Chapter 1 – Risk, Risk Management, and Insurance

Introduction

When faced with the possibility of a loss, it is important to begin by understanding exactly what risk exposures are involved how the losses might occur, and how these losses might be prevented or reduced before deciding to insure against them
First Principle: Law of Large Numbers explains how insurers can figure out how much to charge different classes of insureds.
Second Principle: AN insurance policy is a contract. The insurance industry holds 7.5% of the assets of the 22 industries in Canada while having some 14% of the operating profit margin. It employs more than 230,000 people.

Risk

Risk Management is the process of dealing with the consequences of being wrong and it should concentrate on either limiting the size of the bet or on finding ways to hedge the bet so you are not wiped out if you take the wrong side
Risk is defined as an uncertainty about the occurrence of a loss – if there is uncertainty about a loss, there is a risk and, conversely, if a loss in a given situation is a certainty, then there is no risk sine the loss is a sure thing
Exclusion – If the insured has diabetes, a life insurance policy might be prepared to excluded complication arising from this disease
Premature death – A smoker’s policy may be declined life insurance or will charge a higher premium to reflect the increase risk for early demise

Exogenous and Endogenous Risks

Exogenous Risks are risks over which we have no control and which are not affected by our actions – example: earthquakes or hurricanes
Endogenous Risks are risks that are dependent on our actions. Example: Smoking in bed, not studying for an exam.
Combination of both: A car accident – While a drive has no control over other drivers (the exogenous portion), the probability of an accident happening is strongly influenced by the driver’s behaviour and ability (endogenous)

Objective and Subjective Risks

An objective risk is a risk that is determined by analyzing past experiences and calculating the mean (average) of the losses and the standard deviation (the average difference of each loss from this average) of the actual losses from the expected losses for a particular risk exposure
Insurers can calculate the objective probability of a loss by tracking various classes of drivers over several years
However, in terms of stocks vs. T-bills, a long term (15 to 20 year look) may be required to find the real average (compared to short term – less than 10 years)
A subjective risk means the uncertainty is based on a person’s mental condition or state of mind and the resulting subjective probability is based on an individual’s personal estimate of a chance of loss.
Example: Some drivers cannot accurately assess safe driving speeds in bad weather
Insurance companies use inductive reasoning to come to conclusions about objective risks – they analyse past data to predict future losses
Deductive reasoning can be used with probabilities where the probability is obvious from the nature of the event
Example: Probability of pulling a red card from a deck of cards is 50%

Pure and Speculative Risks

Pure Risk refers to risks where there is a chance of a loss or no loss, but no chance of a gain – these risks are generally insurable.
Example: Your house burns or it doesn’t; you die in an airplane crash or not
Speculative Risk describes situations where there is the possibility of a loss but also the possibility of a gain
For example: An investment in common stock can either return a profit or sustain a loss

Pure Risk for Individuals

Individuals are exposed to three broad categories of pure rise:
Property risk is the risk of damage to or loss of one’s auto, home, and personal belongings as a result of a fire, an accident, an earthquake, theft, etc.
Direct loss is the damage to or loss of property
Indirect loses – example: the need to rent another space while there