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Erschienen in: Review of Quantitative Finance and Accounting 1/2012

01.01.2012 | Original Research

Underwriting and investment risks in the property-liability insurance industry: evidence prior to the 9–11 event

verfasst von: Hong Zou, Min-Ming Wen, Charles Chuanhou Yang, Mulong Wang

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 1/2012

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Abstract

Underwriting and investment are two important and related business activities of insurance companies. However, studies on the interrelation between underwriting and investment risks of Property-Liability (P-L) insurance companies are sparse in the literature. Using a sample of US P-L insurers, this article conducts an empirical investigation of how these two risks are associated with each other in the 1994–2000 period (before the September 11th terrorist attack in 2001). Our results, robust to various estimations, suggest that there is no significant relationship between the underwriting and investment risks among our sample firms. Such results based on pre 9–11 event period provide some support for the conjecture of Achleitner et al. (Geneva Pap Risk Insur Issues Pract 27:275–282, 2002) that many insurance companies may have failed to take an integrated approach to risk management. This resulted in a heavy loss due to dual exposures in both underwriting and investment in the 9–11 event. In the aftermath of the recent global financial crisis, risk taking and risk management of financial institutions have received more attention and increasing scrutiny. We believe the current paper provides some useful insights in this vein.

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Fußnoten
1
Prior studies on the risk-taking behavior of financial institutions (e.g., banks and insurance companies) mainly go along three lines. First, one line focuses on the relation between risk-taking behavior and ownership structures of financial institutions. Studies (e.g., Saunders et al. 1990; Downs and Sommer 1999; Chen et al. 2001) have examined the effect of managerial ownership on risk taking. Lamm-Tennant and Starks (1993) compare the underwriting risk of stock and mutual P-L insurers and report that stock insurers tend to exhibit a higher underwriting risk than do mutual firms. A second line examines whether franchise value of financial institutions can mitigate excessive risk-taking (e.g., Keeley 1990; Staking and Babbel 1995; Demestz et al. 1996; Saunders and Wilson 2001). A third line investigates the relation between capital and overall risk-profile of insurers (e.g., Cummins and Sommer 1996; Baranoff and Sager 2002).
 
2
Prior insurance-related studies use various terminologies to describe insurance firms’ major risks—for example, assets/investment risks and liabilities/product/underwriting risks. In the current study, we adopt the terms of underwriting and investment risks.
 
3
For example, Achleitner et al. (2002) report that the Allianz Group suffered a loss of more than 4 billion Euros in its investments in the initial several days following the attack on the WTC and incurred liabilities of 1.5 billion Euros while the significant underwriting loss was expected.
 
4
Due to data limitation, we leave the effect of the 9–11 event on the relation between underwriting and investment risks as an interesting question for future research.
 
5
P-L and life insurers tend to differ in their earnings mix (i.e., with P-L insurers’ profit relying more on investment income) and the investment of P-L tends to be riskier. For example, Hammond and Shilling (1978) and Fairley (1979) report that many P-L insurers have zero or negative underwriting profit and rely on investment income for profit. In contrast, Boose (1993) notes that only about one-third of life insurers’ profit is typically derived from investment income. In addition, while life insurance’s underwriting function is reasonably predictable (thank to the use of mortality table), the occurrence of P-L insurance claims is largely uncertain and stochastic.
 
6
Empirical study by Lee and Cummins (1998) shows that the arbitrage pricing theory (APT) and Wei's unified CAPM/APT (1988) models perform better than the CAPM in estimating the cost of equity capital for the P-L insurers.
 
7
For example, the famous Kenney rule argues that the ratio of premiums to surplus for a P-L insurer should not exceed 2. In recent years, there is a declining trend in Kenney ratio in the US P-L industry probably reflecting that insurers leave more financial slack for catastrophes (Cummins and Doherty, 2002). For example, Smith (2001) reports that over the period 1994–1999, the industry average for US P-L insurers was in the range of 0.84–1.3. The mean Kenney ratio of our sample is 1.12.
 
8
For example, in the September 11th attack of the World Trade Center (WTC), if an insurer provided coverage to the WTC, but also held a lot of aviation and insurance shares, both its underwriting and investment losses can be substantial.
 
9
We do not have access to the details of the investment mix of insurers and by-class return data and hence cannot use a measure reflecting the financial market risk of different asset classes. Nevertheless, in Sect. 5.3, we also test the sensitivity of our results using an alternative proxy of investment risk that is defined as the proportion of investment in common stocks, preferred stocks, and long-term low-grade bonds (i.e., class-3 to class-6 bonds with a maturity over 5 years).
 
10
This is because, unlike shareholders, company managers are often inefficient in diversifying their personal wealth outside the company (Mayers and Smith 1981).
 
11
Specifically, we define franchise value (FV)=1 if the Best rating is A++ or A+; FV = 2 if the rating is A or A−; FV = 3 if the rating is B++ or B+; FV=4 if the rating is B or B−; FV=5 if the rating is C++ or C+; and FV = 6 if the rating is C, C−, or D. We also exclude the insurers without rating (codes 88 or 99) or with rating under the regulatory supervision, or in liquidation, or with rating suspended.
 
12
The inclusion of year 1993 data is to extract the lag values in some variables.
 
13
The panel data is unbalanced and Stata—the statistical software that we use—can conveniently handle the related estimation issue of unbalanced panel datasets internally.
 
14
Among the total 35 underwritten insurance lines, 13 of them are long-tail insurance and have generated significant amount of premium income.
 
15
If we include them simultaneously in the models, none of their coefficient estimate is statistically significant (these two variables have a correlation coefficient of 0.52).
 
16
We cannot use Sargan/Hansen test to examine whether the instrument is correlated with the error term of the model since our system of simultaneous equations is exactly identified.
 
17
Fixed-effects cannot be incorporated given that the stock dummy is time-invariant.
 
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Metadaten
Titel
Underwriting and investment risks in the property-liability insurance industry: evidence prior to the 9–11 event
verfasst von
Hong Zou
Min-Ming Wen
Charles Chuanhou Yang
Mulong Wang
Publikationsdatum
01.01.2012
Verlag
Springer US
Erschienen in
Review of Quantitative Finance and Accounting / Ausgabe 1/2012
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI
https://doi.org/10.1007/s11156-010-0217-9

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