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Insurance and RiskFinance 640

- Class 3 September 29, 2004

Normal Distribution Selected Threshold Points

Common Decision Mistakes

- Recency effect
- Settling for the information at hand
- Failing to identify criteria
- Failing to generate alternatives

The Antidote

- Following a systematic procedure when making a

choice - Adopting a rational decision-making method
- Then, sticking to it with discipline.
- There are no rational people, there are only

rational methods.

Problems and Decisions

- Problem Difference between what we want or

expect and what we got. - Decision To select the best alternative which

balances goal achievement with risk. - Elements to a decision
- Objectives
- Criteria
- Alternatives
- Risk mitigation

Intuitive Decision- Making

- Natural way to make decisions
- Use gut-feel to process information and select

among alternatives - Do so automatically, quickly and without

awareness of details

Intuitive Decision- Making(cont.)

- Intuitive decision-making suffers greatly from

inconsistency. - On different days, the same expert will decide

the same clear-cut question differently.

New England Journal of Medicine Study

- Three different panels of physicians examined a

group of 389 boys suffering symptoms of sore

throat. - The first panel judged that 45 needed a

tonsillectomy

New England Study (cont.)

- Of the remaining 214, the second panel concluded

that an additional 46 needed a tonsillectomy. - The third panel examined only the 116 judged

healthy by both groups. - It found that 44 more needed a tonsillectomy.

Corroborating Evidence

- Other professionals show more consistency than

the doctors in the tonsillectomy study. - But numerous studies show inconsistencies far

higher than the professionals imagine themselves.

Correlation with True Outcomes

Implication of Studies

- People making decisions usually
- 1. Suffer from information overload.
- 2. Have a hard time applying simple decision

rules consistently even when they try.

Risk Management Matrix

Risk Exposures of An OSU Business Student

- Physical damage to 1994 Ford Taurus.
- Liability lawsuit arising out of use of the

vehicle. - Total loss of clothes, electronic equipment and

personal property due to a kitchen fire in

apartment. - Disappearance of a contact lens.

Risk Exposures (cont.)

- Bodily injury from being hit by a car while

jogging on a busy street. - Liability because pet dog bites a child.
- Malfunction and repair of personal computer.

Basic Characteristics of Insurance Revisited

- Pooling of losses
- Payment of fortuitous losses
- Risk transfer
- Indemnification

Pooling

- Spreading losses incurred by the few over the

entire group so that the average loss is

substituted for actual loss. - I have been loss-free for 4 years, how can they

possibly justify raising my premium? - Example of 10 Boats on the Yangtze.
- The role of underwriters and actuaries.

How Big Should the Pool Be?

- The greater the number of exposures, the more

closely will the actual result approach the

expected result. - This is known as the Law of Large Numbers.
- It is derived from the Central Limit Theorem.

Central Limit Theorem

- In random samples of n observations, the

distribution of the sample means will be a normal

distribution. - The mean of the sample distribution will equal

the mean of the population distribution.

Central Limit Theorem (cont.)

- The standard error of the sample mean will be

equal to the standard error of the population

divided by the square root of n. - The standard error of the sampling distribution

can be reduced simply by increasing the sample

size.

Example Law of Large Numbers

Insurance and Law of Large Numbers

- Insurance companies expect losses to occur.
- The major concern is the deviation between actual

losses and expected losses. - By insuring large numbers, insurance companies

reduce their objective risk. - The whole is less than the sum of its parts.

Pooling Arrangements

- Basic Idea
- Replace your loss with the average loss of a

group - Issues
- What happens to each persons
- Expected loss
- Standard deviation of loss
- Maximum probable loss
- How do these results change with
- More participants
- Correlation in losses among the participants

increases

Risk Pooling Example with 2 People

- Two people with same distribution
- Outcome Probability
- 2,500 0.20
- Loss
- 0 0.80
- Assume losses are uncorrelated
- Expected value 500
- Standard deviation 1000

Risk Pooling Example with 2 People

- Pooling Arrangement changes distribution of

accident costs for each individual - Outcome Probability
- 0 (.8)(.8) .64
- Cost 1,250 (.2)(.8)(2) .32
- 2,500 (.2)(.2) .04
- Expected Cost 500

Risk Pooling Example with 2 People

- Effect on Expected Loss
- w/o pooling, expected loss 500
- with pooling, expected loss 500
- Effect on Standard Deviation
- w/o pooling, standard. deviation 1000
- with pooling, standard. deviation 707

Risk Pooling with 4 People

- Pooling Arrangement between 4 people
- Outcome Probability
- 10,000 0.000006
- 7,500 0.000475
- Loss 5,000 0.014
- 2,500 0.171
- 0 0.815
- Expected Loss 500
- Variance 1,089

Risk Pooling with 20 People

Risk Pooling of Uncorrelated Losses

- Main Points
- Pooling arrangements
- do not change expected loss
- reduce uncertainty (variance decreases, losses

become more predictable, maximum probable loss

declines) - distribution of costs becomes more symmetric

(less skewness)

Effect of Correlated Losses

- Now allow correlation in losses
- Result uncertainty is not reduced as much
- Intuition
- What happens to one person happens to others
- One persons large loss does not tend to be

offset by others small losses - Therefore pooling does not reduce risk as much

Effect of Positive Correlation on Risk Reduction

Main Points about Risk Pooling

- Main Points
- Pooling reduces each participants risk
- i.e., costs from loss exposure become more

predictable - Predictability increases with the number of

participants - Predictability decreases with correlation in

losses

Costs of Pooling Arrangements

- Pooling arrangements reduce risk, but they

involve costs - Adding Participants
- marketing
- underwriting
- Verifying Losses
- Collecting Assessments

Insurance and Law of Large Numbers

- Insurance companies expect losses to occur.
- The major concern is the deviation between actual

losses and expected losses. - By insuring large numbers, insurance companies

reduce their objective risk. - The whole is less than the sum of its parts.

Number of Exposure Units Required

- Formula exists to estimate the number of exposure

units for a given degree of accuracy. - Assumes loss population is normally distributed
- Estimates the occurrence of a loss, not the size

of the loss - Formula is based on the fact that known

percentages of losses will fall within 1, 2 or 3

standard deviations of the expected value. - Should be used with great caution

Formula (cont.)

- N S2p(1- p)/E2
- Where
- N Number of exposure units required for the

degree of accuracy desired - S the number of standard deviations
- p probability of loss
- E the degree of accuracy desired
- Expressed as a ratio of the actual losses to the

total number in the sample

Example 1

- 30 Probability of Loss
- 95 Desired Confidence
- That the actual loss ratio will not differ from

the expected probability by more than 2

percentage points - ( the range will be 28 to 32).

Example 1 (cont.)

- N S2p(1- p)/E2
- N 22(.3)(1- .3)/(.02)2
- N 4(.3)(.7)/(.0004)
- N 4(.21)/(.0004)
- N .84/(.0004)
- N 2,100

Example 2

- Probability of loss p 5.0
- Degree of accuracy 0.5
- Degree of confidence 95 2 std. Dev.
- Exposure units needed N
- N S2p(1- p)/E2
- N 22(0.05)(0.95)/(0.005)2
- N 7,600

Implication of Two Examples

- When the probability of loss is small
- A larger number of exposure units is needed to

create an acceptable degree of risk

Function of Insurance Companies

- Insurers are intermediaries that lower the cost

of pooling arrangements by - reducing the number of contracts
- employing people with expertise in
- marketing, underwriting, and claims processing
- Insurers also provide services needed by

businesses - loss control
- claims processing (third party administrators)

More on Insurance Distribution

- Marketing in Insurance
- Exclusive agents
- Independent agents
- Brokers
- Direct marketing
- Internet

Fixed Premiums Versus Assessments

- Why do insurers charge fixed premiums (as opposed

to having ex post assessments)? - Cost of collecting assessments
- With assessments, there might be a delay in

payments to those who have claims - Assessments impose greater uncertainty to

policyholders than fixed premiums

Implications of Fixed Premiums

- Revenues may not match costs
- Someone must be the residual claimant
- i.e., someone must bear unexpectedly high losses

and receive profits when losses are lower than

expected - Insurers can fail (become insolvent)
- Examine the implications of these observations in

Ch. 5

Other Examples of Diversification

- The result that pooling reduces risk applies to

many scenarios - stock market diversification
- diversification across lines of business within a

firm

What is Enterprise Risk Management?

- ERM is the application of the basic risk

management principles to all risks facing an

organization - Other names for ERM
- Enterprise-wide risk management
- Holistic risk management
- Integrated risk management
- Strategic risk management
- Global risk management

ERM Features

- Consolidates risk exposures and identifies core

and non-core risks - Views risk through common lens
- Coordinates risk management process

organizationally - Systems
- Processes
- People

Class Exercise 1

- Step One
- What is the top revenue driver for Scooper

Dooper? - Asset that contributes most to corporate

earnings - Impact of a disruption to this driver would have

the greatest impact on your organizations

financial health

Class Exercise 1

- Step Two
- What peril would cause the greatest disruption

to your top revenue driver?

Protecting Value Study 2004

- Sponsored by FM Global
- Mutual commercial property insurer
- Headquartered in Johnston, RI
- Conducted by Harris Interactive
- Surveyed over 600
- CFOs and treasurers
- Risk managers
- Investment professionals
- US and Europe

Survey Results

- ERM should be a board level issue
- 90 CFOs, Treasurers and Risk Managers
- 93 Investment Professionals
- ERM is a board level issue
- 65 US
- 93 Europe

Top Revenue Drivers

Top Peril to Companys Top Revenue Driver

Where Did ERM Come From?

- Traditional risk management
- Formally developed as a field in the 1960s
- Focused on pure risks
- Loss/no loss situation
- Often could be insured
- Developed from insurance purchasing area

New Elements of Risk 1970s

- Foreign exchange risk
- End of Bretton Woods agreement in 1972
- Commodity price risk
- Oil price fluctuations of the 1970s
- Equity risk
- Development of option markets - 1973
- Interest rate risk
- Federal Reserve Board policy shift - 1979

Failure to Manage Financial Risk

- Foreign exchange risk
- Laker Airlines 1970s
- Borrowing in dollars
- Revenue in pounds
- Interest rate risk
- U. S. Savings and Loans 1980s
- Borrowing short
- Lending long
- Commodity price risk
- Continental Airlines 1990
- Fuel costs not hedged
- Oil price doubled with Gulf War

The New Risk Management -1980s

- Financial risk management
- Dealt with financial risk
- Foreign exchange risk
- Interest rate risk
- Equity risk
- Commodity price risk
- Use derivatives to hedge financial risk

Financial Risk Management Toolbox

- Forwards
- Futures
- Options
- Swaps

New Elements of Risk 1990s

- Failure to manage derivatives appropriately
- Financial model failures
- Improper accounting for derivatives

Mismanagement of Financial Risk

- Mismanagement of derivatives
- Gibson Greetings
- Proctor and Gamble
- Barings Bank
- Orange County
- Model failure
- Long Term Capital
- Accounting improprieties
- Enron
- Cedant
- Arthur Andersen

The New Risk Management - 1990s and beyond

- Enterprise Risk Management
- Initial focus on avoiding derivative disasters
- Developing into optimizing firm value
- Chief Risk Officer
- Sarbanes-Oxley Act 2002
- Increased focus on risk models

Components of ERM

- Corporate governance
- Line management
- Portfolio management
- Risk transfer
- Risk analytics
- Data and technology resources
- Stakeholder management

ERM Risk Categories

- Common risk allocation
- Hazard risk
- Financial risk
- Operational risk
- Strategic risk
- Bank view New Basel Accord
- Credit risk
- Loan and counterparty risk
- Market risk (financial risk)
- Operational risk

Hazard Risk

- Pure loss situations
- Property
- Liability
- Employee related
- Independence of separate risks
- Risks can generally be handled by
- Insurance, including self insurance
- Avoidance
- Transfer

Financial Risk

- Components
- Foreign exchange rate
- Equity
- Interest rate
- Commodity price
- Correlations among different risks
- Use of hedges, not insurance or risk transfer
- Securitization

Operational Risk

- Causes of operational risk
- Internal processes
- People
- Systems
- Examples
- Product recall
- Customer satisfaction
- Information technology
- Labor dispute
- Management fraud

Strategic Risk

- Examples
- Competition
- Regulation
- Technological innovation
- Political impediments

Enterprise (Global) Risk Management

- Three step process
- Consistent measurement
- Allocation
- Incremental dealing

Consistent Measurement

- Need is to have a single relevant risk metric
- Common to all risk areas
- Must be understandable, and understood, by top

decision makers in an organization - With outside markets

Incremental Dealing

- Incremental market for risk
- Sliding price scale
- As risk level approaches firms maximum, price of

more risk rises - Creates flows to products and services that

create largest risk-adjusted returns - Firm will grow to reflect its natural strengths

where firm is more efficient vs. external markets

Enterprise Risk Management Infrastructure

- Analytics
- Valuation models
- Simulation models
- Data sets
- Risk information
- Transactions
- Internal data (customers, risk limits, products)
- Market data
- Reliable communications
- Operations
- Impact of technology

Impediments to Effective ERM

- Risk models and technology
- Organization
- Motivation
- Operating infrastructure
- Data problems
- Regional fiefdoms
- High failure rate of IT projects

Risk Metrics - Examples

- Hazard risk
- Probable Maximum Loss (PML)
- Deductibles/Retention
- Policy limits
- Financial risk
- VaR
- Misunderstanding of definition
- Limited information
- Stress based models
- Risk adjusted return on capital (RAROC)
- Operational and strategic risk
- Harder to quantify

Risk Metrics Examples (cont.)

- Risk map
- Frequency
- Severity

How ERM Can Increase Firm Value

- Process can focus on protecting
- Value
- Cash flows
- Earnings
- Cannot protect all three at once
- Examples
- Reducing taxes is earnings based strategy
- Insuring to prevent assets from declining is

value based - Hedging to maintain internal funding sources is

cash flow based

Evolution of ERM

- Control function
- How much can we lose?
- Risk adjusted returns
- Optimization
- Maximize shareholder value
- Vision of the future