2.0 General Insurance Principles (risk Management Key Terms)

Question 1

Risk

Answer 1

Risk can be defined in different ways, depending on the context in which the word is used when used insurance risk means a chance of loss

The term risk is also sometimes used to refer to the person property or activity that is insured. For example, an insurer may refer to the insured under an auto insurance policy as a risk.

Question 2

Speculative risk

Answer 2

Can result in loss or gain a good example of speculative risk is investing in the stock market, stocks, increase or decrease in value over time, the stockholder may experience, a financial gain or loss of at the time the stock is sold.
speculative risk are generally uninsurable.

Question 3

Pure risk

Answer 3

Pure risk involved. Only the chance of a loss. game is not possible.purest include:

The possibility of loss of a home as a result of a fire

The possible death of a person

Question 4

In general what risks are insurable?

Answer 4

Only pure risks

Question 5

Hazard

Answer 5

A hazard is something that does not directly cause a loss but increases the likelihood that a loss will occur. It’s essentially a factor or condition that makes a loss more probable or likely. Hazards can be categorized into:

Physical Hazards: Conditions physically present that increase the chance of loss, such as poor maintenance or dangerous environments.
Moral Hazards: Relate to a person’s dishonest tendencies, such as filing fraudulent claims.
Morale Hazards: Arise from a person’s careless or indifferent attitudes towards risk, like leaving doors unlocked or reckless driving.
Important note:
Hazards themselves do NOT directly cause loss; they merely increase the probability or likelihood that a loss will occur.

Question 6

Peril (cause of loss)

Answer 6

A peril is explicitly the cause of loss itself, and it differs from a hazard.
Peril = The direct cause of loss (examples include fire, explosion, windstorm).
Hazard ≠ Peril. Instead, a hazard simply increases the probability that a loss due to a peril will occur.

Question 7

Loss

Answer 7

Losses can be categorized as either direct or indirect.

Direct Loss:
Defined as the immediate result of an event caused directly by a covered peril.
Example: Fire damages a house. The destruction or physical damage itself is the direct loss.
Indirect Loss (also called Consequential Loss):
Refers to the secondary consequences or expenses resulting from the initial (direct) loss.
Example provided: If a home is severely damaged by fire (direct loss), the homeowner might incur additional expenses such as temporary housing or renting a car during repair. These additional expenses constitute an indirect loss, directly resulting from the covered peril (fire).
Important Points:
An insurance policy generally provides protection for direct losses caused by specific covered perils.
Indirect losses must be directly connected to the direct loss, typically involving additional expenses that would not have occurred without the initial damage.
Example from your document:
If a home with a poorly maintained furnace (hazard) catches fire (peril), the immediate physical damage to the house is a direct loss. The homeowner’s subsequent living expenses (such as temporary accommodation or a rental car) while the home is repaired represent an indirect loss.

Understanding these distinctions ensures clarity about coverage when filing insurance claims, and clarifies the scope of protection provided by insurance policies.

Question 8

Example of perils

Answer 8

Examples of Perils:

Fire
Explosion
Windstorm

Question 9

Law of Large numbers

The Law of Large Numbers is a statistical concept fundamental to insurance, stating that the larger the group of insured individuals or exposure units, the more accurately losses can be predicted.
It involves using historical loss statistics and probabilities to predict future losses accurately. This allows insurers to estimate the number and size of future losses effectively.

Answer 9

How It Works:
Insurance relies heavily on statistical probability.
Predictions are made based on past loss data from a large group of similar risks or exposure units (people, homes, cars, etc.).
When the size of this group increases, predictions about future losses become more accurate.
Example from your document:
An actuary using loss data from only 10 similar homes would not have enough data to confidently predict future losses accurately.
However, if loss statistics from 10,000 similar homes are available, predictions about losses become significantly more reliable and accurate.
Important Principle:
To apply the law, a risk must be part of a large group of similar risks.
Larger groups mean more accurate predictions.
Accurate loss predictions help insurers set appropriate premiums and remain financially stable, benefiting both insurance providers and consumers.