PERFORMANCE OF THE CROATIAN INSURANCE COMPANIES - MULTICRITERIAL APPROACH

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1 PERFORMANCE OF THE CROATIAN INSURANCE COMPANIES - MULTICRITERIAL APPROACH Davorka Davosir Pongrac Zagreb school of economics an management Joranovac 110, Zagreb avorka.avosir@zsem.hr Višna Vovoić Rosenzweig Zagreb school of economics an management Joranovac 110, Zagreb vovoic.visna@gmail.com Hrvoe Volarević Zagreb school of economics an management Joranovac 110, Zagreb hrvoe.volarevic@zsem.hr Abstract This paper will perform a multi-criteria analysis of the insurance sector in the Republic of Croatia. The analysis is performe base on five inicators for the eight largest insurance companies in Croatia. The multicriteria business performance is calculate with use of a score, the weighte sum of relative values of inicators. The score is obtaine by calculating weights as a solution of a goal programming problem. The goal of a specific insurance company is to increase the value of an inicator in comparison to it s value a year before. Hence, some insurance companies have more goals that they wish to obtain. The results reveal that the Croatian insurance sector has given the highest priority to return on investment an return on equity for Key wors: Insurance Companies, Goal Programming, Multicriteria performance, Ranking, Profitability 1. INTRODUCTION This paper analyses the business performance of insurance companies, specific non-eposit financial institutions that eal with collecting an unerwriting risk. Collecting risk allows the insurance companies to recoup policyholers that sustaine acciental amages, that are insure. The financial buren is ivie on all the members of the risk community. In view on the specificity of their 142

2 business, insurance companies keep accounts an financial recors in their own specific way that is ictate by the regulations of the Croatian Financial Services Supervisory Agency (CFSSA). Taking that into account, the analysis of their success is obtaine by using financial inicators that are moifie to the peculiarities of the insurance sector, an iffer from other classical inicators that are use in the financial sector (Toby, 2011). The Croatian insurance sector for consiste of 28 insurance an reinsurance companies. The share of their assets consiste of 6,1% 1 of all assets of financial institutions at the en of Base on their market share, this paper observes the business performance of the eight largest insurance companies. Gross written premium is use as the inicator that represents market share. The following insurance companies are observe: Jaransko osigurane.., Basler osigurane Zagreb.., Euroherc osigurane.., Croatia osigurane.., Allianz Zagreb.., Kvarner Vienna Insurance Group.., Triglav osigurane.. an Grawe Hrvatska.. Among above mentione companies, two of them provie only non-life insurance services, while the other ones provie both, life an non-life insurance services. The observe insurance companies generate 78,3% of the total gross written premium in an 77,6% of the total gross written premium for The inicators are erive from the financial reports of the insurance companies for two consecutive years, 2010 an The five chosen financial business inicators are those that the CFSSA uses in their annual reports. The first criterion is the combine ratio which shows operating results before incluing income from investments. The secon criterion is return on investment that shows net income from investments for every 100 investe units. The thir criterion is ebt ratio which shows the amount of assets finance by liabilities which o not inclue capital an reserves. The fourth criterion is return on equity (ROE) showing how much net profit of the accounting perio can be generate by 100 units of equity. The fifth an last criterion is the market share inicator that represents the share of a single insurance company in the insurance market. All five inicators are calculate taking into account the whole performance of insurance companies, ie for companies that provie life an non-life insurance, both lines of business are taken into consieration. The purpose of this research is a multicriteria analysis of insurance companies business in the The Republic of Croatia using the above mentione inicators. The multicriteria business performance is calculate with the use of a score, the weighte sum of relative values of inicators. Since the weight values epen on subective assesment, this paper proposes the evaluation of inicator values using goal programming. The goal of a specific insurance company is formulate on the assumption of what 1 source: Croatian National Bank 143

3 is their strategy for the observe perio. For that goal the insurance company oes not want to eviate from. The approach here iffers from the approach in previous papers (Garcia, F., Guiarro F., Moya I. 2010), (Vovoić Rosenzweig, V., Volarević, H., Varović, M., 2011), in view of the chosen sector an the number of goals for the insurance companies. The calculate inicator values show what was the multicriteria performance of the insurance companies for the given year. The insurance companies goals in the first moel are inicator values that have increase in relation to the values from the year before. The goal in the secon moel is the maximum score for every insurance company. For the remaining inicators it is assume that the insurance companies strategy i not force their improvement. The score, as an insurance company multicriteria business performance, shoul be as close to the given goals as possible. The istance is calculate using the enhance Chebyshev norm or the Dinkelbach-Isermann norm. By solving the given goal programming moel we obtain the weights assigne to iniviual inicators an the score of every specific insurance company. The paper consists of five sections. The first section is the introuction. The secon section escribes the specific inicators that are use as criteria neee for the analysis in the business performance of insurance companies. In the thir section the goal programming moel is formulate that is applie on inicator values. The fourth section prouces the results of the analysis, while the closing consierations are in the fifth section. 2. INSURANCE BUSINESS INDICATORS SELECTION In orer to apply a multicriteria approach using goal programming, we nee to select inicators, i.e. criteria. Five insurance business inicators are selecte in this paper, which CFSSA uses in their annual reports. The inicators are as follows: 1. The combine ratio is the sum of the claims ratio an expense ratio an it shows operating results before incluing income from investments. The claims ratio is the ratio of the sum of claims pai, changes in claim provisions an changes in other technical provisions (incluing changes in life assurance technical provisions when the policyholer bears the investment risk) to insurance premiums earne multiplie by 100, with net value of reinsurance being inclue into the calculation. The expense ratio is the ratio of the sum of operating expenses (acquisition costs an aministrative costs) an other technical charges to gross written premium, reuce by premiums cee to reinsurance, multiplie by

4 Y 1 claims pai changes in provisions changes in other technical provisions combine ratio *100 premiums earne operating expenses other technical charges gross written premium - premiums cee to reinsurance 2. Return on investment is calculate as the ratio of income from investments reuce by investments expenses to the amount of investment, multiplie by 100. *100 Y 2 investment income - investment expenses return on investment *100 amount of investment 3. The ebt ratio is calculate as the ratio of total liabilities to total assets. This ratio shows the amount of assets finance by liabilities which o not inclue capital an reserves. Y 3 total liabilities - capital an reserves ebt ratio *100 total assets 4. Return on equity (ROE) represents the relationship between after-tax profit or loss of the accounting perio an equity (subscribe capital, premium on shares issue, revauation reserves, reserves an accumulate profit or loss). It is expresse as a percentage, showing how much net profit of the accounting perio can be generate by 100 units of equity. Y 4 after - tax profit or loss ROE *100 equity 5. Market share inicators represents the share of each insurance company in the total insurance market. Gross written premium is use as a market share inicator in this analysis. Y 5 gross written premium of insurance company market share inicator *100 total gross written premium Table 1. The inicator values of the selecte insurance companies for Y 1 Y 2 Y 3 Y 4 Y 5 Jaransko 89,650 2,358 64,610 7,588 6,900 Basler 132,933 3,289 93,356-43,940 4,400 Euroherc 96,202 3,690 70,516 11,263 10,800 Croatia 102,157 2,586 78,697 2,638 31,400 Allianz 109,134 6,282 84,707 15,227 10,600 Kvarner VIG 135,666 6,502 94,499-5,220 5,500 Triglav 116,546 5,513 87,386-20,979 4,400 Grawe 136,825 6,114 90,960 10,214 Source: Authors results 4,

5 By using the formulas mentione above, we obtaine the values of the five chosen inicators for the eight selecte insurance companies for the given perio of two years. 2 They are shown in tables 1 an 2. Table 2. The inicator values of the selecte insurance companies for Y 1 Y 2 Y 3 Y 4 Y 5 Jaransko 88,755 3,146 61,328 13,740 7,000 Basler 138,534 2,331 91,255-58,024 4,500 Euroherc 86,023 4,054 67,852 20,108 10,900 Croatia 113,878 4,250 78,960 4,794 30,500 Allianz 104,057 6,142 85,166 18,901 11,200 Kvarner VIG 160,795 1,512 87,320-41,507 4,900 Triglav 109,308 4,186 87,620 0,533 4,300 Grawe 137,503 7,081 90,475 12,477 Source: Authors results 4,300 The first an the thir criteria are cost criteria, that means that it is preferable that their values are as small as possible. The secon, fourth an fifth criteria are benefit criteria, that means that it is preferable that their values are as large as possible. It is neccessary that all the criteria in the table are either benefit or cost criteria, so we transform the cost criteria into benefit criteria by calculating their reciprocal values. The obtaine benefit criteria are transforme into their relative values in orer for them to be in the same measuring units. The relative values of the criteria are obtaine by stanarizing the empirical values with the following relation: x i y y i max - y min min y As in Garcia, Guiarro an Moya (2010). The stanarise inicator values are shown in tables 3 an 4. Table 3.The stanarise inicator values of the selecte insurance companies for /X 1 X 2 1/X 3 X 4 X 5 Jaransko 1,000 0,000 1,000 0,871 0,096 Basler 0,056 0,225 0,026 0,000 0,004 Euroherc 0,802 0,321 0,735 0,933 0,240 Croatia 0,645 0,055 0,434 0,787 1,000 Allianz 0,482 0,947 0,250 1,000 0,232 Kvarner VIG 0,016 1,000 0,000 0,654 0,044 Triglav 0,331 0,761 0,176 0,388 0,004 Grawe 0,000 0,906 0,084 0,915 Source: Authors results 0,000 2 Data source for inicators calculation are Annual Reports of the selecte insurance companies. 146

6 Table 4. The stanarise inicator values of the selecte insurance companies for /X 1 X 2 1/X 3 X 4 X 5 Jaransko 0,934 0,293 1,000 0,918 0,103 Basler 0,185 0,147 0,000 0,000 0,008 Euroherc 1,000 0,456 0,707 1,000 0,252 Croatia 0,474 0,492 0,319 0,804 1,000 Allianz 0,627 0,831 0,147 0,985 0,263 Kvarner VIG 0,000 0,000 0,092 0,211 0,023 Triglav 0,542 0,480 0,085 0,749 0,000 Grawe 0,195 1,000 0,018 0,902 Source: Authors results 0, GOAL PROGRAMMING APPROACH In a multicriteria problem, with five benefit criteria, the Pareto optimal solution or an efficiant solution is the solution which is not ominate by any other solution (Ehrgott, M., Klamroth, K., Schwehm, C. 2004). In this paper the solution is an insurance company. That is why the comparison of the relative value vectors easily show us which insurance companies are not efficient. In Basler osigurane is inefficient because it is ominate by Jaransko osigurane, because the value of every note inicator for Jaransko osigurane is greater than the value of Basler in the same inicator. Also Kvarner VIG is not efficient because it ominate by Euroherc osigurane an Triglav osigurane is ominate by Allianz. The remaining insurance companies that are not ominate by any other insurance company are efficient. This means we can not say which one is the best. That is why we introuce the score in the usual way, that is use most often in literature, ie the weighte value of inicator relative values. That is why the selection of weights efines the ranking of an insurance company base on the total amount of points obtaine by the score. In orer to avoi any subectivity, we formulate the goal programming moel. The goal reflects the strategy of the insurance company for the given year, where their managment have to esignate which business segment nees improvement. The notations in the formulate moel are as follows: 1. i insurance company, i = 1,..., inicator = 1,..., w weight of criteria, = 1,..., x i relative value of inicator of insurance company i, i = 1,..., 8; = 1,..., S i score of insurance company i, i = 1,..., g goal k of insurance company i, i = 1,..., 8; k = 1,, negative eviations from the goal k of the insurance company i, i = 1,..., 8; k = 1,, positive eviations from the goal k of the insurance company i, i = 1,..., 8; k = 1,, 5. The score of insurance company i is S i, efine in the usual way: 147

7 5 S i w x i, i 1,..., 8 (1) 1 The score can be efine ifferently, that can be observe in Triantaphyyllou (2000). We label (i = 1,..., 8) for every one of the eight insurance companies(1 Jaransko; 2 Basler; 3 Euroherc; 4 Croatia; 5 Allianz; 6 Kvarner VIG; 7 Triglav; 8 Grawe). Two goal programming moels are efine epenent on the appointe goals. For the first moel it is assume that the goals are the inicator values that have improve in relation to the same values the year before an that every insurance company i not have more than two goals. The goal values are as follows: g 11 = x 12, g 12 = x 14, g 21 = x 25, g 31 = x 34, g 41 = x 42, g 42 = x 44, g 51 = x 54, g 61 = x 63, g 71 = x 74, g 81 = x 84. Note that only two insurance companies have two goals. The general problem of goal programming is fining the solution as close as possible to the assigne goal (Ignizio an Romero, 2003). In this case, it is necessary to fin inicator weights for which the eviation of the score, i.e. the values of the business performance of the note goals is the smallest. The istance of the goal g = (g 11, g 12, g 21, g 31, g 41, g 42, g 51, g 61, g 71, g 81 ) an the score S = (S 1, S 1, S 2, S 3, S 4, S 4, S 5, S 6, S 7, S 8 ) is usually efine by a metric. This paper uses augmente Chebyshev metric (2), also known as the Dinkelbach-Isermann, for more etail (Sawaragi, Nakayama i Tanino, 1985). Using the mentione norm the goal programming moel (P α ) is formulate as follows: min ( S i g - S g ( ) ( )) (2),4 k1, i 1, 4; k 1, 2,4 S i g, i 2, 3, 5, 6, 7, 8 (4) 5 S i - wi xi 0, i 1,..., 8 (5) w 1 (6) i 1, i 1, 11, 12, 41, 42, w 0, i 2, 3, 5, 6, 7, 8 ; 1,..., 5 The parameter α is a small positive number. Alongsie non-negativity, the following constraints are efine in the mathematical moel. The value of the score can iffer from the appointe goal (3) an (4). The group of constraints (5) efine the score. Constraint (6) refers to norming weights. The goal (3) 148

8 function (2) as is efine in the given mathematical moel, in the optimal solution at least one of the variables or have the value zero: 0, i 1,..., 8; k 1, 2 (7) This statement can be checke in Sawaragi ET. al. (1985). We assign as y g - S (8) Because of relations (7) an (8) we have: y, i 1, 4; k 1, 2 (9) y i 1, i 2, 3, 5, 6, 7, 8 (10) The problem (P α ) is transforme into an equivalent problem(p yα ) using (8): min ( y 2,4 k1 ( ) ( )),4 Si g, i 1, 4; k 1, 2 (11) Si gi 1, i 2, 3, 5, 6, 7, 8 (12) 5 Si - wi xi 0, i 1,...,8 (13) w 1 (14) y, i 1, 4; k 1, 2 (15) 1 i i 1 y, i 2, 3, 5, 6, 7, 8 (16),,,,, w 0, i 2, 3, 5, 6, 7,8 ; 1,..., 5 i 1, y 0 For the secon moel we assume that the goal of every insurance company is the highest score, i.e. the best business performance for the given year: g max S1, max S2, max S3, max S4, max S5, max S6, max S7, max S8,. The problem is solve using the same norm as in the the first moel, while the moel itself can be foun in (Vovoić Rosenzweig, V., Volarević, H., Varović, M., 2011). 4. RESULTS Problem (P yα ) is solve for the following parameter values α = 0,1 i α = 0,01. Optimal weight values are as follows: 149

9 w 1 = 0,0639; w 2 = 0,4966; w 3 = 0; w 4 = 0,4356; w 5 = 0,0038. The solution of the problem gives the highest weight values to the return on investment an the return on equity inicators. The inicators combine ratio an the market share inicator have a very small value in the total score, while the weight of the ebt ratio is equal to zero. If we analyse the weight values, we can conclue that the strategy of the insurance companies was irecte to improve profitability, what is the funamental goal of every oint stock company. The secon part that they concentrate on is the investment segment, i.e. actively managing assets with the goal of the highest return on total investe assets. The combine ratio criteria has a very small weight value assigne to it, which means that the insurers have given a certain amount of attention in their business to the enhancment of their business score, that arises from the pure insurance component of the performance. The market share criteria also has a very small value, which can be attribute to the fact that the total gross written premium is constantly eclining since An that the entire economic situation oes not favor exapaning business on the insurance market. The ebt ratio criteria has the weight value of 0, which shows us that insurance companies i not inclue the increase of their own capital in their business strategies. It is obvious they are aware that there is no new capital on the market that they can attract. The increase of asset is base on the increase of liabilities other than capital an reserves (ebt liabilities). The obtaine weight values inicate that insurance companies have base their strategy on improving the inicators return on equity an return on investment. The score values are: S 1 = 0,6055; S 2 = 0,0849; S 3 = 0,7270; S 4 = 0,6287; S 5 = 0,8829; S 6 = 0,0920; S 7 = 0,5993; S 8 = 0,9020. If we rank the insurance companies base on their score we obtain the following ranking: 1. Grawe osigurane..; 2. Allianz Zagreb..; 3. Euroherc osigurane.., 4. Croatia osigurane.., 5. Jaransko osigurane.., 6. Kvarner VIG.., 7. Triglav osigurane.., 8. Basler osigurane.. The secon moel assumes that the goal of every insurance company is their maximal score. The moel is solve for the values α=0,1 an gives the following optimal weight values assigne to iniviual inicators for w 1 = 0; w 2 = 0,1818; w 3 = 0; w 4 = 0,8182; w 5 = 0. This means that return on equity inicator is the most important, followe by return on investment, while the rest are unimportant. 150

10 The score values are: S 1 = 0,7126; S 2 = 0,0409; S 3 = 0,8217; S 4 = 0,6539; S 5 = 0,9904; S 6 = 0,7169; S 7 = 0,4149; S 8 = 0,9134. If we rank the insurance companies base on their score we obtain the following ranking: 1. Allianz Zagreb.., 2. Grawe osigurane..; 3. Euroherc osigurane.., 4. Kvarner VIG.., 5. Jaransko osigurane.., 6.Croatia osigurane.., 7. Triglav osigurane.., 8. Basler osigurane.. The solution of the secon moel for 2011 is as follows: w 1 = 0; w 2 = 0; w 3 = 0; w 4 = 1; w 5 = 0. While the score values are: S 1 = 0,9180; S 2 = 0; S 3 = 1; S 4 = 0,8040; S 5 = 0,9850; S 6 = 0,2110; S 7 = 0,7490; S 8 = 0,9020. The weight value of one is given to return on equity, while the values of the rest are equal to zero. The score values give us the following ranking: 1. Jaransko osigurane.., 2. Allianz Zagreb.., 3. Euroherc osigurane.., 4. Grawe Hrvatska.., 5. Croatia osigurane.., 6. Triglav osigurane.., 7. Kvarner VIG.., 8. Basler osigurane.. 5. CONCLUSIONS This paper applies a multi-criteria approach in orer to analize the business performance of insurance companies in the Republic of Croatia for an by formulating a goal programming moel. Eight insurance companies are observe that have the largest share on the market measure by gross written premium. Five insurance business inicators that the CFSSA uses in their annual reports are use in the moel. Two goal programming moels are solve that iffer in relation to the appointe goals. Both of the moels use the same norm, the Dinckelbah-Isermann norm, in orer to measure the ifference from the ascertaine goals. It is assume in the first moel that the goals for insurance companies business for are those that increase in value in comparison to their value in The obtaine optimal weight values assigne to iniviual inicators show the importance of the given inicators in the business strategies of the observe group of insurance companies. The highest weight is assigne to the return on investment inicator, while an insignificantly smaller value is assigne to return on equity. The weights assigne to the combine ratio an market share inicators have small values, while the weight assigne to ebt ratio inicator is equal to zero. 151

11 The business strategy of the observe insurance companies that is erive from the weight values can be explaine by the current economic situation. For the observe year their business strategy i not inclue the growth of their share on the insurance market because of the constant ecline of the total gross written premium since The insurance companies i nothing in orer to attract fresh equity capital, aware of the fact that there is no such capital on the market. Their business strategy is irecte towars increasing revenue from active asset management an the increase of profitability. Insurance companies have coorinate their business strategies with the economic enviroment in which they currently operate. The score values obtaine from the moel are use to rank the insurance companies. The secon moel assumes that the business goal is the maximum score. Base on the ascertaine score values, the ranking of the observe insurance companies was obtaine for every of the observe years. REFERENCES Annual Reports, Croatian Financial Services Supervisory Agency (CFSSA), available at Ehrgott, M., Klamroth, K. an Schwehm, C. (2004), An MCDM approach to portfolio optimization, European Journal of Operational Research, Vol. 155, pp Garcia, F., Guiarro F. an Moya I. (2010), Ranking Spanish savings banks: A multicriteria approach, Matematical an Computer Moelling, Vol. 52, pp Ignizio, J.M. an Romero, C. (2003), Goal Programming, Encyclopeia of Information Systems, Acaemic Press, Vol. 2, pp Sawaragi, Y., Nakayama, H. an Tanino, T. (1985). Theory of Multiobective Optimization, Acaemic Press, Inc., Orlano, USA. Toby, A.J. (2011), Moelling Financial Fragility an Bank Profitability in an International Context, International Journal of Business Insights & Transformation, Vol. 4, Issue 2, pp Triantaphyyllou, E. (2000), Multi-Criteria Decision Making Methos: A Comparative Stuy, Kluwer Acaemic Publishers. Vovoić Rosenzweig, V., Volarević, H. an Varović, M. (2011), A Goal Programming Approach to Ranking Banks, Proceeings of the 11 th International Symposium on Operations Research (SOR 2011), Dolenske Toplice, Slovenia, pp