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📊 '''Experience data''' refers to the historical records of [[Definition:Loss | losses]], [[Definition:Premium | premiums]], [[Definition:Claim | claims]], and other statistical information that an [[Definition:Insurance carrier | insurer]] or [[Definition:Reinsurer | reinsurer]] collects over time to evaluate the performance of a specific book of business, policyholder, or class of risk. Unlike broader [[Definition:Actuarial data | actuarial data]] drawn from industry-wide tables, experience data is specific to a particular account, program, or portfolio, making it an essential ingredient in [[Definition:Underwriting | underwriting]] decisions and [[Definition:Rate-making | rate-making]] exercises.

⚙️ Insurers compile experience data by aggregating information across policy periods — typically three to five years — to smooth out anomalies and reveal underlying trends. The data usually includes earned premiums, incurred losses, [[Definition:Loss adjustment expense (LAE) | loss adjustment expenses]], claim counts, and [[Definition:Loss ratio (L/R) | loss ratios]]. [[Definition:Actuary | Actuaries]] and underwriters analyze this information to determine whether a risk is performing better or worse than expected, which directly feeds into renewal pricing, [[Definition:Experience modification | experience modification]] factors, and decisions about policy terms and [[Definition:Deductible | deductible]] structures. In [[Definition:Reinsurance | reinsurance]], [[Definition:Ceding company | ceding companies]] provide experience data to reinsurers during treaty negotiations so that both parties can assess the adequacy of proposed [[Definition:Reinsurance rate | rates]].

💡 Reliable experience data is the backbone of credible pricing. Without it, underwriters are forced to rely on proxy benchmarks or manual judgment, which introduces uncertainty and the potential for adverse outcomes. As [[Definition:Insurtech | insurtech]] platforms and advanced [[Definition:Data analytics | data analytics]] tools become more prevalent, companies can now capture and structure experience data more granularly — segmenting it by geography, line of business, or coverage trigger — enabling more responsive and accurate portfolio management. Regulatory bodies also increasingly expect carriers to demonstrate that their pricing is supported by robust experience data, reinforcing its central role in both sound actuarial practice and [[Definition:Regulatory compliance | compliance]].

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Experience modification]]
* [[Definition:Loss ratio (L/R)]]
* [[Definition:Actuarial analysis]]
* [[Definition:Rate-making]]
* [[Definition:Loss development]]
* [[Definition:Underwriting performance]]
{{Div col end}}

Definition:Experience data - Revision history

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