Claims frequency

What Is Claims Frequency?

Claims frequency, within the realm of actuarial science and insurance, refers to the number of claims filed over a specific period relative to a given unit of exposure. It is a critical insurance metric that helps insurers understand the likelihood of an insured event occurring. Essentially, claims frequency measures how often claims happen. A higher claims frequency indicates that insured events are occurring more often, which can significantly impact an insurer's risk management strategies and profitability. Understanding claims frequency is fundamental for accurate premium pricing and for assessing the overall risk profile of a portfolio of insurance policies.

History and Origin

The concept of analyzing claims to predict future losses is deeply rooted in the history of actuarial science. Early forms of risk assessment and the rudimentary beginnings of insurance can be traced back thousands of years to ancient civilizations. However, the systematic application of mathematical and statistical methods to quantify risk and predict future events, including claims frequency, truly began to formalize in the 17th century. Pioneers like John Graunt and Edmond Halley, through their groundbreaking work on mortality tables, laid the groundwork for understanding the patterns of life and death, which could then be applied to early life insurance products.²¹, ²², ²³, ²⁴, ²⁵

The formalization of actuarial practices, which inherently involved calculating claims frequency to set fair premiums, gained momentum with the establishment of institutions like the Equitable Life Assurance Society in 1762.¹⁹, ²⁰ Over centuries, as the insurance industry evolved and collected more data, the methodologies for analyzing and predicting claims frequency became increasingly sophisticated, moving from simple averages to complex statistical models.¹⁶, ¹⁷, ¹⁸

Key Takeaways

• Claims frequency is a core measure in insurance, indicating how often insured events lead to claims.
• It is calculated by dividing the total number of claims by the total exposure units over a specific period.
• A rise in claims frequency can signal increased risk, potentially leading to higher insurance premiums.
• Insurers use claims frequency to inform underwriting, pricing, and reserving decisions.
• External factors like economic conditions, weather events, and regulatory changes can significantly influence claims frequency.

Formula and Calculation

The formula for claims frequency is straightforward: it is the total number of claims observed within a specific period divided by the total exposure units during that same period.

The formula is expressed as:

Where:

• Number of Claims: The total count of claims filed or reported during the period.
• Number of Exposure Units: The measure of risk exposure, which can vary depending on the type of insurance. For example, in auto insurance, it might be the number of insured vehicles, vehicle years, or policy years. For homeowners insurance, it might be the number of insured homes.

For instance, if an insurer has 100,000 insured vehicles (exposure units) in a year and processes 5,000 claims, the claims frequency would be:

This translates to an average of 0.05 claims for every insured vehicle in that year.

Interpreting Claims Frequency

Interpreting claims frequency involves understanding its context and looking for trends and patterns. A claims frequency of 0.05, as in the example above, means that for every 100 policyholders, approximately 5 claims are expected to occur. Insurers meticulously track this metric over time to identify shifts in risk. An increasing claims frequency might indicate worsening risk conditions, such as more accidents, a rise in severe weather events, or an increase in property damage incidents. Conversely, a decreasing claims frequency could suggest improved safety measures, reduced risk exposure, or favorable external conditions.¹⁵

For example, in homeowners insurance, claims frequency for property damage due to wind or hail might be about one in 35 insured homes annually, while for theft it could be one in 700.¹⁴ These benchmarks allow insurers to evaluate their own portfolio's performance against industry averages and adjust their risk models accordingly. Actuaries also analyze claims frequency by various demographic factors or geographical locations to pinpoint high-risk segments.¹³

Hypothetical Example

Consider "SafeDrive Insurance," an auto insurance provider. In 2023, SafeDrive insured 500,000 vehicles. During that year, they processed a total of 20,000 claims for various incidents, including collisions, comprehensive losses, and bodily injury.

To calculate SafeDrive's claims frequency for 2023:

1. Identify the Number of Claims: 20,000
2. Identify the Number of Exposure Units: 500,000 insured vehicles
3. Apply the Formula: $$\text{Claims Frequency} = \frac{20,000 \text{ claims}}{500,000 \text{ vehicles}} = 0.04 \text{ claims per vehicle}$$

This means that, on average, SafeDrive experienced 0.04 claims for every vehicle they insured in 2023. This figure is vital for SafeDrive's underwriting process for 2024. If industry trends or internal analysis suggest this frequency is rising, SafeDrive may need to adjust its rates or risk selection criteria to maintain profitability.

Practical Applications

Claims frequency is a cornerstone of the insurance business, with wide-ranging practical applications across various lines of coverage and financial analysis:

• Premium Calculation: Actuaries rely on historical claims frequency data to predict future claims, which is a primary component in determining the appropriate premiums to charge. A higher expected claims frequency for a particular risk profile or geographical area will typically result in higher premiums.
• Risk Assessment: Insurers use claims frequency to assess the overall risk of an individual policyholder or an entire portfolio. For instance, in auto insurance, data shows that claim frequency and severity for electric vehicles (EVs) have been higher than traditional internal combustion engine (ICE) vehicles, leading insurers to adjust their risk assessments for EVs.¹²
• Underwriting Decisions: Underwriters use claims frequency analysis to decide whether to offer coverage, and if so, at what terms. High-frequency risks might be declined or priced significantly higher.
• Product Development: Understanding claims frequency patterns helps insurers design new products or modify existing ones to better meet market needs and manage profitability.
• Regulatory Oversight: Regulatory bodies, such as the National Association of Insurance Commissioners (NAIC), collect and analyze claims frequency data to monitor market conditions, ensure fair practices, and assess the solvency of insurance companies. The NAIC's comprehensive reports provide insights into factors driving insurance costs, including claims frequency.¹⁰, ¹¹
• Economic Analysis: Broader economic trends can influence claims frequency. For example, during periods of economic downturn, certain types of claims, such as those related to unemployment insurance, may see a significant increase. The Federal Reserve Bank of St. Louis, for instance, provides data on initial unemployment claims as a key economic indicator.⁹

Limitations and Criticisms

While claims frequency is a vital metric, it has limitations. One significant criticism is that it does not account for the severity or financial cost of each claim. A low claims frequency with a high average claim cost could be more detrimental to an insurer than a high claims frequency with very low average costs. This is why it is almost always analyzed in conjunction with claims severity to understand the complete picture of total loss costs.

Another limitation is that claims frequency models often assume that frequency and severity are independent, which may not always be true in real-world scenarios.⁸ Furthermore, historical claims frequency data, while informative, may not always accurately predict future trends due to unforeseen circumstances, changes in laws, technological advancements, or sudden shifts in economic conditions. For example, the COVID-19 pandemic significantly impacted auto claims frequency, causing it to plummet initially before rebounding.⁷

The accuracy of claims frequency analysis can also be affected by data quality, including underreporting of minor incidents or delays in claim processing. Factors like inflation can also distort the interpretation of trends if not properly accounted for, as rising costs for repairs or medical expenses can influence insurer profitability even if claims frequency remains stable.⁶ The development of advanced predictive analytics and machine learning models aims to overcome some of these limitations by capturing more complex relationships within claims data.³, ⁴, ⁵

Claims Frequency vs. Claims Severity

Claims frequency and claims severity are two distinct but complementary metrics crucial in actuarial modeling. Claims frequency, as discussed, measures how often claims occur (e.g., number of claims per policy or per unit of exposure). It focuses on the count of incidents.

In contrast, claims severity measures the average cost of each claim. It quantifies the financial impact of each individual claim. For example, if an insurer pays out $500,000 across 100 claims, the average claims severity is $5,000 per claim.

The confusion between the two often arises because both contribute directly to an insurer's total losses. While a high claims frequency means many small incidents, a high claims severity means fewer, but more expensive, incidents. Both can significantly impact an insurer's profitability and require different strategic responses. Actuaries typically model these two components separately and then combine them to forecast total losses for financial planning and risk assessment.

FAQs

What factors can increase claims frequency?

Several factors can increase claims frequency, including changes in driving habits, an increase in natural disasters, rising crime rates (leading to more theft claims), stricter regulations that make it easier to file claims, or even an economic downturn that might lead to more fraudulent claims.²

How do insurers use claims frequency?

Insurers primarily use claims frequency to assess risk, calculate premiums, and manage their reserves. It helps them understand the likelihood of future losses and set appropriate pricing to remain solvent and profitable. It's a key input in loss ratio calculations.

Is a high claims frequency always bad for an insurer?

Not necessarily. While a high claims frequency generally indicates more frequent incidents, the financial impact depends heavily on the claims severity. Many low-cost claims might be less damaging than a few very expensive ones. Insurers analyze both metrics through statistical analysis to get a complete picture.

How does technology impact claims frequency?

Technology can have a dual impact. Features like advanced driver-assistance systems (ADAS) in cars or smart home devices can reduce claims frequency by preventing accidents or detecting issues early. However, the increased cost of repairing these complex systems can lead to higher claims severity, even if the frequency decreases.¹