Hazard types and the law of large numbers

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Hazards increase loss potential

A peril is a cause of loss, such as fire. A hazard increases the likelihood or severity of loss, such as frayed wiring.

  • Physical hazard: a tangible condition, such as an icy walkway or defective wiring.
  • Moral hazard: dishonesty, such as deliberately burning property for insurance proceeds or knowingly inflating a claim.
  • Morale hazard: carelessness or indifference toward loss, often because insurance provides a sense of protection. Leaving an insured bicycle unlocked through indifference is not the same as staging its theft.

Classify the fact being tested. A broken stair is physical; inventing an injury claim is moral; ignoring precautions because insurance will pay is morale. One setting can contain several hazards. Carelessness alone does not establish dishonest intent.

The law of large numbers

With many similar, sufficiently independent exposures, actual average loss experience tends toward the expected average. Group averages become more predictable even though an individual's next loss remains uncertain.

Three boxes distinguish physical hazards, meaning tangible conditions, moral hazards, meaning dishonesty, and morale hazards, meaning indifference. All increase loss likelihood or severity. A separate pooling relationship shows that more similar, sufficiently independent exposures make average loss experience more predictable, while individual outcomes remain uncertain.
Hazard types explain loss potential; suitable pooling improves prediction of averages.

Imagine a small pool and a much larger pool of comparable exposures. Random variation generally has less effect on the average in the larger pool. The law does not guarantee an exact number of claims or eliminate losses.

If ten thousand comparable exposures each have expected annual losses of one hundred dollars, expected total losses are one million dollars. This is an estimate, not a guaranteed payout or a complete premium calculation. Premiums also reflect expenses and other pricing factors.

Pool quality matters

Large numbers alone do not solve every problem. A catastrophe may strike many properties together, correlating their losses. Adding properties exposed to the same catastrophe does not create independence. Relevant data and comparable exposures remain essential.

Hazard classification explains what increases loss potential. Pooling explains why the average experience of a suitable group can be more predictable than an individual outcome.

Key terms

Sample questions

Which statement defines a hazard?

  • The dollar amount paid after a loss
  • The event that directly causes a loss
  • A guarantee that a loss will occur
  • A condition that increases the likelihood or severity of loss
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