Large number of similar exposure units: Since insurance operates through pooling resources, the majority of insurance policies are provided for individual members of large classes, allowing insurers to benefit from the law of large numbers in which predicted losses are similar to the actual losses. Exceptions include Lloyd's of London, which is famous for ensuring the life or health of actors, sports figures, and other famous individuals. However, all exposures will have particular differences, which may lead to different premium rates.
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In July 2007, The Federal Trade Commission (FTC) released a report presenting the results of a study concerning credit-based insurance scores in automobile insurance. The study found that these scores are effective predictors of risk. It also showed that African-Americans and Hispanics are substantially overrepresented in the lowest credit scores, and substantially underrepresented in the highest, while Caucasians and Asians are more evenly spread across the scores. The credit scores were also found to predict risk within each of the ethnic groups, leading the FTC to conclude that the scoring models are not solely proxies for redlining. The FTC indicated little data was available to evaluate benefit of insurance scores to consumers. The report was disputed by representatives of the Consumer Federation of America, the National Fair Housing Alliance, the National Consumer Law Center, and the Center for Economic Justice, for relying on data provided by the insurance industry.
Insurable interest – the insured typically must directly suffer from the loss. Insurable interest must exist whether property insurance or insurance on a person is involved. The concept requires that the insured have a "stake" in the loss or damage to the life or property insured. What that "stake" is will be determined by the kind of insurance involved and the nature of the property ownership or relationship between the persons. The requirement of an insurable interest is what distinguishes insurance from gambling.