2025 Frequency-Severity Method Explained: How Insurers Calculate Claim Costs and Frequencies
Discover the 2025 frequency-severity method, an essential actuarial technique insurers use to estimate the expected number and cost of claims over time, helping them manage risk effectively.
Julia Kagan is a seasoned financial and consumer journalist with extensive experience in personal finance editorial roles at Investopedia.
What Is the Frequency-Severity Method in Insurance?
The frequency-severity method is a key actuarial approach used by insurers to forecast the expected number of claims and the average cost per claim within a specific timeframe.
This method relies on analyzing historical claim data to estimate both the average claim frequency and severity, then multiplying these figures to project total expected losses.
Breaking Down the Frequency-Severity Method
Within this method, frequency refers to how many claims an insurer anticipates during a certain period. A higher frequency indicates more claims are expected.
Severity measures the average cost associated with each claim. High-severity claims are costlier than average, while low-severity claims cost less.
Key Insights
- The frequency-severity method helps insurers estimate claim counts and average claim costs for effective risk management.
- Frequency quantifies the expected number of claims over time.
- Severity assesses the financial impact per claim.
- Insurers integrate this method into broader predictive models to set premiums and reserves.
For example, a prospective buyer of a Miami beach house should consider that the Florida coast experiences about one hurricane annually. Due to the high frequency and severity of potential hurricane damage, the frequency-severity method would likely discourage insurers from underwriting policies for such high-risk properties.
How the Frequency-Severity Method Fits Into Risk Modeling
Insurance companies employ advanced models to estimate claim likelihood and costs, aiming to balance premium income with claim payouts. While ideally insurers prefer collecting premiums without claims, realistic models like frequency-severity provide accurate forecasts to maintain financial stability.
This method uses long-term historical averages, making it less sensitive to short-term fluctuations but also slower to react to sudden changes, such as increased flood claim severity due to rising water levels.
By combining claim frequency and severity data, insurers can better price policies and prepare reserves, ensuring they remain solvent while offering competitive coverage.
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