Underwriters live and breathe risk evaluation, but even seasoned pros struggle with one key document: the loss run report. These reports are often messy, inconsistent, and painfully manual to process. If you’ve ever received a 200-page PDF filled with cryptic tables from five different carriers, you’re not alone.

This guide breaks down everything you need to know to make sense of loss runs quickly, accurately, and efficiently. You’ll be able to make confident underwriting decisions without wasting hours on data wrangling.

What Is a Loss Run Report?

A loss run is a report provided by an insurer that shows the claims history on a specific policy over a set time. It usually includes:

• Policy Information: Policy number, type, and term.

• Claim Details: Date of loss, date reported, type of claim, and incident description.

• Financials: Amounts paid to date, reserve amounts for future costs, and total incurred losses.

• Claim Status: Open, closed, or pending.

• Additional Notes: Any relevant comments or notes on the incident.

Different carriers may use varied formats and terminologies, making comparisons challenging.

Why Do Loss Runs Matter in Underwriting?

Loss runs provide a factual account of an insured's claims history, offering insights into:

• Risk Assessment: Evaluating the frequency and severity of past claims helps in predicting future risks.

• Behavioral Patterns: Identifying recurring issues can indicate underlying problems in risk management practices.

• Fraud Indicators: Unusual patterns or inconsistencies may signal potential fraudulent activities.

• Operational Insights: Understanding the nature and causes of claims can inform recommendations for risk mitigation.

However, inconsistent formatting and lack of standardization often hinder effective analysis. A structured approach is essential to leverage the full value of loss run reports.

How to Analyze a Loss Run Report

1. Gather Comprehensive Loss Runs

Collect complete loss run reports from all relevant insurers, ideally covering the past 3 to 5 years. Ensure there are no gaps, as missing data can distort the risk profile.

2. Normalize the Data

Standardize the formatting across different carriers. Focus on key fields such as date of loss, line of business, claim amounts, status, and descriptions. This step is crucial for accurate comparisons and analysis.

3. Identify High-Severity and High-Frequency Claims

Spot claims that occur frequently or have high costs. Look for patterns in claim types, timing, and recurrence. For instance, multiple injuries at a single location or repeated weather-related damages may indicate specific risk areas.

4. Calculate Loss Ratios and Trends

Determine the loss ratio by dividing total losses (paid and reserved amounts) by the earned premium. Analyze this ratio over multiple years to identify trends, whether improving or deteriorating.

5. Detect Anomalies or Gaps

Look for unexplained spikes in reserves, large claims that remain open for extended periods, or missing data. Such anomalies may signal risk mismanagement or potential concealment.

Advanced Techniques

Once the basics are mastered, delve deeper with these techniques:

• Multi-Year Trend Analysis: Identify cyclical risks and changes in claim frequency over time.

• Outlier Identification: Flag unusually large or atypical claims and investigate their causes.

• Benchmarking: Compare claim metrics to industry norms, such as average loss ratios.

• Predictive Forecasting: Use historical patterns to anticipate future loss activity or pricing needs.

Manual analysis can be tedious and error-prone. Leveraging automation tools, especially those with machine learning capabilities, can expedite the process and enhance accuracy.

Turning Analysis into Action

The true value of loss run analysis lies in applying the insights gained:

• Adjust Premium Pricing: Align premiums with actual risk exposure.

• Flag High-Risk Accounts: Identify accounts with persistent red flags for further review.

• Recommend Risk Control Measures: Suggest improvements based on identified loss types.

• Strengthen Negotiations: Use historical data to build compelling cases with brokers.

For organizations handling numerous submissions annually, automating this process not only saves time but also enhances underwriting accuracy.

Analyze Loss Runs with AI

Simply upload your loss runs to Ferofill and get comprehensive analytics in seconds. Our AI is trained across 1000+ carrier formats. It can extract key information and provide actionable insights right away. It can identify claim patterns, red flags and coverages that are driving losses.