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Expected Loss Ratio

Expected loss ratio (ELR) method is a technique used to determine the projected amount of claims, relative to earned premiums. The expected loss ratio (ELR) method is used when an insurer lacks the appropriate past claims occurrence data to provide because of changes to its product offerings and when it lacks a large enough sample of data for long-tail product lines.

Definition: The Expected Loss Ratio (ELR) method is a technique used to determine the expected ratio of claim amounts to premiums received. It is particularly useful when an insurance company lacks adequate historical claims data due to product configuration changes or when dealing with long-tail product lines with insufficient data samples.

Origin: The ELR method originated in the insurance industry, especially when dealing with new products or long-tail product lines. As insurance products became more diverse and complex, traditional pricing methods based on historical data became less applicable, necessitating a new approach to estimate future claim amounts.

Categories and Characteristics: The ELR method mainly falls into two categories: industry data-based ELR and expert judgment-based ELR.

  • Industry Data-Based ELR: This method uses historical data and statistical models from the industry to estimate the expected loss ratio. Its advantage is a solid data foundation, but it may not fully apply to specific companies.
  • Expert Judgment-Based ELR: This method relies on the experience and judgment of experts to estimate the expected loss ratio. Its advantage is high flexibility and quick adaptation to new situations, but it is more subjective and may have biases.

Specific Cases:

  • Case 1: An insurance company launched a new health insurance product. Lacking historical data, they used the industry data-based ELR method. By analyzing industry data of similar products, they estimated the product's expected loss ratio to be 70%. This means they expect to pay 70 units in claims for every 100 units of premium received.
  • Case 2: Another insurance company entered a new market without local historical data. They invited several industry experts and used the expert judgment-based ELR method to estimate the market's expected loss ratio at 60%. This helped them reasonably price and manage risk in the absence of sufficient data.

Common Questions:

  • Question 1: How is the accuracy of the ELR method ensured?
    Answer: The accuracy of the ELR method depends on the quality of data and the experience of experts. Using multiple data sources and opinions from several experts can improve accuracy.
  • Question 2: Is the ELR method applicable to all insurance products?
    Answer: The ELR method is mainly suitable for new products and long-tail product lines lacking historical data. For products with rich historical data, traditional pricing methods may be more appropriate.

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