Hazards and Risks

Risk in Insurance

Two Meanings of Risk

  • In the insurance industry, "risk" has two specific meanings:
    • Probability of Loss: The potential for loss, damage, injury, or liability.
      • Example: "I am going to risk investing in that company."
    • Insured Item: The item being insured.
      • Example: "The insured risk is the house of a property owner."
  • Combining the terms: "ACME insurance is willing to risk insuring the risk."
    • First use: risk meaning the potential for financial loss.
    • Second use: risk defines it as the insured item.

Classification of Risk

  • Insurers classify risk into two categories:
    • Speculative Risk:
      • Cannot be insured.
      • Involves the possibility of both gain and loss.
      • Undertaken with uncertainty of outcome.
      • Examples: Buying a lottery ticket, investing in the stock market.
    • Pure Risk:
      • Can be insured.
      • Involves the possibility of loss or no loss, but no possibility of gain.
      • Does not violate the principle of indemnity.
      • Aligns with the principle of indemnity, which states that the insured should be restored to their approximate financial condition before the loss but cannot profit from it.

Pure Risks: Insured Entities

  • Insurers cover pure risks, which include:
    • Persons
    • Items
    • Organizations

Exposure

  • Exposure is an Insured item's openness, or vulnerability, to loss or damage.
    • Example: A house built on the Gulf Coast has high exposure to hurricane damage.
    • Example: A car in a high-crime area has high exposure to theft.
  • Insurers approximate a risk's exposure in units or dollars to determine the premium.

Underwriting

  • Insurers evaluate exposure to approximate the premium.
  • Underwriters determine the probability of loss using actuarial statistics.
  • The goal is for actual losses to match expected losses, allowing the insurer to protect insureds from catastrophic losses while operating at a profit.
  • Underwriters evaluate an applicant's risk and exposure to determine if they fit in a similar pool of insureds with an acceptable loss probability.
  • The underwriter may:
    • Reject the application protecting the insurer from unnecessary risk.
    • Accept it in exchange for a higher premium.

Hazard

  • A hazard is any circumstance that increases the chance of loss.
    • Can be physical, moral, or morale (to be covered later).
  • It is a physical or non-physical condition that directly or indirectly increases the likelihood or severity of a loss.
    • Example: Storing explosives in a basement.
    • Example: Hot tub increasing exposure to damage or liability.
    • Example: Flammable liquids stored in a closet.
  • Exposure: The possibility of loss expressed in dollars or units.
  • Hazard: A condition that may increase the exposure.

Peril

  • Peril is the actual cause of a loss.
    • Examples: Lightning, fire, theft, flood.
  • Another name for a covered peril is an insurable event.
  • Insurance policies protect against perils in two ways:
    • Named Peril Policy: Lists every peril that it covers.
    • All Peril Policy: Covers all causes of loss except those specifically excluded.

Loss

  • Loss occurs when the value of an insured item is reduced by a covered peril, or when expenses have to be paid because of an incident.
  • To an insurer, loss is the amount paid out after a claim has been settled.
    • Example: Dan wrecked his car and broke his wrist. The car's damage and Dan's medical bills are losses. The insurer indemnifies Dan, and the amount paid is the insurer's loss.

Summary of Terms

  • Risk:
    • Potential for financial loss.
    • The insured item.
  • Speculative Risk: Cannot be insured; involves the possibility of gain.
    • Examples: Gambling, investing in businesses, buying lottery tickets.
  • Pure Risk: Can be insured; involves only loss or no loss.
  • Exposure: Likelihood of being damaged or lost; vulnerability to damage.
  • Hazard: Increases the possibility of damage or loss; can be a condition or behavior.
    • Examples: Smoking, storing flammable materials, swimming pools, nearby rivers prone to flooding, or high crime neighborhoods.
  • Peril: Causes actual damage.
    • Examples: Lightning, hail, fire, vandals, hurricanes.
  • Loss: Reduction of value of insured items, expenses caused by a covered peril, and the amount paid to a policyholder making a claim.

Conditions for Insurability

  • Not everything is insurable; an item must meet certain conditions.

1. Collect Enough Income

  • Insurers must collect enough income from premiums to cover claims and operating costs.
  • Some catastrophes are too widespread for insurers to cover.
    • Example: Texas homeowners policies often exclude hurricane coverage because catastrophic losses make premiums unaffordable.
    • The Texas Windstorm Association provides state-subsidized hurricane coverage.

2. Define Conditions of Coverage, Precise Value, and Clear Terms

  • The insurer must be able to:
    • Define the exact conditions of coverage.
    • Know the precise dollar value of the risk.
    • Clearly set out the terms under which a claim would be paid.
  • Parameters must be exactly defined by description and value to be insurable.

3. Loss Must Be Unpredictable and Unpreventable

  • Loss must be unpredictable and caused by circumstances no one could reasonably prevent.
    • Examples: Roof blown off in a tornado, car accident, theft, fire caused by lightning.
  • Insurance protects against unforeseen, catastrophic events.

4. Loss Must Cause Substantial Economic Hardship

  • Loss must cause substantial economic hardship.
  • Insurance protects against loss the insured would be unable to easily recover from.

5. Ability to Exclude Catastrophic Disasters

  • Insurers must be able to exclude coverage for significantly catastrophic disasters to remain solvent.
  • Examples: Wars, nuclear missile attacks, earthquakes, and floods.
  • California earthquakes example: Many insurers exclude earthquake coverage due to the potential for hundreds of billions of dollars in damages.

6. Cover a Large Number of Similar Risks

  • Insurers must cover a large number of similar risks to spread the risk of loss and predict losses accurately.
  • Reliant on the law of large numbers.

Law of Large Numbers

  • The law of large numbers states that statistics are more accurate and predictable when a larger group of units is involved.
  • Example: Car thefts
    • If 10% of cars are stolen annually, insuring only 10 cars is risky due to potential for outliers.
    • Insuring 100,000 cars makes losses more predictable.
  • The larger the number of insured units, the more predictable the losses.
  • Coin flip example: Flipping a coin 1,000 times will result in a ratio of heads to tails much closer to 50/50 than flipping it only 10 times.

Adverse Selection

  • Adverse selection occurs when someone buys insurance based on their own knowledge of their likelihood to file a claim.
  • Often due to information about the risk that the insurer is unaware of or unable to discriminate against.
  • Examples:
    • Smokers being more motivated to purchase health insurance.
    • Healthy young people buying minimal health insurance, while high-risk people choose more extensive coverage.
  • To manage adverse selection:
    • Insurers may raise premium rates across the board.
    • Insurers can charge higher rates for individuals who exhibit certain risk factors, such as smoking.
  • Insurers take on risks that command reasonable premiums likely to cover claims and expenses.

Final Summary

  • Insurers must be able to state the conditions under which an item's loss or damage will be covered.
  • The item must be clearly describable and have a precise dollar value.
  • Loss must be reasonably unpreventable and cause real financial hardship.
  • Large-scale catastrophes can be excluded from coverage.
  • A large number of the same types of risks must be insured.