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Combined Ratio (Insurance) – Definition

Combined Ratio (Insurance) Definition

The combined ratio is a simplified measure used by an insurance company to evaluate its profitability as well as financial health as a way of measuring its day-to-day performance. The combined ratio is calculated by dividing the sum of claim-related losses and expenses by earned premium. The earned premium is the money that an insurance company collects in advance in lieu of guaranteed coverage.

Combined Ratio = (Claim-related Losses + Expenses) / Earned Premium.

From the above formula, it can be inferred that the combined ratio is inversely proportional to the profitability of an insurance company. Thus, it is in the best interest of the company to maintain a low combined ratio of losses and expenses relative to premiums earned, so as to maximize its profitability.

A Little More on What is a Combined Ratio

The combined ratio gives a fairly accurate estimate of the cash outflow of an insurance company. Typically, the cash outflow includes disbursed dividends, claim-related losses and general business expenses. As such, the combined ratio has proved indispensable in evaluating  the efficiency of the insurer in driving revenue growth.

The combined ratio is usually indicated as a percentage – an insurance firm that has a combined ratio below 100% can be said to have made an underwriting profit, i.e. the total sum of money paid out in claims plus the amount spent as business expenses is lesser than the total amount received in premiums from customers. Similarly, if the combined ratio exceeds 100%, the firm is making a loss, i.e. the total sum of money paid out in claims plus the amount spent as business expenses is greater than the total amount received in premiums.

It is important to note here that apart from the actual monies paid out in claims, the incurred losses of an insurance firm should also include the change in loss reserves. Loss reserves are claims that have not been paid out yet by the insurer. Expenses include general expenses (i.e. the costs a business incurs as part of its daily operations), loss adjustment expenses (i.e. the various expenses associated with investigating and settling claims), and miscellaneous underwriting expenses. A premium is the fee that a customer pays for insurance coverage during the signing of the insurance contract. Such a premium is considered unearned by the insurance firm at the time of payment. With the expiration of phases of the coverage period, the insurance firm converts a matching portion of the unearned premium into earned premium, thus reducing the total unearned premium amount.

Combined ratios are generally considered a reliable standard for measurement of an insurance company’s financial health. This is because combined ratios typically evaluate profitability solely from the perspective of the company’s insurance operations. However, insurance firms have several other sources of revenue besides customers’ premiums. Insurance firms earn a sizeable portion of their revenues from investments in stocks, bonds, and other financial instruments outside their core business of selling insurance policies. As such, there are instances where a company that has a combined ratio greater than 100% is still able to make a profit from investment income.

Illustration of Combined Ratio

Let us consider an insurance firm C1. Now, suppose C1 has collected $10,000 in insurance premiums, paid out $7,500 in claims and spent $3,000 towards operating expenses. In this instance, C1‘s combined ratio can be calculated as follows.

Combined ratio of C1 = ($7,500 + $3,000) / $10,000 = $10,500 / $10,000 = 105%.

In the above example, C1 is making an underwriting loss since its combined ratio is greater than 100%. Now, let us consider another example.

Insurance firm C2 has incurred underwriting expenses worth $7,000, paid out $1000 in claims and lost $1500 as loss adjustment expenses. If C2 earns $10,000 in premiums during the same period, then its combined ratio can be calculated as follows.

Combined ratio of C2 = ($7000 + $1,000 + $1,500) / $10,000 = $9,500 / $10,000 = 95%.

Thus, in the above example, C2 is making an underwriting profit since its combined ratio is less than 100%.

Limitations of Combined Ratio

Notwithstanding its several advantages, the combined ratio does have its limitations. The various components that make up the combined ratio (losses, expenses and earned premium) each serves as an indicator of the potential for profitability or the risk of unprofitability. As such, it is necessary to scrutinize these components individually as well as collectively in order to correctly evaluate the company’s financial performance.

References for Combined Ratio

http://www.businessdictionary.com/definition/accident-and-health-combined-ratio.html

https://www.investopedia.com/terms/c/combinedratio.asp

Academic Research

A portfolio approach to the property-liability insurance industry, Kahane, Y., & Nye, D. (1975). A portfolio approach to the property-liability insurance industry. Journal of Risk and Insurance, 579-598. This paper contains an analysis of a portfolio model which simultaneously optimizes the investment and insurance portfolios of the property-liability insurance industry. The mathematical formulation is an extension of earlier approaches in that it permits the direct development of the envelope efficiency frontier for all levels of insurance leverage. Using data on nineteen insurance lines and two types of assets for the period 1956-1971, efficient portfolios for both unconstrained and also constrained solutions are obtained. In each case, some insurance lines tend to be consistently excluded from the optimal portfolios because of their risk-return characteristics. The implications of this effect on the availability of insurance and rate-making are discussed. Finally, in contrast to accepted practice and theory it is found that the investment policy of the firm need not necessarily become more conservative as the insurance portfolio becomes more risky.

A reexamination of the corporate demand for reinsurance, Cole, C. R., & McCullough, K. A. (2006). A reexamination of the corporate demand for reinsurance. Journal of risk and Insurance, 73(1), 169-192. This study examines the effect of the state of the international reinsurance market on the demand for reinsurance by U.S. insurers using data from the years 1993 through 2000. Both the overall demand for reinsurance and the utilization of foreign reinsurance by U.S. insurers are explored. In addition to supporting the findings of prior literature related to the traditional motives for the corporate demand for insurance, evidence indicates that the state of the U.S. reinsurance industry impacts the amount of reinsurance demanded by U.S. insurers. The study also investigates reasons why U.S. insurers utilize a reinsurance program composed of both U.S. and foreign reinsurers. The results indicate that the decision to utilize some percentage of foreign reinsurance is driven primarily by the financial and operational characteristics of the ceding company such as firm size, group affiliation, and organizational form. However, no support is found for the hypothesis that possible differences between the foreign and U.S. reinsurance markets impact the decision to utilize foreign reinsurance.

Economic and market predictors of insolvencies in the life-health insurance industry, Browne, M. J., Carson, J. M., & Hoyt, R. E. (1999). Economic and market predictors of insolvencies in the life-health insurance industry. Journal of Risk and Insurance, 643-659. This study identifies factors exogenous to individual insurers that are statistically related to the overall rate of life-health insurer insolvencies. This is a departure from the methodologies of prior studies, which have focused primarily on firm-specific characteristics in assessing insolvency risk. Empirical analysis is based on quarterly data from 1972 through 1994. Results indicate that life-health insurer insolvencies are positively related to increases in long-term interest rates, personal income, unemployment, the stock market, and to the number of insurers, and negatively related to real estate returns. Findings support the hypothesis that economic and market variables are important predictors of life-health insurer failure rates.

International insurance cycles: Rational expectations/institutional intervention, Lamm-Tennant, J., & Weiss, M. A. (1997). International insurance cycles: Rational expectations/institutional intervention. Journal of Risk and Insurance, 415-439. This study further substantiates the presence of insurance underwriting cycles and analyzes their causes. A generalized least squares analysis of changes in premium levels is used to test the rational expectations/institutional intervention hypothesis across countries as well as within each country. We also examine the relation between cycle length and the market/institutional features of each country. Finally, a logistic model is used to predict the presence of a cycle based on the market/institutional features. The results suggest that the rational expectations/institutional intervention hypothesis explains many aspects of the underwriting cycle, including cycle length

Economies of scope in financial services: A DEA efficiency analysis of the US insurance industry, Cummins, J. D., Weiss, M. A., Xie, X., & Zi, H. (2010). Economies of scope in financial services: A DEA efficiency analysis of the US insurance industry. Journal of Banking & Finance, 34(7), 1525-1539. This paper investigates economies of scope in the US insurance industry over the period 1993–2006. We test the conglomeration hypothesis, which holds that firms can optimize by diversifying across businesses, versus the strategic focus hypothesis, which holds that firms optimize by focusing on core businesses. We analyze whether it is advantageous for insurers to offer both life-health and property-liability insurance or to specialize in one major industry segment. We estimate cost, revenue, and profit efficiency utilizing data envelopment analysis (DEA) and test for scope economies by regressing efficiency scores on control variables and an indicator for strategic focus. Property-liability insurers realize cost scope economies, but they are more than offset by revenue scope diseconomies. Life-health insurers realize both cost and revenue scope diseconomies. Hence, strategic focus is superior to conglomeration in the insurance industry.

Impact of new multiple line underwriting on investment portfolios of property-liability insurers, Lambert, E. W., & Hofflander, A. E. (1966). Impact of new multiple line underwriting on investment portfolios of property-liability insurers. The Journal of Risk and Insurance, 33(2), 209-223.

An investigation of the performance of the US property-liability insurance industry, Chidambaran, N. K., Pugel, T. A., & Saunders, A. (1997). An investigation of the performance of the US property-liability insurance industry. Journal of Risk and Insurance, 371-382. This article presents an empirical analysis of the economic performance of the U.S. property-liability insurance industry, using estimations across 18 lines of insurance for the years 1984 through 1993. It adopts an industrial organization approach, focusing on the economic loss ratio as a measure of pricing performance. The concentration ratio for the line and the share of direct writers in the line are both found to be sig- nificant determinants of performance. The results are consistent with shortcomings in competition in some insurance lines.

An examination of cost economies in the United States life insurance industry, Grace, M. F., & Timme, S. G. (1992). An examination of cost economies in the United States life insurance industry. Journal of Risk and Insurance, 72-103. Using an industry sample of 423 U.S. life insurers, this study reports estimates of overall and product specific scale economies, as well as, pair-wise cost complementarities for a wide variety of products. Estimates of these cost characteristics are provided for numerous output vectors since theory suggests that the magnitude of scale economies and cost complementarities may vary with the scale and mix of outputs. In contrast, previous studies only provide a single point estimate of industry cost characteristics using the sample mean output vector. This study, therefore, provides a more complete representation of the industry’s cost characteristic and, in turn, new insights into decisions related to the optimal scale and mix of outputs.

Forecasting and analyzing insurance companies’ ratings, Van Gestel, T., Martens, D., Baesens, B., Feremans, D., Huysmans, J., & Vanthienen, J. (2007). Forecasting and analyzing insurance companies’ ratings. International Journal of Forecasting, 23(3), 513-529. Insurance companies sell protection to policy holders against many types of risks: property damage or loss, health and casualties, financial losses, etc. In return for this risk protection, insurance companies receive a premium from the policy holder, which is used to cover expenses and the expected risk. For longer-term risk protections, part of the premiums are invested to get higher yields. Although the protection buyer mitigates the individual risk to the large and better diversified portfolio of the insurer, it does not mean that the risk is completely reduced since the insurer may default his obligations. Insurers need to have sufficient equity or buffer capital to meet their obligations in adverse conditions when their losses on the diversified portfolio exceed the expected losses. Ratings provide an assessment of the ability of the insurer to meet its obligations to policy holders and debt holders. In this paper, the relationship between financial ratios and the rating is analyzed for different types of insurance companies using advanced statistical techniques that are able to detect non-linear relationship. The resulting rating model approach is similar to the approach for a low default portfolio, which uses a common set of explanatory variables (such as capitalization, profitability, leverage and size) which is generally applicable for all insurance types, and is complemented with insurance type specific ratios. The resulting model is found to yield a good accuracy, with 75% of the model ratings differing at most one notch from the external rating.

Reinsurance and capital structure: Evidence from the United Kingdom non‐life insurance industry, Shiu, Y. M. (2011). Reinsurance and capital structure: Evidence from the United Kingdom nonlife insurance industry. Journal of Risk and Insurance, 78(2), 475-494. Using a data set consisting of statutory returns of U.K. non‐life insurers from 1985 to 2002, I find that insurers with higher leverage tend to purchase more reinsurance, and insurers with higher reinsurance dependence tend to have a higher level of debt. My results are consistent with the expected bankruptcy costs argument, agency costs theory, risk‐bearing hypothesis, and renting capital hypothesis. I also find that the impact of leverage on reinsurance will be weaker for insurers that use more derivatives than those that use less. Moreover, high levels of derivative use increase the leverage gains attributable to reinsurance.

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