The Role of Contingent Commissions in Property-Liability Insurer

Underwriting Performance

By

Laureen Regan, Ph.D.

Fox School of Business and Management

Temple University

Philadelphia, PA 19122

phone: 215-24-7264

email: lregan@temple.edu

and

Anne Kleffner, Ph.D.

Haskayne School of Business University of Calgary

2500 University Drive N.W.

Calgary, AB T2N 1N4

Phone: (403) 220-8596

e-mail: kleffner@ucalgary.ca

March, 2010

For presentation at the Risk Theory Seminar

The authors thank participants at the American Risk and Insurance Association conference, The

Fox School of Business, and Ludwig Maximilliam University Center, Neil Doherty, Sharon

Tennyson, Scott Harrington, Andreas Richter and Richard Phillips for helpful comments on an

earlier version.

This is a working draft. Please do not cite or quote without permission.

Copyright Laureen Regan and Anne Kleffner, 2009. All rights reserved.

2

Abstract

Investigations into insurance compensation practices have drawn attention to the potential

conflicts of interest that may be associated with payment of contingent commissions to insurance

agents and brokers. However, despite the possible conflicts of interest, contingent commissions

have also been recognized as a way to better align agent and insurer incentives. If effective, then

contingent commissions should result in better underwriting performance. We investigate

whether contingent commissions are associated with improved insurer underwriting

performance. We estimate the determinants of contingent commission payments, as well as the

relationship between the proportion of contingent commissions paid and underwriting

performance. Underwriting performance is proxied by the loss ratio, the combined ratio, and

underwriting return on equity. For the period 2001 through 2005, we find a statistically

significant relationship between the use of contingent commissions and underwriting

performance.

3

1. Introduction

In late 2004, an investigation into insurance broker compensation practices by then New

York Attorney General Eliott Spitzer led to allegations of bid rigging and conflicts of interest in

the payment of contingent commissions. Contingent commissions may be paid in addition to flat

percentage of premium commissions with the object of rewarding insurance producers for

properly matching risks with insurers, and for meeting volume, profitability, and retention

targets. The initial New York lawsuit alleged that the largest broker, Marsh, systematically

engaged in bid-rigging to steer clients to insurers that paid relatively higher contingent

commissions. Spitzer’s initial investigation was widened by other state attorneys general and

other regulators. In January, 2005, Marsh agreed to pay $850 million in restitution to settle the

New York case.1 Since the investigation, the largest insurance brokerage firms have signed

consent agreements that require them to forego contingent commissions. A number of property-

liability insurers subsequently agreed to eliminate the use of contingent commissions in their

compensation formulas (Green, 2007)2. Despite the settlements, the majority of smaller brokers

and independent agencies continue to accept contingent commissions from carriers that offer

them.

Opponents of the contingent commission system argue that it creates conflicts of interest

between insurance intermediaries (agents or brokers)3 and clients. If agents are paid an incentive

commission by the insurer for placing business, and if the client is not informed of this payment

1 For a detailed discussion of the events leading up to the lawsuit, see

www.iii.org/media/hottopics/oct/oct14a_04.html 2 In July, 2009, Arthur J. Gallagher, the 4

th largest broker, announced that the Illinois Insurance Commissioner and

the Attorney General had agreed to allow the firm to resume acceptance of contingent commissions on the firm’s

retail brokerage business. 3 Although there are legal differences in the agency relationships of insurance agents and brokers, in practice, both

agents and brokers represent the interests of both clients and insurers in different aspects of the insurance

transaction. For a detailed discussion of the legal differences between agents and brokers, see chapter 2 in Keeton

and Widiss, (1988).

4

arrangement, then it is possible that the agent might place the business with the insurer offering

the highest compensation package, rather than the one that is most suitable for the client. In this

case, agents may have an incentive to distort information about coverage offers, or misrepresent

coverage offers. Then, clients might pay more for insurance than they otherwise would because

they will not be fully informed of the coverage options available to them. However, in 2008, the

1st Appellate division of the New York Supreme Court ruled that contingent commissions were

not illegal and their use did not create a conflict of interest between brokers and clients.4

Prior studies have supported the idea that contingent commission payments can provide

incentives for agents to place business with insurers so as to match clients with appropriate

insurers (Hoyt, et al., 2006; Cummins and Doherty, 2006; Regan and Tennyson, 1996). Because

agents provide information to insurers about the risk type of the applicants that insurers would

find costly or difficult to verify, agents can reduce problems in pricing and risk classification

caused by asymmetric information. Recent studies have measured the market's response to the

New York litigation and have found significant negative returns for insurers following the

announcement of the investigation, as well as larger discounts for insurers that use relatively

more contingent commissions (Hilliard and Ghosh, 2006; Cheng et al., 2007). This indicates that

investors may believe that contingent commission payments add value to insurers, and that

eliminating them is expected to reduce insurer profitability.5

There have been several studies that examine the performance of insurers using different

distribution systems, (see, for example, Berger, Cummins and Weiss, 1997) but we are not aware

of any papers that analyze the link between contingent commission payments and insurer

underwriting performance. If the use of contingent commissions improves insurer underwriting

4 See People ex rel. Cuomo v. Liberty Mut. Ins. Co. 52 A.D. 3d 378, 861 N.Y.S.2

nd 294 (June 19, 2008).

5This reaction might also signal uncertainty about the probability and size of penalties imposed on insurers under

investigation or that may be targeted in future litigation.

5

performance, then eliminating them might have deleterious consequences. If contingent

commissions do not improve insurer underwriting performance then perhaps the potential

incentive conflicts raised by the use of contingent commissions outweigh any other value they

might have, and thus they should be eliminated.6

The purpose of this research is to evaluate the effectiveness of contingent commissions in

improving insurer underwriting performance. This is an important question because, as noted

above, several insurers have eliminated the use of contingent commissions and the largest

brokers have stated that they will not accept contingent commission payments. Further, both the

National Association of Insurance Commissioners (NAIC) and the National Conference of State

Insurance Legislators (NCOIL) have developed model laws regulating the use and disclosure of

contingent commissions that many states are considering adopting (Carson, et al., 2007). Most

recently, the NAIC has created a broker compensation task force with the charge to monitor

changes to broker compensation disclosure regulations across states (NAIC, 2009).

This is also an important question as an economic matter. Commissions and brokerage

fees represented just over ten percent of net premiums written in 2005, approximately $40

billion, and 41.4 percent of insurer underwriting expenses. However, contingent commissions

accounted for just under nine percent of total commission payments, but just 0.92 percent of

premium volume in 2005 (AM Best, 2006). Despite its relatively small nominal amount,

inefficiency in distribution compensation schemes can also have serious financial consequences.

We hypothesize that if contingent commission payments provide incentives for agents to

exercise discretion in underwriting that results in better risk selection and better matching of

client risk type with insurer risk appetite, then insurers using contingent commissions in the

6 One would expect that in a competitive market for agent services insurers would adopt optimal compensation

schemes, but to our knowledge, this has not been tested.

6

compensation scheme should achieve better underwriting results on average. We measure

underwriting performance using the loss ratio, the combined ratio and underwriting return on

equity ratio. Further, we expect that as the proportion of contingent commissions in the

compensation scheme increases, insurer underwriting performance should improve.

However, if the payment of contingent commissions results in higher expense ratios for

insurers, prices paid by consumers might be higher overall. This would be the case if the saving

from improved loss performance is more than offset by the increase in underwriting costs due to

commission payments to intermediaries. In that case combined ratios would be higher for

insurers that use contingent commissions.7 Our findings indicate that underwriting performance

as measured by the loss ratio is significantly better for insurers that use contingent commissions.

Further, as the proportion of contingent to total commission increases, underwriting performance

improves. Both the loss ratio and combined ratio are lower for insurers that use relatively more

contingent commissions, and the underwriting return on equity is significantly higher as

contingent commission use increases. These findings support the hypothesis that the use of

contingent commissions is effective in providing incentives to for agents to exercise discretion in

risk assessment so as to mitigate the asymmetric information problem between insurers and

policyholders.

The paper proceeds as follows. Section 2 details alternate insurance distribution methods

and compensation schemes, and analyzes incentive conflicts that might arise between insurers,

agents, and clients in the insurance transaction. We develop our hypotheses about the role of

contingent commissions here. In Section 3, our data and empirical methodology are discussed.

Section 4 presents results of our estimation, and Section 5 concludes.

7 The combined ratio is a common measure of underwriting profitability and is measured as the sum of the loss ratio

and the underwriting expense ratio. A lower combined ratio indicates greater underwriting profitability.

7

2. Insurance Distribution Channels and Compensation Schemes

The majority of property-liability insurance in the U.S. is sold through intermediated

channels.8 Principal-agent problems arise in the insurance transaction because the interests of the

three parties to the transaction—intermediaries, insurers and policyholders—are not perfectly

aligned. The nature of the principal-agent problem depends on the distribution model that is

used. There are a variety of ways that property-liability insurers can distribute their products to

clients. Direct channels include mass marketing and employee sales through branch offices. In

this case, there is no intermediary between the client and the insurer, and principal-agency

problems are minimized. Exclusive agency insurers rely on intermediaries who are autonomous

contractors representing the products of a single insurer under an agency contract.9 The insurer

owns the rights to the client expiration list upon severance of the relationship with the exclusive

agency.

Independent agency insurers also rely on autonomous contractors, but the agents

represent the products of several competing insurers. Insurers may also rely on insurance brokers

to distribute products. The chief distinction between independent agents and brokers historically

was that brokers had a legal duty to represent the interests of the clients first, while independent

agents were the legal representatives of the insurer. However, the legal difference is quite

blurred, and has become more so since 2004 with the adoption of the NAIC's Producer Licensing

Model Act (PLMA) by a majority of states. Under the PLMA, the regulatory distinction between

agents and brokers was eliminated, referring to both as insurance "producers". In practice, the

distinction between independent agency and brokerage is defined by the markets served by each

8 Jackson (2000) notes that just over 13% of property-liability insurance was sold through direct channels in 1999.

9 In practice, exclusive agents may represent the product of other insurers when those products are not offered by the

principal.

8

distribution system. Independent agents typically represent personal and small to mid-size

commercial clients, while brokers represent larger commercial clients with more complex

insurance needs. In addition, brokers may offer risk management or loss control consulting and

other services on a fee-basis. Importantly, under either traditional independent agency or

brokerage arrangements, the ownership of the client expirations list lies with the agent/broker

rather than the insurer. Note that we will refer to both brokers and independent agents as

independent agents throughout the remainder of this paper.10

The independent agent's role in distribution is to collect client risk information and

submit business to the insurer that most closely matches the insurer’s risk profile. Insurers differ

in the types of business they underwrite, and also in the terms and conditions offered in policies.

These latter differences are more important in more complex lines of business where policies are

not standardized. Independent agents may also provide claims settlement services, information to

clients on loss control and. often have the authority to bind insurers to coverage.

From the principal's (insurer's) perspective, there are two types of agency costs that are

important in insurance distribution. The first arises from asymmetric information between

insurers and agents about agent effort in placement, also known as moral hazard.11

If the insurer

cannot perfectly monitor agent effort in business production the agent may have incentives to

shirk. This incentive can be mitigated by paying the agent a flat commission based on the

volume of business placed with the insurer. Volume based contingent commissions may be paid

in addition to flat commissions to reward agents for meeting volume targets. The commission

rate may increase as higher volume targets are met (Cummins and Doherty, 2006; Wilder, 2002).

This type of contingent commission payment encourages agents to place enough business with

10

For completeness, we include an appendix that details the main property-liability distribution channels and the

differences among them. 11

Note that we are not interested in moral hazard in claiming on the part of the insured post-placement.

9

an insurer so that the insurer can capture economies of scale in its agency relationships. These

might also allow insurers to benefit from portfolio diversification by adding more risks to the

portfolio.

The second type of agency cost arises from asymmetric information between the potential

insured and the insurer. The underwriting process is designed to determine the risk class of a

potential insured and apply the appropriate price, such that actual losses are close to expected

losses. Unlike in most other industries, in property-liability insurance, the insurer’s profitability

depends on the risk characteristics of buyers, but true risk type cannot be known by the insurer

with certainty in advance of the sale. If an insurer cannot observe risk type directly, potential

insureds that are higher risk may have an incentive to hide their true risk type from the insurer so

as to qualify for a lower premium than would otherwise be applied if the true risk type were

known. In this case, the ―bad‖ risk would receive a premium subsidy, and might also purchase

more insurance than she otherwise would. Then, losses of the pool in which the ―bad‖ risks are

priced as average risk would be higher than anticipated by the premiums charged, and premiums

would not cover losses on average.

Thus, risk assessment is directly related to the insurer’s profitability. To operate

profitably, insurers must devise a cost-effective method for risk classification. Once risks are

assessed, policyholders can be offered products at prices that allow the insurer to cover losses,

the costs of risk assessment and other expenses, and earn a fair return on capital. One method of

risk assessment is to sort risk types based on classification variables that are observable and

verifiable at low cost. However, as risks become more complex, or as the costs of risk mis-

classification increase, this method may no longer be feasible.

10

To minimize adverse selection in this case, the insurer may rely on an agent to participate

in gathering and verifying risk information. Regan and Tennyson (1996) and Regan (1997) argue

that the optimal agent compensation scheme depends on both the complexity and underlying risk

associated with the exposure. Compensation methods that are linked to the insurer’s profitability

can induce the optimal level of risk assessment by agents so that agents will expend effort on risk

assessment when direct risk assessment by the insurer is more costly or less efficient. This will

ensure proper risk classification at lower cost, thus resulting in better performance for insurers.

Consumers will be better served as well since a proper match between consumers and insurers

may result in higher levels of customer satisfaction, and thus lower switching costs for

consumers. Contingent commissions may also provide incentives for agents to provide loss

mitigation services to reduce the frequency and / or severity of loss events, thus directly reducing

loss ratios (Dumm et al., 2006).

Eliminating contingent commissions may have adverse consequences for insurance prices

since agents will have less incentive to screen risks and match clients with appropriate insurers.12

If it is more costly for insurers to verify risk types, then insurers may pass this increased cost on

to consumers. If the insurer cannot distinguish between good and bad risks, it may set prices too

low, resulting in higher than expected loss ratios. Prices would then be likely to increase for all

exposures in the next period, regardless of true risk type. Alternatively, insurers may simply

place all risks into the "high risk" category. In this case the true high risks would be

appropriately priced, but the lower risk types will be over-charged and may reduce insurance

12

One argument against contingent commissions is that agents might have an incentive to under-report losses or to

actively interfere in loss settlement negotiations to the detriment of clients so as to maintain the profitability of the

book of business and thus qualify for the contingent commissions. This seems unlikely for several reasons. First,

agents are selling a service and rely on their reputations for repeat business. Second, even if reputation were not a

consideration, it seems unlikely that such systematic interference in the claims process would be undetected or even

tolerated by insurance claims department staff.

11

purchases or exit the market completely. Finally, insurers may restrict availability of coverage in

lines of business where the agent's role in risk classification is particularly important, such as

complex commercial lines.

Insurance agent compensation schemes thus consist of two parts. The first is a flat

percentage based on premium volume which is used to address potential moral hazard in agent

effort in placing business. There may be different flat rates paid for new and renewal business,

and rates differ significantly across insurers and across lines of business. Contingent

commissions are paid in addition to flat commissions, and may be based on profit, volume,

retention, or business growth, and are typically some combination of these (IIAA, 1991).

Contingent commissions are not payable on a per risk basis, but are allocated based on the

performance of the entire portfolio of business placed with a particular insurer. The contingent

commission schedule is known to agents at the beginning of the period, but contingent

commissions actually earned are calculated some period after business is placed and loss

experience is observed. The calculation of the profitability of the book of business is determined

by the insurer and is not subject to influence by the agent.

As noted above, contingent commissions may be effective in reducing insurers’ loss

ratios. However, one might argue that the payment of contingent commissions would increase

insurer underwriting expenses, and thus increase prices paid by policyholders. The Consumer

Federation of America (2004) argues that the payment of contingent commissions results in

higher costs for consumers. Cummins and Doherty (2006) show that commissions paid by

insurers are mostly passed through to policyholders in premiums charged. If contingent

commission payments benefit insurers through lower loss ratios, but result in higher combined

12

ratios13

then their use might be welfare reducing. Of course, this assumes that the higher expense

ratio does not reflect differences in services provided to consumers that are of value.

The discussion above indicates that the use of contingent commissions should be more

common in complex and more uncertain lines of business, and contingent commission use

should be related to improved insurer underwriting performance. Several researchers have

examined loss ratios and / or combined ratios as the measure of insurer underwriting

performance. For example, Lamm-Tennant and Starks (1993) examine differences in

underwriting risk across stock and mutual insurers using the both the loss ratio and the variance

in the loss ratio as measures of risk. Several studies examine loss ratios or combined ratios in the

context of underwriting cycles and insurer performance (see, for example, Venezian, 1985; Gron,

1994; Grace and Hotchkiss, 1995). Since we are interested in the role of compensation in

improving underwriting performance, we follow that method here and hypothesize that both loss

and combined ratio levels are sensitive to contingent commission payments. However, each of

these measures has been criticized as inaccurate because the denominator, premiums written, is

discounted for the time to loss payout, while the numerator is not.14

To ensure that this does not

bias our results, we also measure underwriting performance as the ratio of underwriting gains

(losses) for each period to insurer equity.15

This is similar to return on equity, a commonly used

measure of profitability for non–insurance firms. However, return on equity includes investment

income which is not related to underwriting performance. Therefore, we use a modified return on

13

The combined ratio is a measure of insurer underwriting profit for the current year, and includes both losses and

underwriting expenses, including commission expense payments. A combined ratio greater than one indicates that

insurers paid out more in losses and expenses than they collected in premium revenue. 14

One way to control for this effect is to use the economic loss ratio rather than the reported loss ratio. The

economic loss ratio makes an explicit adjustment for the loss payout profile of the insurer by applying discount

factors to premiums in each of the lines of business written. However, studies that use the reported loss ratio provide

results that are generally consistent with those that use the economic loss ratio, so any bias in our results should be

minor. 15

Note that we also control for the effect of discounting by using shares of business in short-tailed and long-tailed

lines as independent variables in the analysis.

13

equity measure, the underwriting return on equity, as an additional measure of underwriting

performance.

We test the following hypotheses:

H1: The use of contingent commission compensation is associated with greater

underwriting complexity.

H2: Underwriting performance is better for insurers that use contingent commissions in

the compensation structure.

H3: Underwriting performance improves as the proportion of contingent commissions in

the compensation scheme increases.

3. Data and Methodology

We use data drawn from the AM Best Property-Casualty statement file for the years 2001

through 2005. This allows us to measure insurer performance over a significant period of time,

and also captures the transition period beginning in 2004 when many larger insurers changed

their compensation plans in response to the investigations and legal settlements discussed above

regarding the use of contingent commissions16

. Our initial sample included all consolidated

groups and unaffiliated single insurers reporting data for each year. Because we are interested in

the effect of contingent commissions on property-liability insurers in general, we eliminated

professional reinsurers, credit and accident and health insurers, and insurers that specialize in

financial guarantee products. We also eliminated insurers that reported negative assets, liabilities,

or direct premiums written in any year. Our final sample consists of 1,998 observations for the

period.

3.1 Determinants of Contingent Commission Compensation

16

As a robustness test, we also estimated models that included only the years 2001 through 2003, and also estimated

regression models for each of these years separately. The results across these models are consistent with those that

are reported here.

14

As noted above, contingent commission payments should be used by insurers that focus

on more complex lines of insurance. This is because the agent’s efforts in risk assessment will be

more valuable than in standard lines. We estimate a binary dependent variable model where the

dependent variable is set equal to one if the firm pays contingent commissions, and zero

otherwise. The model is estimated using both probit and logistic regression. The probit model

assumes that the errors are normally distributed, while the logistic model assumes that errors

follow a logistic distribution.

To test the hypothesis that contingent commission payments should be used for more

complex lines of business, we include the share of business written by insurers in each of eight

lines of business. We include private automobile insurance liability and physical damage,

homeowners insurance, workers compensation, commercial multiperil, commercial general

liability, and inland marine insurance17

. These lines account for over 84 percent of net premiums

written in 2005, and represent a mix of personal and commercial lines of business. Within

commercial lines, these also reflect a range of complexity.

Prior research has shown that insurers using independent agency are more likely to use

profit contingent commissions (Regan and Tennyson, 1996). To control for differences in

insurers using different distribution systems, we include a dummy variable set equal to one if the

insurer is classified by the AM Best company as using either independent agency or brokerage

distribution, and zero otherwise. There is a large literature that examines the relationship

between ownership form and insurer risk and line of business strategy in insurance (see for

example Lamm-Tennant Starks, 1993; Mayers and Smith 1981, 1988). To control for possible

17

Inland marine insurance originally covered property risks associated with inland transportation of goods by rail,

road, or waterway. It has evolved to include a number of types of property subject to uncommon perils, and has

historically been exempt from state rate and form filing requirements. There is greater discretion required in

underwriting inland marine insurance than for most other commercial property insurance lines.

15

differences in underwriting strategy across insurers with different ownership structures, we

include a dummy variable set equal to one if the insurer is classified by AM Best as stockholder

owned, and zero otherwise.

The majority of firms in our sample are members of insurance groups. It is possible that

firms that are members of groups could reduce loss ratios by pooling losses and premiums with

other group members. Therefore, we include an indicator variable set equal to one to control for

group membership, and zero otherwise. Cheng et al. (2007) find a strong adverse stock market

reaction to the announcement that the contingent commission system was being challenged in

2004. This may indicate that equity investors believe that contingent commissions improve

insurer underwriting performance. Firms that are publicly traded may be expected by investors to

use contingent commissions in the compensation scheme or face equity prices that are

discounted by the market. To control for this we also include an indicator variable set equal to

one if the firm is publicly traded and zero otherwise.

As a substitute for compensating agents for risk assessment efforts, insurers may increase

advertising to their targeted markets. This may attract qualified risks that match the insurer’s

profit objectives at a lower cost. If this is the case, then advertising expenditures should be

negatively associated with the payment of contingent commissions. Advertising is measured as

the ratio of advertising expenditures to net premium written. Insurers might also incur costs in

conducting underwriting surveys or audits to directly observe client risks as a substitute for agent

efforts. Alternately, underwriting surveys and audits may complement the agents efforts in initial

risk assessment if the risk type is particularly complex. We include a variable called

underwriting surveys that is measured as the ratio of underwriting survey and auditing expenses

to net premiums written to capture this effect.

16

To control for other factors that might influence underwriting performance, we also

include variables that measure within-firm concentration and firm size. Within-firm

concentration is measured by summing the squared proportion of firm shares in each of fourteen

lines of business.18

A higher value for this index indicates a more specialized firm. A firm that is

specialized in one or a few lines may have superior underwriting information in those lines, and

so may see lower loss ratios on average. Of course, a firm that is highly specialized loses any

benefits of portfolio diversification, and may respond more sharply to exogenous shocks in the

underlying environment. Firm size as measured by assets is included to control for differences in

economies of scale in underwriting and in agency management across firms. This variable is

highly skewed and is transformed by taking the natural logarithm.

3.2 Contingent Commissions and Underwriting Performance

To test hypothesis 2, ordinary least squares regression is used to model underwriting

performance as a function of the set of independent variables described above and an indicator

for whether the insurer uses contingent commissions in the year of observation.19

We also

include additional control variables that are likely to be related to underwriting performance, but

that are not likely to be related to the decision to use contingent commissions. Because loss ratios

and net underwriting gains and losses are measured net of reinsurance, a variable that is specified

as the ratio of net to direct premiums written is included in the models. Underwriting results

might also be related to the insurer’s overall risk profile. Two common measures of insurer risk

are the premium to surplus ratio and the leverage ratio. The premium to surplus ratio is a

18

The lines of business used here are fire, allied lines, private passenger auto, commercial auto, homeowners,

commercial multiperil, workers compensation, medical malpractice, ocean marine, inland marine, burglary and

theft, boiler and machinery, fidelity and surety, and a composite "other " to capture premiums in the remaining lines

of business. 19

To test for selection bias we included the estimated coefficient for the probability of paying contingent

commissions generated by the binary regression models. The coefficient in the OLS regression was not significant,

indicating that selection bias is not a concern for our model.

17

measure of underwriting capacity and also reflects the insurer’s exposure to errors in pricing

(AM Best, 2009). As exposure to pricing errors increases, accurate risk assessment becomes

more important. The insurer’s risk profile increases with the premium to surplus ratio and

declines with the assets to liabilities ratio.

Our third hypothesis relates the payment of contingent commissions to improved

underwriting performance by analyzing only the subset of insurers that paid contingent

commissions during our period. We expect that underwriting performance improves as the ratio

of contingent commissions to total commissions paid increases.20

Ordinary least squares is used

to estimate a model for each of our measures of underwriting performance. All of the

independent variables above are included in the models. The ratio of contingent commissions to

total commissions paid is included as an additional predictor, while the indicator variable for the

payment of contingent commissions is dropped from this analysis.

We use three measures of underwriting performance. The loss ratio is measured as the

sum of losses and loss adjustment expenses incurred divided by net premiums written.21

The

combined ratio is measured as the sum of the loss ratio and the ratio of underwriting expenses,

including commission payments, to net premiums written. These two measures are highly

skewed and are transformed by the natural logarithm function.22

Underwriting return on equity is

20

It might be argued that there is an endogenous relationship between contingent commissions and our performance

measures. If that is the case, then the estimated coefficients for our contingent commission variable would be biased.

The Hausman test for endogeneity indicates that this is not a problem for our data. The estimated coefficient on the

residual for our contingent commission variable was not statistically significant, with a p-value of .56. 21

The loss ratio can also be measured using net premiums earned as the denominator. However, we found this

specification to be significantly noisier than using net premiums written in the denominator for our sample. Since

net premiums earned and written are highly correlated for the market as a whole, we should be able to make reliable

predictions using this specification. 22

Heteroscedasticity is a common problem when using firm level data in insurance. However, we performed tests to

detect heteroscedasticity, Goldfeldt-Quandt and Breusch-Pagan tests fail to reject the hypothesis of no

heteroscedasticity. Multicollinearity can be a concern in models using company level data. We tested for

multicollinearity in two ways. First, Pearson correlation coefficients were calculated for each variable pair, and none

were greater than 40%. Second, we calculated variance inflation factors for each variable in our regression model,

18

measured as the level of underwriting gains (losses) in year t to surplus in year t-1. All models

include year dummy variables to capture changes across time that might be associated with

underlying industry loss trends or with regulatory or legal interventions in the market. The

reference year is 2005.

The summary statistics for all the variables used in the analysis are shown in Table 1. The

sample is divided into two groups; those insurers that use contingent commissions and those that

do not. For those firms that pay contingent commission, the average ratio of contingent to total

commissions paid is 10.2 percent for our period. T-Tests are conducted to determine whether

there are statistically significant differences in the means of the variables used in this analysis for

firms that use contingent commissions and those that do not. Firms that use contingent

commissions show better underwriting performance on average than firms that do not. The

average loss ratio for firms that pay contingent commissions is 68.38 compared to 71.19 for

firms that do not use contingent commissions. Combined ratios are also lower, at just over 102

for firms that pay contingent commissions compared to 106.5 for those that do not. Each of these

differences is statistically significant at better than the one percent level. Although the

underwriting return on equity is higher for firms using contingent commissions on average, the

difference is not statistically significant.

Table 1 also shows that firms that pay contingent commissions are significantly larger as

measured by both net premiums and assets. These firms tend to be less concentrated by line of

business and spend relatively less on advertising as compared to insurers that do not offer

contingent commissions. As expected, firms that offer contingent commissions tend to be less

specialized in auto and homeowners insurance than those that do not pay contingent

and none of these were greater than 1.7. Therefore, we conclude that multicollinearity is not a problem for our data.

We also tested for autocorrelation in the time series, but Durbin-Watson statistics indicate that this is not a problem.

19

commissions. Each of these differences is statistically significant at the one percent level. Also

consistent with our hypotheses, the firms that pay contingent commissions are more likely to use

the independent agency distribution system, more likely to be publicly traded and more likely to

be members of insurance groups. While these results provide general support for our hypotheses,

more rigorous regression estimation allows us to control for the factors that affect the use of

contingent commissions and the impact of contingent commissions on underwriting performance

on a multivariate basis. The regression estimation results are discussed below.

4. Empirical Results

Recall that hypothesis 1 is that contingent commission compensation is more likely for

firms offering more complex products. The results of the models that test hypothesis 1 are shown

in Table 2. Logistic regression estimates are shown in Model 1, and probit estimates are shown

in Model 2. Results are consistent across both models. As expected, the probability of using

contingent commissions is positively associated with the share of business written in workers

compensation, inland marine, and commercial multiperil. However, there is also a positive and

significant relation between the share of homeowners insurance and the use of contingent

commissions. The estimated coefficients on these variables are statistically significant at the one

percent level. One explanation might be that homeowners insurance results are relatively more

volatile than most other lines because of the occurrence of natural catastrophes. It may be the

case that the payment of contingent commissions allows insurers to pass off some of the

volatility risk in their underwriting results, an area worth exploring further in a follow-on study.

There is no significant relation between the share of business in auto insurance or commercial

20

general liability insurance and the use of contingent commissions. These results suggest mixed

support for our hypothesis.

The results also indicate a strong negative relationship between the use of contingent

commission and insurer concentration and advertising. Insurers that are more specialized may

not need the services of agents in risk assessment if specialization allows them to develop

efficient risk assessment tools. Also, the negative relationship between advertising and the use of

contingent commissions suggests that insurers may use advertising to attract clients for which the

agent’s efforts in risk assessment are not important to profitability.

We find strong evidence that the use of contingent commissions is associated with

distribution system and ownership form. The estimated coefficient on the independent agency

distribution variable is positive and significant, indicating that independent agency insurers are

more likely to use contingent commissions in their compensation scheme. This supports the

findings in Regan and Tennyson (1996). Our results also show that stockholder owned insurers

are less likely to use contingent commissions, but that publicly traded (stockholder owned)

insurers are more likely to use contingent commissions. This difference may reflect the range of

stock ownership forms in the industry and is something that might be further investigated.

Table 3 reports the results of the regression models that estimate underwriting

performance as a function of whether the insurer pays contingent commissions in the period.

Model 1 uses the log of the loss ratio as the dependent variable, Model 2 uses the log of the

combined ratio, and Model 3 uses underwriting return on equity as the dependent variable for the

analysis. Results are generally consistent across models. The estimated coefficient for the

contingent commission indicator variable is negative and significantly associated with the loss

ratio in Model 1. This supports the hypothesis that the use of contingent commissions improves

21

underwriting performance. Although this negative relationship also holds for Model 2, the

estimated coefficient for the contingent commission indicator is not statistically significant. This

suggests that insurers that use contingent commissions have higher expense ratios, but do not

have higher combined ratios than insurers that do not use contingent commissions, and thus

premiums should not be higher for insurers that use contingent commissions, all else equal.

Model 3 shows no relationship between underwriting performance and the use of contingent

commissions for the period.

Table 4 presents the result of the regression models that relate the relative proportion of

contingent commissions used to underwriting performance. The sample includes only those

insurers that have positive contingent commission payments in any year. These results provide

strong support for hypothesis 3. Model 1 shows that the loss ratio declines as the proportion of

contingent commission increases. Model 2 shows that the combined ratio also declines as the

proportion of contingent commissions increases. This indicates that insures that use relatively

more contingent commissions in the compensation scheme do not have higher expense ratios on

average that other insurers that have positive contingent commission payments. Thus we would

expect not just a neutral effect, but a positive effect on premiums to policyholders or on insurer

profitability from the payment of contingent commissions. Model 3 also supports the hypothesis

that contingent commissions improve underwriting performance. Controlling for other factors

that might be expected to influence underwriting returns, the proportion of contingent

commission in the compensation scheme is positively related to the underwriting return on

equity. The estimated coefficient is statistically significant at the five percent level for our

sample.

5. Conclusion

22

Recent lawsuits and regulatory investigations since 2004 have resulted in several large

insurers modifying agent compensation systems and the largest brokers barred from accepting

contingent commissions. This research has examined the role of contingent commissions in

insurer underwriting performance. We first examine the determinants of the decision to use

contingent commissions in the compensation mix. We find mixed support for the hypothesis that

contingent commissions will be more likely to be used when firms offer more complex products.

We hypothesize that, if contingent commissions align agents’ incentives in risk assessment with

the business objectives of insurers, insurers that use contingent commissions in the compensation

scheme will have lower loss ratios and higher return on equity from underwriting, and will not

have higher combined ratios than those that do not. We also hypothesize that, as the proportion

of contingent commission in the compensation scheme increases, underwriting performance

should improve. We find strong support for this hypothesis for each of our underwriting

performance measures. This finding is robust after controlling for other factors that might

influence underwriting performance, including distribution system, ownership form, group

membership, intra-firm specialization, line of business mix, reinsurance, and insurer expenditure

ratios on advertising, risk surveys and audits and insurer risk levels.

This finding has important implications from both a public policy and economic

perspective. If regulatory or legislative measures mandate that contingent commissions may not

be used by insurers, then in the absence of another system that provides incentives for agents to

provide appropriate information in risk assessment, insurance prices would likely increase, and

insurer loss ratios might become more variable on average.

23

References

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Reexamination of the Cost Differential, Journal of Risk and Insurance, 59: 375-397.

Berger, Allen N., J. David Cummins, and Mary A. Weiss, 1997, The Coexistence of Multiple

Distribution Systems for Financial Services: The Case of Property-Liability Insurance, The

Journal of Business, 70: 515-546.

Carson, James, Randy Dumm, Robert Hoyt, 2007, Incentive Compensation and the Use of

Contingent Commissions by Smaller Distribution Channel Members, Journal of Insurance

Regulation, 25:

Cheng, Jiang, Elyas Elyasiani, and Tzuting Lin, 2007, Daily Return Behavior of the Property-

Liability Insurance Industry: The Case of Contingent Commissions, manuscript, Temple

University.

Cummins, J. David and Jack VanDerhei, 1979, A Note on the Relative Efficiency of Property-

Liability Insurance Distribution Systems, Bell Journal of Economics, 10: 709-719.

Cummins, J. David and Neil Doherty, 2006. The Economics of Insurance Intermediaries,

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D'Arcy, Stephen and Neil A. Doherty, 1990, Adverse Selection, Private Information, and

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Ghosh, Chinmoy, and James I. Hilliard, 2007, Attorney General Regulatory Enforcement:

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Insurance Cycle, Journal of Risk and Insurance, 62: 738-754.

Gron, Ann, 1994, Capacity Constraints and Cycles in Property-Casualty Insurance

Markets, Rand Journal of Economics, 25: 110-127.

Hoyt, Robert, E., Randy E. Dumm, and James M. Carson. 2006, An Examination of the Role of

Insurance Producers and Compensation in the Insurance Industry, manuscript.

Jackson, Donald R., 2000, One on One, Best's Review, 12: April

Joskow, Paul L., 1973, Cartels, Competition and Regulation in the Property-Liability Insurance

Industry, Bell Journal of Economics, 4: 375427.

24

Keeton, Robert E. and Alan I. Widiss, 1988, Insurance Law: A Guide to Fundamental

Principles, Legal Doctrines, and Commercial Practice, West Publishing Company St. Paul, MN

Lamm-Tennant, Joan and Laura Starks, 1993, Stock versus Mutual Ownership Structures:

The Risk Implications, Journal of Business, 66: 2946.

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Conflict Control in Insurance Markets, Journal of Business, 54:407-34.

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Casualty Insurance, Journal of Law and Economics, 31: 351-78.

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Marketing System, Journal of Law and Economics, 39: 637-666.

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Transaction Cost Approach, Journal of Risk of Insurance, 64: 41-62.

Regan, Laureen, 1999, Expense ratios Across Insurance Distribution Systems: An Analysis by

Lines of Business, Risk Management and Insurance Review, 2: 44-59.

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Insurance, Journal of Risk of Insurance. 52: 477-500.

25

Table 1

Sample Summary Statistics and T-Test for Differences In Means

Contingent Commission =1 Contingent Commission =0

Standard Standard

Variable Name Mean Deviation Mean Deviation

Loss Ratio 68.38 19.22 71.19 33.15 ***

Combined Ratio 102.02 23.13 106.48 39.97 ***

Underwriting Return on Equity -0.056 0.516 -0.092 0.551

Concentration 0.3735 0.2032 0.4345 0.269 ***

Advertising 0.0027 0.0053 0.0056 0.0201 ***

Underwriting Surveys 0.0082 0.008 0.0086 0.019

Natural Log (Assets) 12.17 2.18 10.91 2.02 ***

Net Premiums Written ($000) 782,625 2.48E+06 445,924 3.56E+06 ***

Net Reinsurance Ratio 0.8003 0.242 0.712 0.118

Assets to Liability Ratio 1.82 1.01 2.45 9.49 ***

Net Premium to Surplus Ratio 1.455 1.77 1.59 2.37

Personal Auto Share 0.17 0.2 0.205 0.272 ***

Homeowners Share 0.191 0.213 0.132 0.238 ***

Independent Agency Indicator 0.86 NA 0.64 NA

Stockholder Owned Indicator 0.458 NA 0.709 NA

Group Membership Indicator 0.592 NA 0.328 NA

Publicly Traded Firm Indicator 0.13 NA 0.069 NA

Contingent Commission Ratio 0.102

Number of Observations 1189 809

Loss Ratio is measured as the sum of losses and loss adjustment expenses divided by premiums

Combined Ratio is the sum of the loss ratio and the expense ratio

Concentration is the within-firm sum of shared squares across lines of business

Advertising is measured as the ratio of advertising expenditures to net premiums written ($000)

Underwriting Surveys is measured as the ratio of expenditures on underwriting surveys and audits to new premiums written ($000)

Net Reinsurance Ratio is measured as the ratio of net to direct premiums written

Underwriting Return on Equity is measured as the ratio of underwriting gains (losses) to surplus

Line of Business Shares are measured as premiums written in auto, homeowners, or workers compensation divided by net premiums written

Independent Agency indicator is equal to one if the insurer is identified as independent agency by AM Best

Stockholder Owned indicators is equal to one if the insurer is identified as stockholder owned by AM Best

Group Membership indicator is equal to one if the insurer is identified as a group by AM Best

Publicly Traded Indicator is equal to one if the insurer is identified as being publicly traded by AM Best

Table 2

Regression Estimation for the Use of Contingent Commissions

Dependent variable = 1 if contingent commissions are paid, 0 otherwise

Includes Year Effects

Estimated coefficients and standard errors

shown

Model 1 Model 2

Variable Logistic Estimation Probit Estimation

Intercept 4.24 0.5077 *** 2.31 0.3112 ***

Concentration -0.7904 0.2675 *** -0.716 0.161 ***

Advertising -10.55 5.53 ** -5.79 3.25 *

Underwriting Surveys and Audits -215.2 36.5 -24.72 39.64

Natural Log (Assets) 0.3063 0.0395 *** 0.183 0.024 ***

Personal Auto Share 0.467 0.383 0.179 0.173

Homeowners Share 1.442 0.282 *** 0.757 0.101 ***

Workers Compensation Share 3.717 0.957 *** 2.32 0.584 ***

Commercial General Liability Share 0.013 0.405 0.11 0.252

Commercial Multiperil 4.42 0.453 *** 3.67 0.387 ***

Inland Marine Share 4.622 0.828 *** 2.34 0.474 ***

Independent Agency Indicator 1.95 0.142 *** 1.1 0.083 ***

Stockholder Owned Indicator -1.32 0.1227 *** -0.734 0.075 ***

Group Membership Indicator 0.518 0.148 *** 0.186 0.091 **

Publicly Traded Firm Indicator 0.322 0.185 * 0.229 0.121 **

Likelihood Ratio 780.54 641.62

Match Rate 83.10% 81.90%

Pseudo R-squared 73.9 76.2

Note: ***,**,* indicate statistical significance at the 1, 5, and 10% levels respectively.

Indicator variables for each year are included in the model but their estimates are not reported here

Concentration is the within-firm sum of shared squares across lines of business

Advertising is measured as the ratio of advertising expenditures to net premiums written ($000)

Underwriting Surveys is measured as the ratio of expenditures on underwriting surveys and audits to new premiums written

($000)

Line of Business Shares are measured as premiums written in a line divided by total net premiums written

Independent Agency indicator is equal to one if the insurer is identified as independent agency by AM Best

Stockholder Owned indicators is equal to one if the insurer is identified as stockholder owned by AM Best

Group Membership indicator is equal to one if the insurer is identified as a group by AM Best

PubliclyTraded Indicator is equal to one if the insurer is identified as being publicly traded by AM Best

Table 3

OLS Regression Results: Contingent Commission Payment and Underwriting Performance

All Models Include Year Effects (estimated coefficients and standard errors shown)

Model 1 Model 2 Model 2

Dependent Variable Log(Loss Ratio) Log(Combined Ratio)

Underwriting Return on

Equity

Independent Variables

Intercept 3.63 0.0715 *** 4.37 0.0544 *** 0.38 0.097 ***

Concentration 0.1247 0.0392 *** 0.0673 0.03 ** -0.027 -0.0537

Advertising -2.669 0.5787 *** -2.54 0.39 *** -1.34 0.698 **

Underwriting Surveys 3.002 0.5228 *** 2.31 0.287 *** -0.912 0.466 **

Natural Log (Assets) 0.042 0.0056 *** 0.0131 0.0043 *** -0.0038 0.0077

Personal Auto Share 0.2117 0.042 *** -0.0403 0.032 0.0074 0.0574

Homeowners Share 0.176 0.041 *** 0.0641 0.0317 ** -0.327 0.057 ***

Workers Compensation Share 0.191 0.129 -0.051 0.099 -0.3 0.178 *

Commercial General Liability Share 0.062 0.06 *** 0.0065 0.045 ** -0.161 0.082 **

Inland Marine Share -0.485 0.112 *** -0.158 0.082 ** -0.177 0.147 ***

Independent Agency Indicator -0.065 0.019 *** -0.0081 0.015 0.078 0.027 ***

Stockholder Owned Indicator 0.009 0.0178 0.00512 0.014 -0.065 0.025 ***

Group Membership Indicator -0.055 0.0216 ** -0.032 0.0165 ** 0.0513 0.029 *

Publicly Traded Firm Indicator -0.0082 0.0215 -0.0012 0.0212 -0.037 0.03

Net Reinsurance Ratio -0.0026 0.0106 -0.0137 0.00739 * -0.0017 0.0013

Assets to Liability Ratio 0.00225 0.0144 0.00755 0.00107 *** 0.0019 0.016

Net Premium to Surplus Ratio -0.021 0.00375 *** -0.00152 0.00287 -0.166 0.051 ***

Contingent Commission Indicator -0.0369 0.0179 ** -0.108 0.0137 -0.014 0.0246

Model F-Statistic 23.31 *** 14.26 *** 48.5 ***

adjusted R-square 0.224 0.189 0.375

Note: ***,**,* indicate statistical significance at the 1, 5, and 10% levels respectively. Indicator variables for each year are included in the model but their estimates are not reported here

29

Table 4

OLS Regression Results: Contingent Commission Payment Proportion and Underwriting Performance

(Firms with Positive Contingent Commissions, n=1191)

All Models Include Year Effects (estimated coefficients and standard errors shown)

Model 1 Model 2 Model 2

Dependent Variable Log(Loss Ratio) Log(Combined Ratio)

Underwriting Return on

Equity

Independent Variables

Intercept -2.91 0.176 *** -0.886 0.098 *** 0.394 0.109 ***

Concentration 0.441 0.0986 *** 0.254 0.055 *** -0.066 0.0618

Advertising -8.32 3.26 *** 3.09 0.811 *** 1.25 2.02

Underwriting Surveys 12.54 1.18 *** 7.41 0.818 *** 0.108 0.732

Natural Log (Assets) 0.15 0.012 *** 0.059 0.0076 *** -0.0068 0.0076

Personal Auto Share 0.0248 0.112 -0.0556 0.059 0.205 0.069 **

Homeowners Share -0.33 0.101 *** -0.331 0.0583 *** -0.234 0.062 ***

Workers Compensation Share 1.48 0.304 *** 1.07 0.183 *** -0.243 0.189

Commercial General Liability Share 1.43 0.169 *** 0.544 0.087 *** -0.002 0.105

Inland Marine Share -1.18 0.207 *** -0.087 0.148 -0.107 0.129

Independent Agency Indicator 0.165 0.051 *** 0.093 0.0267 *** 0.08 0.031 ***

Stockholder Owned Indicator -0.03 0.039 -0.013 0.025 -0.35 0.024

Group Membership Indicator 0.027 0.045 0.0046 0.03 0.051 0.028 *

Publicly Traded Firm Indicator -0.026 0.055 -0.01 0.038 -0.055 0.036

Net Reinsurance Ratio -0.117 0.074 * -0.00187 0.0147 0.087 0.046 **

Assets to Liability Ratio 0.071 0.0171 *** 0.00577 0.0029 ** -0.341 0.011 ***

Net Premium to Surplus Ratio -0.047 0.009 *** -0.0039 0.0052 0.266 0.0057 ***

Contingent Commission Proportion -0.0054 0.0016 *** -0.00398 0.0012 *** 0.00255 0.0009 **

Model F-Statistic 57.21 *** 37.05 *** 101.19 ***

adjusted R-square 0.535 0.298 0.6689

Note: ***,**,* indicate statistical significance at the 1, 5, and 10% levels respectively.

Indicator variables for each year are included in the model but their estimates are not reported here

30

General Characteristics of Property-Casualty Insurance Distribution Channels23

Salaried Salesforce Exclusive Agency Independent Agency Agency / Broker

Agency Relation Insurer Insurer Insurer Insurer / Client

Multiple Insurers Represented? No No Yes Yes

Compensation from Insurer Salary Commission Commission Commission

Placement No Yes Yes Yes

Profit -Sharing Varies Not typical Yes, based on loss ratio Varies

retention, and growth rate

Volume Bonus Yes Yes Built into contingents Yes, (Market

service agreements)

Compensation from Clients No No No Fee-for-service

Example Insurer GEICO, State Farm Chubb AIG

Liberty Mutual

__________________________________________________________________________________________________________________

Service provided by independent agents and brokers include: Client risk analysis, shopping for appropriate coverage, policy administration

and issuance, premium collection, and claims administration. In addition, independent agents typically have authority to bind the insurer to

coverage without the insurer's prior approval. This is not generally the case for brokers with agency contracts with insurers.

Large commercial property-casualty brokers may also provide risk management services, including alternative risk transfer, loss control and

risk assessment, and crisis management. These are typically provided on a fee-basis.

23

This chart was originally prepared by Laureen Regan for presentation to the NCOIL annual meeting in March, 2005. Used with permission of the Griffith

Foundation for Insurance Education.