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How DFA Can Help the Property/Casualty Industry, Part 4
Hurricanes Katrina, Rita, Wilma...
Catastrophes: Models and Reserving
Risk Measures
Reinsurer Results:
Catastrophe and Strengthening
Hurricanes: 2003 and 2004 Results, Clustering and TransitioninG
Brushfire and Fire Following Exposures
Tsunami Exposure Worldwide and U.S.
Wind and Hail: Relative Hazard Levels
Cat Modeling Class
Introduction to Reinsurance
Holborn Technical Seminar
Catastrophe, Injury, and Insurance
Review of Myers & Read ARIA Paper
A Perfectly Ordinary Tuesday Morning
This is Not Your Father’s Cat Model
Global Warming and Increased Catastrophes?
Reinsurer Risk Loads from Marginal Surplus Requirements, PCAS LXXVII
Reinsurance Markets
Risk Transfer Assessment
Introduction to Asset Returns and Risks
CAS Call Paper Panel
Ceded Reinsurance Issues in DFA
Catastrophe Reinsurance Simulation Game
Reinsurance by any other name
Clash Pricing
ALLOCATION OF SURPLUS FOR A MULTI-LINE INSURER
Optimization to Improve Business Performance
 
1987
Paul J. Kneuer
 
Page: 1 2 3 4 5 6 7 8 9

Table III-A -- Total Squared Error (in 10¹² 's) From Regressing Quarterly Losses

Table III-B -- Chi-Square Statistics From Regressing Quarterly Losses

These results show substantial instability, as well as the problems noted with using one-year flows to allocate surplus.

Other allocation methods have avoided using one-year flows by examining ratios of surplus to unpaid losses, total reserves or total liabilities (10). Table IV shows an allocation on loss reserves.

Table III-C -- December 31, 1985 Surplus ($000's)
Allocated on Unpredicability of Losses

Table IV -- Surplus Allocated On Loss and Loss Expense Reserves

Line
December 31, 1985 Reserves
Allocated
December 31, 1985 Surplus
Auto Liability
$ 40,583,226
$19,847,726
Auto Physical Damage
3,357,221
1,641,890
Homeowners
5,168,457
2,527,697
Other Property
3,510,750
1,716,975
Workers' Compensation
33,330,445
16,300,664
Medical Professional
10,074,143
4,926,884
Other Liability
26,123,56
12,776,050
Miscellaneous
32,252,599
15,773,530
Total
$154,400,404
$75,511,417

These methods have reversed the problems of growth and runoff that the other methods pose. A growing line presents an exposure to catastrophic loss that may be out of proportion to its reserves or other liabilities that arose earlier. A short-tailed line will be similarly under-represented even if the potential for very large losses is significant. In short, the volatility of a dollar of expected paid losses is not uniform among lines. Khury pointed this out for reserves in his paper, "Loss Reserves: Performance Standards" (PCAS, LXVII, 1980).

Clearly, the uncertainty in a dollar of windstorm unearned premiums, or casualty excess-of-loss loss adjustment expense reserves is higher than that of a dollar of automobile collision loss reserve. However, the principal difficulties in using these methods to make informed business decisions is the lack of support for these allocations. This is summarized in the NYCB Report.

"The hardest choices facing anyone wishing to evaluate insurance profits are those associated with returns on invested capital.

  1. "It is not possible to satisfactorily determine how much capital is associated with a particular group of policies.

  2. "It is even harder to determine how much capital should be associated with such a group of policies.

  3. "It is hardest of all to determine whether an observed rate of return on capital is satisfactory or not.

"..Any prospective method must deal with expected capital requirements and expected rates of return on that capital. Thus, the prospective approach adds its own set of significant estimation problems to the problems inherent in both methods." [Emphasis in original.]

Attempts to rationally allocate a risk margin to unpaid losses on the basis of expected variability cannot solve these problems. This is because the observed variability is neither constant in time, (as shown above) nor uniform among lines (as noted by Khury).

Without downplaying the specific problems of each at these allocation methods, there are general, practical problems that any method must address. Three problems deserve mention here. Sections of an insurer's book are often tied together in the marketplace, such as a piece of accommodation business written to obtain other, desirable business. In any adversarial decision there is an incentive to make the most favorable allocation, which may not be the most accurate. Finally, surplus is not in itself relevant. Equity is. While surplus is the key component of equity, pre-paid expenses, tax loss carry forwards, Schedule P excess reserves, non-authorized reinsurance, other non-admitted assets, and sunk costs such as training or software development costs have value and need to be reflected in any informed economic decisions, in addition to surplus. These other quantities are less subject to analysis.

Tables I, II, IIIc and IV each allocated the industry's surplus. The results, which are summarized in Table V, are substantially different. That is because, while each of these four methods reflected an allocation based on one variable that is associated with increased exposure, each method based its allocation on a different variable. Each method reflects some of the limitations on the insurers' capacity: none reflects all of them.

We have seen several practical concerns which would limit the usefulness of each allocation method for economic decision-making. But this is not to conclude that every allocation method must be impractical. However, before practical allocation methods can be discussed, there is a need to understand

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(10) See for example the 1984 New York Compensation Board Report to the New York Insurance Department , or Model D in Report of the NAIC Investment Income Task Force, Section III. The NYCB allocates surplus, first to fund any unearned underwriting losses, and the remainder in proportion to the sum of loss reserves and the expected loss component of the unearned premium reserves. The NAIC approach , which has been used in Texas, allocates surplus in proportion to estimated total liabilities.

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