RISK 6

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Risk-Taking Appetite and Ability

Learning Objectives

1. Discuss the risk-taking appetite and ability of an organization and its importance to an effective risk management program. (p. 2)

2. Identify the key financial and non-financial factors used to

determine per-occurrence and aggregate retention amounts. (p. 7) 3. Discuss how loss stratification helps determine per-occurrence

retentions. (p. 13)

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Learning Objective #1: Discuss the risk-taking appetite of an organization and its importance to an effective risk management program.

I. Alternatives for Treating Loss Exposures

A. Loss exposures are either:

1. Avoided 2. Transferred 3. Financed

B. Insurance is not a “transfer,” in spite of several risk

management theorists’ proclamation otherwise. Insurance is a financing technique; a type of loan in which the premium is the interest and the limit of coverage is the amount borrowed, but only if a covered loss occurs. The contingent nature of the insurance contract does not require repayment of the principal borrowed (unlike an ordinary loan) as the “interest” of the fortunate many that do not have a loss repays it on behalf of the unfortunate ones who do.

C. An uninsured loss is a retained loss. D. Most insured losses require the insured to retain part of the

loss, either in the form of a deductible or a self-insured retention.

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II. Risk-Taking Appetite

A. Risk-taking appetite is the organization’s willingness to accept or tolerate risk.

1. Internal factors affecting an organization’s risk-taking

appetite a. History of risk-taking b. Long-term organizational objectives c. Stage in organizational life cycle

1) Start-up stage 2) Growth stage 3) Mature stage 4) Declining stage

d. Financial stability (assets, income and cash flows) e. Management’s willingness to take risk vs. the

organization’s financial ability to assume risk

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2. External factors affecting an organization’s risk-taking appetite a. Market maturity b. Competition and the need to take business risk c. Public image d. Stakeholders’ attitudes (owners, creditors,

government, beneficiaries, etc.)

III. Risk-Taking Ability

A. Risk ability is the financial capacity for assuming risk

1. Likelihood of loss (frequency and severity) 2. Predictability of loss (variance of actual from expected) 3. Cash flows 4. Income levels 5. Asset levels and liability levels

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B. Importance of a risk-taking appetite and ability in a risk management program

1. Willingness to assume risk without the financial

capacity to assume risk is an empty promise. 2. Financial capacity to assume risk without the

willingness to assume risk is underutilized capacity.

C. The risk manager, working with the CFO and other senior management, must determine the organization’s risk-taking appetite as well as its financial ability to assume risks by using both financial and non-financial measurements to effectively manage the organization’s risks.

D. The risk management definition of retention is the

acquisition of funds to pay losses.

Note: the definition does not address if the funds are needed to pay the first portion of the loss (sometimes called a deductible), part of each loss (sometimes called co-payment corridor or co-insurance), the amount of the loss in excess of policy limits (something usually not thought about), or the entire amount of the loss (often called a retention).

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Commentary Risk Management versus Insurance Management

Assume that the organization has only two alternatives for handling its risks: buy insurance policies or apply risk management treatments except insurance. Payments under insurance policies for losses are contractually guaranteed, but at a cost of premium payments, application of deductibles or retentions, application of exclusions and restrictions, and the possibility, remote as it is, that the insurance company will become insolvent and unable to pay for losses.

Risk management without insurance does not have guarantees of payment, but it also does not have many of the insurance company expenses passed on in the insurance premium (along with state taxes) and does not have exclusions or restrictions or a risk of insolvency, except for your own organization’s insolvency.

The organization’s risk-taking nature and financial ability to assume risk must be compatible to either alternative. Considering insurance only, we can assume the organization is very conservative and takes as little risk as possible. However, if an exposure is not covered, or a large deductible is imposed, or the insurance company becomes insolvent, the organization’s financial ability to respond to uncovered losses suddenly becomes the primary means of handling the risk. Considering risk management without insurance only, it can be assumed the organization is very aggressive at taking risk, but now the financial ability becomes even more important as every risk, from the smallest to the largest, must be financed by the organization through internal funds or by borrowing external funds.

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Learning Objective #2: Identify the key financial and non-financial factors used to determine per-occurrence and aggregate retention amounts.

IV. Factors Used to Determine Retention Levels

A. Financial factors

1. Net income 2. Net worth 3. Ability to borrow 4. Cash flows

B. Non-financial factors

1. Risk appetite – aggressive or conservative 2. Match of financial constraints and risk appetite (ability

versus willingness) 3. Cost effectiveness of retention, e.g., the price of

insurance relative to the cost of losses retained

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Example 1: Company A is strongly entrepreneurial in philosophy and willing to take risks. However, it is a start-up company with negative net income, little net worth, and little ability to borrow. Does a match of financial constraints and risk attitude exist? What needs to change? Example 2: Company B is very conservative and not willing to take much risk. They are flush with cash, have great net income, awesome net worth, and probably have more money than their banks. Does a match of financial constraints and risk attitude exist? What needs to change?

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C. Insurance is the most costly of all methods of handling loss exposures.

1. Predictable losses to the insured are also predictable to

the insurance carrier. 2. The insurance carrier will build the cost of predictable

losses into its premium calculations, along with all other cost factors.

3. Predictable losses will cost the insured more if the

insurance carrier pays those losses through the insurance contract.

4. Expected losses are paid plus the costs and profit of an

insurance company. The expense ratio is the determining factor.

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Commentary

Now that we have your attention, think about this carefully. We are talking about the risk management universe, not the asteroid-sized world of a BOP policy or the microcosm of a homeowner’s or personal auto policy. Once a commercial account reaches a sufficient size, underwriters will switch from pricing the account on a schedule basis to loss rating, using experience to modify premiums to make their premiums competitive and to try to make an underwriting profit.

The insurance industry is full of wise old axioms or truths, and here is one that addresses this subject: in the long run, every account will pay for its losses. If this did not happen over the long run, the insurance company funds would be gone in the blink of an eye. The premium for the account that doesn’t have a loss (this year) pays for the loss someone else has, and so on and so on.

Once you believe this old axiom, then it becomes easy to understand why insurance is the most costly of the risk management alternatives. Think about what is required to be paid out of the premium collected: Losses and loss adjustment expenses Loading for acquisition expenses (commissions, underwriting and policy issuance costs, loss control, management, etc.) Loading for insurer profit Loading for contingencies (extra profit or unexpected loss) State premium taxes

To the extent the organization can retain loss, it eliminates most of the acquisition expense, insurer profit, contingencies, and possible premium taxes on those losses.

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Skills Application Scenario #12 – Retention Levels At the yearly meeting of facility managers, Mary Donner, the risk manager, made a presentation on the cost of risk and the current structure of the insurance and risk management program for DCRI. Mary mentioned that the current program was rather conservative and somewhat expensive, particularly after the recent spate of catastrophic property losses affecting coastal areas, such as in New Jersey, Florida, California, and Mexico, and the resulting increase in property insurance premiums. She said she was investigating alternatives that could result in a lower premium cost if DCRI was willing to assume more risk. Using the financial information provided, how would you assist Mary in making a decision regarding the following alternative risk treatments? What additional information might be needed? What are the financial and management implications to the corporation for any of these alternatives? a. Increase the general property deductible from $10,000 per

occurrence to $100,000 per occurrence. On average, there are 10 property losses a year in excess of $10,000. The total cost of these losses, including the deductibles is $185,000. Damage is generally confined to guest rooms as the result of wild parties.

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b. Increase the wind and hail deductible from 2% of total insurable values, subject to a minimum of $100,000, to 5%, minimum $250,000 for properties located in Atlantic City and Naples, and from $25,000 to $50,000 in all other locations. One sign in Lake Tahoe was destroyed last year at a replacement cost of $75,000 when high winds toppled it.

c. Increase the flood deductible from $50,000 to $1,000,000 except

for Naples, Florida, which is eligible for the $500,000 federal flood insurance program coverage on the structure with an additional $200,000 for business personal property. Engineers estimate the probable maximum flood loss to be $5,000,000 at Naples and $500,000 at all other locations. The premium savings is estimated to be $25,000. There have been no flood losses in the last 5 years.

d. Fully retain all general liability, product liability losses, and

workers compensation losses using a captive insurance company domiciled in North Carolina. The workers compensation exposures will be fully retained with the captive providing reinsurance to the fronting company. The fronting fees and administrative costs of operating the captive are $200,000 a year.

Total liability losses average $250,000 a year for the last five years. Workers compensation losses average $2,000,000 a year, with 75% of the losses being medical payments only and the balance indemnity payments. The allocated loss adjustment expense for these three types of loss is 10%. The premiums for these coverages, as currently written, are approximately $3,250,000.

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Learning Objective #3: Discuss how loss stratification helps determine per-occurrence retentions.

V. Loss Stratification Process

A. Determining per-occurrence events

1. Need for record of past experience

a. Credibility of past loss history b. Probable maximum loss – estimate developed for

property insurance underwriters that represents the worst amount of loss that is likely to happen, as opposed to the worst possible result that could happen

A PML estimate includes adverse conditions, such as the impairment or failure of a sprinkler system, a delayed fire alarm, insufficient water supply or delayed firefighting response, if such conditions seem reasonable.

c. Maximum possible loss – worst possible loss that

could occur regardless of protective measures, limited only by adequate separation between buildings or other engineering safeguards

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Commentary Risk management professionals are sometimes concerned that the focus of attention is on the probable maximum loss and not the maximum possible loss. One only need recall several “classic” losses to see how this shortsightedness can occur. 1. The “Titanic” was unsinkable because of its redundant bulkheads

that created compartments that would eliminate massive flooding should the hull be breached.

2. The “fireproof” McCormick Place in Chicago caught fire and was

completely destroyed in spite of a massive sprinkler system when the unprotected steel beams melted.

3. The Union Carbide accidental release of toxic pesticides that

killed between 3,000 and 15,000 people in the first month and permanently injured over 100,000 in Bhopal, India.

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Commentary

The Loss That Couldn’t Happen

An insurance company was asked to insure a collection of fine Egyptian statuary to be stored in a fireproof, secured warehouse in New Jersey. An underwriter sent a loss control specialist out to survey the location and the specialist came back with a glowing report. “I never saw a more perfect risk. The statues are about ten feet high, weigh several tons each, and are made from solid stone. I don’t know how they got them there, but it would take a railcar to get them out. The building is a stand-alone fireproof structure with a team of watchmen and dogs patrolling regularly. There hasn’t been an earthquake in Jersey for centuries, the warehouse is on high ground away from the coast, and meteorites don’t worry me. What could possibly happen to them?” The underwriter promptly insured them for $500,000 and a few weeks later the insurance company wrote out a check for $500,000 for the destruction of the statues. It seems the statues were waxed to keep them at a high finish and prevent mold and discoloration. A little fire broke out in the wax- impregnated rags used to polish them, and the fire then spread to the wax on the statues. The next thing you knew, the statues were red-hot. Then the firemen came and sprayed water on the statues to put out the fire, and the statues shattered into tiny pieces. Story adapted from UPrinciples of Insurance U, Mehr and Cammack, Richard D. Irwin, Homewood, IL

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d. Ultimate total loss – incurred losses that have been developed

e. Ranges or grouping of similar values

(stratification)

2. Loss stratification helps determine per-occurrence retention levels by

a. Reducing large number of observations into

smaller, more manageable number b. Using measures of central tendency to manage

tails or outliers c. Reducing bias and triviality by size of strata

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Commentary The Law of Large Numbers The Law of Large Numbers has guided the insurance industry for centuries without anyone knowing what to call it. In the 19th century, French mathematician Simeon Denis Poisson formalized what early underwriters were doing with this: If you increase the number of observances, the more closely the actual results obtained will approach the probable results expected with an infinite number of observations. He called this “the law of large numbers.” We apply this principle to help us make decisions: if losses are predictable (because there are a sufficiently large number of them), we can be comfortable that the actual results will approach the predicted results. If losses are unpredictable, we can combine our smaller number of observations with others also seeking more certainty, and our combined numbers will become large enough to make the actual results approach the predicted results. Hence, when we insure our risks with an insurance company, we combine our “small numbers” with all of their insureds that also had “small numbers.” With all the “small numbers” from individual insureds combined, there is now a sufficiently “large number” and predictability is enhanced.

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A Practical Exercise State Farm Insurance Company, Allstate Insurance Company, Country Companies, and Farmers Insurance Company insure most of the private passenger vehicles in the U.S. The actual results and the predicted results from automobile collisions with other vehicles will be virtually the same because the number of vehicles exposed is so great. Let’s assume that the rate of vehicle collision for today is 1 per 1000 autos. If we try to predict the number of vehicle collisions occurring today involving the members of this class, the likelihood of an accident is very small (since we are here for eight or more hours and not out driving among the crazies,) but our confidence in our prediction of “none” is not as great as the four insurance companies prediction of 1 per 1000 vehicles. If we combine our exposures with all other CRM courses being conducted this week, the confidence in our prediction will rise, but not by much. If we combine our exposures with all other National Alliance courses (CIC, CISR, CSRM, Ruble Seminars, Graduate Seminars) being held this week, the confidence level in our prediction will increase even more, but it would still not be as accurate as the insurance companies’ prediction. If we combine even more exposures by extending our observations to include the vehicles of all people working in the insurance business, the confidence level in our prediction will begin to approach the insurance companies’ confidence level in their prediction, but the 3,000,000 or so vehicles we would be tracking is still significantly smaller than the insurance companies’ number of exposures, and our confidence level, while good, is still not as good as theirs.

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The problem in selecting retention as an option is that most organizations are not sufficiently large enough to have a high degree of confidence in any prediction. Frequency is notoriously difficult to predict for most organizations because most organizations are simply too small. Predicting severity is even harder; while we know that most losses are very small, there is always the possibility of the multi-car accident involving a truck carrying nuclear waste and the bus full of brain surgeons from Johns Hopkins. However, there are methods to improve the predictability of losses, particularly with respect to severity.

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B. Setting ranges for stratification

1. Primary layer of losses (sometimes called the “working layer” or “burning layer,” even for liability losses)

a. Identify the predictable losses b. Choose a maximum value of an acceptable single

loss to keep in the primary layer (loss limit) c. Determine the appropriate severity value of losses d. Determine the number of losses to keep in the

primary layer e. Multiply the retained number of losses times the

severity value to determine the total dollars of expected losses from the frequency and severity analysis

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2. Top or excess layer

a. Identify the maximum amount of loss tolerable per occurrence

b. Identify the annual aggregate retention (maximum

acceptable accumulated losses in a year) c. Determine the maximum possible loss scenario

3. Buffer layer

a. Minimum of layer is maximum budgeted losses (management’s estimate of losses likely to occur)

b. Maximum of layer is the annual aggregate

retention The question is now: How large should a retention layer be?

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C. Determining per-occurrence retention strata

1. Review historical loss data 2. Identify patterns of frequent losses

a. Patterns of size of loss b. Patterns of seasonality c. Patterns of location d. Patterns of products e. Patterns of…whatever

Commentary There is another reason for using patterns besides determining per- occurrence retention data – if there is a pattern, the losses are probably predictable, and if the losses are predictable, the risk manager can use that information to identify loss prevention measures to control the losses. If the same losses keep happening over and over again, the risk manager should try something different to try to get a different result. While predictability may then suffer, some losses may be prevented, and preventing losses is nearly always a positive result.

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3. Define possible ranges – stratify the values

a. Place 75% or 80% of the losses in the primary layer

b. Place all losses that are too worrisome to retain,

either per risk or in the annual aggregate, in the excess layer

c. All other losses fall in between, in the buffer layer

Commentary Loss stratification is more art than science. One gets a feel for setting ranges only by doing it. However, the general rule is to define the primary or bottom layer by relying on the old management saw, the 80/20 rule (80% of everything is done by 20% of everyone). Another general rule is 75% / 25%. Either one works for the first try.

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Top or excess layer

Center or buffer layer

Bottom, small loss, or primary layer

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Exhibit 1 Loss Run - Current Year (in chronological order)

First-time period Second-time period

8,767 977 9,644 978 1,944 1,457 1,554 345

345 1,754 246,546 1,876

348 346 8,467 357

453 9,678 455 1,945

2,166 345 2,355 190 2,466 675

567 456 644 5,475

123,385 345 677 8,647 766 776 770 777

5,366 864 1,889 9,755

64,566 43,455 867 477 868 543 977 1,934

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Exhibit 2 Loss Run – Current Year

(Sorted by value – loss array)

Lowest values Highest values 190 977

345 978 345 1,457 345 1,554 345 1,754 346 1,876 348 1,889 357 1,934 453 1,944 455 1,945 456 2,166 477 2,355 543 2,466 567 5,366 644 5,475 675 8,467 677 8,647 766 8,767 770 9,644 776 9,678 777 9,755 864 43,455 867 64,566 868 123,385 977 246,546

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Stratification Option 1

U Loss Value U U# of Losses 0 - 500 12 501 - 1,000 15 1,001 - 2,500 11 2,500 - 10,000 8

10,000+ U 4 50

In this option, the stratum is too narrow. Less than 75% to 80% of the losses fall in the first stratum, and since these are total dollars of loss, a minimum of 30 losses in a stratum would provide some degree of credibility (Central Limit Theorem). Stratification Option 2

ULoss Value U U# of Losses 0 - 1,000 27 1,001 - 10,000 19 10,001 - 100,000 2 100,000+ U 2

50 In this option, slightly more than half of the losses fall within the first stratum, and the number of losses is close to 30, but not quite.

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Stratification Option 3

ULoss Value U U# of Losses 0 - 2,500 38 2,501 - 10,000 8 10,001 - 100,000 2 100,000+ U 2

50 In this option, slightly more than 75% of the losses fall within the first stratum, and there are at least 30 losses for credibility. Accordingly, DCRI might define its per occurrence retention plan as follows:

Primary layer of retention – all losses up to $2,500 (predictability)

Per risk retention is up to $100,000 (any per loss value higher will strain the risk management budget and adversely affect the cost of risk)

Buffer layer is $2,501 to $100,000 (not predictable, but manageable)

With respect to the annual aggregate retention, DCRI would determine the highest value of losses acceptable in a year. Since the total losses are roughly $575,000 in the current year, DCRI might decide that $1,000,000 would be an acceptable annual aggregate retention.

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4. Considerations

a. Use of ultimate developed losses b. Index ultimate developed losses against indexed

exposures c. Loss history issues

1) Accuracy 2) Credibility (number of data items, years of

information) 3) Integrity of loss history

d. Predictability of individual losses due to

1) Accuracy in claim reserving 2) Consistency in claim reserving and handling 3) Errors in reporting, recording, reserving,

and settling

e. Predictability of aggregate losses

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5. Decision rules

a. If losses are predictable, retain as much as possible and affordable

b. If losses are unpredictable, insure as much as

possible and affordable c. Predictability means less variance; unpredictable

losses are made less variable with insurance

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Review of Learning Objectives

1. Discuss the risk-taking appetite and ability of an organization and its importance to an effective risk management program. (p. 2)

2. Identify the key financial and non-financial factors used in

determining per-occurrence and aggregate retention amounts. (p. 7)

3. Discuss how loss stratification helps determine per-occurrence

retentions. (p. 13)

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Notes