Underwrite for frequency
When it may fit: More claims per policy.
Evidence needed: Frequency by segment and cause.
Trade-off: May reduce volume.
Insurance Intelligence Brief
How to Investigate Changes in Claims Frequency and Severity
Claims cost is frequency times severity. When it rises, knowing which of the two moved, and in which products, points to different causes and different remedies.
1. The business problem
Are there more claims, or are the claims bigger?
Claims incurred is the product of how many claims occur and how much each costs. Both can rise at once, and they have different drivers: frequency reflects exposure, behavior and weather, while severity reflects repair and medical costs, litigation and inflation.
Splitting the change into the two shows whether the problem is underwriting, claims handling or the environment.
2. What the evidence can reveal
A frequency and severity analysis includes:
- Calculated Claims per 100 policies, and average cost per claim, over time.
- Calculated The contribution of each to the change in claims cost.
- Calculated The same split by product, cause and region where available.
- Information gap Drivers behind each: weather, driving patterns, repair costs, medical inflation, legal environment and mix.
Frequency and severity compound: a 9% rise in one and a 7% rise in the other produce about a 17% rise in claims cost per policy.
3. Investigate the problem
In the synthetic insurer, Calculated claims frequency rose from 9.3 to 10.2 per 100 policies (9.5%), and average severity rose from $12,000 to $12,818 (6.8%). Together they raised claims cost per policy about 17% (1.095 times 1.068), well above the premium per policy increase of roughly 8% that the figures imply.
Calculated Both are costly in the scenario. A 1% rise in frequency lowers the underwriting result by about $623K and a 1% rise in severity by about $564K. A 1% rise in rate adds about $720K, so about 0.9% of rate offsets a 1% rise in frequency. The quarterly series shows frequency creeping up, from 2.3 per 100 policies in the first quarter of FY25 to 2.6 in the last quarter of FY26 (quarterly figures), and severity stepping up from $11,990 in the last quarter of FY25 to $12,860 in the first quarter of FY26.
Hypothesis A step in both frequency and severity at once suggests more than one cause, perhaps weather or loss-cost inflation alongside a change in the mix of risks. Information gap The demo does not split frequency and severity by product or cause. That split, together with claims by cause of loss, is the next piece of evidence to gather. Rate need should be set from loss-cost trends that consider both.
4. Explore the interactive experience
Investigate it yourself.
Insurance Portfolio Explorer: a portfolio dashboard with loss, expense and combined ratios, a scenario simulator for rate, volume, frequency and severity, evidence-linked answers from APIS, and a sample brief, all on synthetic data.
The experience below is built on a synthetic insurer, “Demo Mutual Insurance,” analyzed by product line. It uses no policyholder or claims data of any kind, and it has no distribution-channel data, so product lines are used to show the method. Every figure is illustrative.
- Click the Claims frequency card and then the Average claim severity card. Which moved more?
- In the Scenario tab, raise rate by 8%. Does it offset the rise in frequency and severity?
- Ask APIS how frequency and severity affect underwriting results.
5. Evaluate possible solutions
Responses differ for frequency and for severity.
6. What leadership should do next
Questions to answer
- How much of the claims cost increase is frequency and how much severity?
- Which products?
- What drives each?
- Is the trend continuing?
Data to gather
- Claim counts and costs by product and cause
- Exposure measures
- Rate history
- Loss-cost trend studies
Steps to take
- Split the change.
- Locate it by product.
- Choose rate or underwriting action.
- Monitor monthly.
7. Engage Two Pillars
Investigate Performance Across Your Insurance Business
Two Pillars can help carriers, agencies and brokerages investigate portfolio, claims operations, agency economics and process improvement using your own data. This demo uses no policyholder data. A good first step is a frequency-and-severity analysis that locates the claims cost increase by product and cause.
Sources and data notes
- The organization, its figures, and every number in this article and its interactive experience are synthetic and illustrative. They are not real data, a benchmark, or a forecast.
- Reviewed October 2026. This article describes an approach to investigation. It does not replace review by qualified professionals.