Insurance and Risk Finance 640

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Insurance and RiskFinance 640

• Class 3 September 29, 2004

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Normal Distribution Selected Threshold Points
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Common Decision Mistakes

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

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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.

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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

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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

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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.

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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

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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.

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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.

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Correlation with True Outcomes
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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.

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Risk Management Matrix
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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.

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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.

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Basic Characteristics of Insurance Revisited

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

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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.

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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.

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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.

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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.

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Example Law of Large Numbers
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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.

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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

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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

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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

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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

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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

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Risk Pooling with 20 People
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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)

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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

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Effect of Positive Correlation on Risk Reduction
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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

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Costs of Pooling Arrangements

• Pooling arrangements reduce risk, but they
  involve costs
• Adding Participants
• marketing
• underwriting
• Verifying Losses
• Collecting Assessments

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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.

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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

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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

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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).

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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

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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

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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

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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)

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More on Insurance Distribution

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

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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

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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

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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

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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

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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

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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

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Class Exercise 1

• Step Two
• What peril would cause the greatest disruption
  to your top revenue driver?

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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

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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

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Top Revenue Drivers
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Top Peril to Companys Top Revenue Driver
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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

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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

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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

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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

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Financial Risk Management Toolbox

• Forwards
• Futures
• Options
• Swaps

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New Elements of Risk 1990s

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

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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

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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

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Components of ERM

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

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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

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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

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Financial Risk

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

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Operational Risk

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

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Strategic Risk

• Examples
• Competition
• Regulation
• Technological innovation
• Political impediments

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Enterprise (Global) Risk Management

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

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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

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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

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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

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Impediments to Effective ERM

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

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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

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Risk Metrics Examples (cont.)

• Risk map
• Frequency
• Severity

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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

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Evolution of ERM

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