim patterns, brokers can propose solutions to reduce future exposures and enhance insurability. The ability to interpret and communicate the implications of loss runs increases a broker’s value, ensuring the client receives both competitive terms and strategic risk guidance.
What Information Is Included in a Loss Run Report?
A loss run report typically includes the following data elements for each reported claim:
Policy information
This section identifies the policy number, coverage type (e.g., general liability, workers’ compensation), and policy period. It confirms the time frame over which the claims were incurred.
Claim details
Each claim entry lists the claim number, date of loss, and a brief description of the incident. This information helps identify the nature of each claim and its timing in relation to the policy period.
Financial summary
The report specifies key financial figures, including total paid, total reserved (estimated future payments), and total incurred (paid plus reserved). These figures provide a snapshot of both past payouts and expected future liabilities.
Claim status
The report indicates whether each claim is open, closed, or pending. This status helps underwriters and policyholders understand if liabilities are still developing.
Loss categorization
Some reports include a breakdown by loss type (e.g., property damage, bodily injury, medical payments) and may include cause-of-loss codes. This categorization allows users to identify patterns and assess loss sources.
Loss history summary
Many reports include a summary section showing aggregate claims data for the policy term or multiple years, which aids in trend analysis and risk evaluation.
Types of Insurance Policies That Use Loss Runs
Loss runs appear in several types of commercial insurance. They help insurers review past claims and evaluate future risk. The format is similar across policies, but the details vary by line of coverage.
Commercial general liability: These reports show bodily injury and property damage claims. They help underwriters check patterns such as repeat slip and fall claims or frequent property damage incidents.
Commercial property: Loss runs list events such as fire, water damage, or theft. They show how often losses occur and whether the insured maintains buildings and equipment.
Workers’ compensation: Reports include injury dates, claim status, paid amounts, and reserves. They help assess workplace safety and the cost of employee injuries.
Commercial auto: Loss runs show collisions, liability claims, and physical damage events. Underwriters review driver behavior, accident frequency, and repair costs.
Professional liability: These reports summarize allegations of errors or omissions. They help insurers understand legal exposures and the severity of past disputes.
Cyber insurance: Loss runs capture security incidents, data breaches, and system outages. Insurers use them to assess vulnerabilities and the cost of past cyber events.
Requesting a Loss Run Report
To request a loss run report, policyholders or their authorized brokers must contact the current or prior insurer. Most insurers accept requests via email, customer portals, or standardized forms.
A few important things to know when requesting loss run reports:
The request should include the policyholder’s name, policy number(s), coverage types, and the time frame for which the loss history is needed.
For businesses with long coverage histories or multiple policies, specify the full period of coverage across all applicable lines.
In the US, many states require insurers to provide loss run reports within a fixed time frame, commonly 10 to 15 business days, after receiving a written request. Some jurisdictions impose penalties on insurers that fail to comply.
To avoid delays, it's important to verify the insurer’s specific request procedure and ensure the request includes all required information.
Automating Loss Run Report Analysis with AI
Manual loss run analysis is time-consuming, error-prone, and expensive. Insurance professionals often spend hours parsing inconsistent, multi-format documents just to extract basic data. AI-powered tools streamline this process by automating extraction, normalization, and analysis, transforming a slow task into an efficient, scalable workflow:
The first step in automation is converting PDFs or scanned documents into machine-readable text using optical character recognition (OCR). AI then applies natural language processing (NLP) to identify key data points—such as claim dates, paid amounts, reserves, and causes of loss—and maps inconsistent terminology from different carriers to a standardized format. This allows underwriters and brokers to compare loss histories across multiple insurers without manual translation.
Once data is structured, machine learning models can detect patterns, group related claims, and flag anomalies, like a sudden spike in frequency or repeated losses just under the deductible. This pattern recognition helps uncover hidden risks or emerging trends that manual reviews might miss. Automated tools can also generate summaries and dashboards in real time, providing instant insights into loss patterns, historical trends, or portfolio-wide exposure.
Some platforms, like Kolena, allow insurance teams to configure AI workflows without writing code. Users can instruct the AI in plain language to extract and summarize specific fields, then refine the output through feedback. This adaptability is critical when working with diverse formats from different carriers. Once set up, the AI continuously improves with usage and can scale to handle hundreds of reports in minutes.
In practice, these AI systems can reduce review cycles from days to hours, or even minutes, while improving accuracy. This not only accelerates underwriting and quoting but also frees staff from repetitive tasks, reduces operational costs, and supports more informed decision-making. As AI adoption grows, insurers and brokers gain a strategic edge by turning loss run data into fast, actionable intelligence.
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How to Transform Your Run Loss Analysis Process with AI
For Underwriters
Automate data extraction and standardization. AI tools can ingest loss-run reports in varied formats, whether scanned PDFs, Excel sheets, or mixed-carrier documents, and automatically extract claim details (dates, amounts paid/reserved, status, cause codes, etc.). Data gets normalized into a consistent structure, removing the manual burden of reconciling different insurer formats.
Enable rapid, scalable loss history review. Rather than spending hours or days manually reading and entering data, AI can process hundreds of pages in minutes, producing ready-for-analysis loss history. This speed helps underwriters handle more submissions, avoid bottlenecks, and respond faster with quotes.
Spot patterns, anomalies and emerging risk trends. Once data is structured, machine-learning models, often part of AI platforms, can identify repeated losses, clusters of small claims, frequency spikes, or other outliers that may signal higher future risk. This supports more informed underwriting: selecting risk, pricing appropriately and setting reserves or coverage limits with greater confidence.
Integrate seamlessly with underwriting workflows. Modern AI-powered loss run tools often plug directly into underwriting platforms or agency management systems, enabling automatic import of cleaned data into policy-evaluation workflows, including quoting, risk scoring, and portfolio analysis. This reduces duplication of effort and helps maintain consistency across underwriting, actuarial, and risk management teams.
For Brokers
Speed up submissions and placement. For brokers handling multiple clients and carriers, AI-driven loss‐run automation slashes the time needed to compile loss histories, enabling quicker submissions to insurers or underwriters.
Produce polished, standardized reports for clients and insurers. Instead of sharing raw PDFs from carriers, brokers can deliver structured and uniform summaries: clean data tables, loss history dashboards, trend analysis, and even narrative summaries, reducing back-and-forth with underwriters and accelerating negotiations.
Advise clients with data-driven risk management insights. Because AI highlights patterns (for example, recurring small claims or claim concentrations) brokers can provide actionable guidance to clients: implement safety improvements, adjust operations, or refine coverage requests before renewal.
Maintain audit trails and compliance with ease. Many AI-powered systems include human-in-the-loop review and validation, producing traceable data extractions and consistent formatting, helping brokers meet regulatory or underwriting documentation requirements while reducing clerical errors.
AI Automation for Loss Run Report Analysis with Kolena
Kolena’s Loss Run Analysis workflow takes carrier PDFs and runs them through a proven AI pipeline: it ingests loss run reports from any carrier, standardizes the layout, and extracts the fields underwriters actually care about—claim counts, incurred losses, reserves, dates of loss, locations, and causes of loss. The output is a clean, consistent spreadsheet that drops straight into existing pricing models, with no change to how underwriters price risk.
Because loss run reports touch almost every commercial renewal, automating this step is high leverage. In production deployments, Kolena’s customers have seen massive time savings from loss run analysis alone, simply by turning a mechanical, repeatable task into an AI workflow that runs in the background. Underwriters go from chasing formats and totals to working with reliable, standardized inputs on day one of the renewal—freeing up hours for actual risk analysis and broker conversations instead of data cleanup.
Kolena also offers a free loss run workflow so teams can experience the process on a single file: upload a loss run report, and in minutes you receive an underwriting-ready spreadsheet with the key fields already extracted and aligned. It’s a simple way to see how AI can remove the bottlenecks around loss run reports before you roll the full platform out across your entire book.