Specifically, we evaluate resource management and investment efficiency as two production levels of insurance companies. Keywords: data envelopment analysis; Dynamic network measure based on slacks; efficiency of resource management; Investment efficiency; Insurance companies. The literature documents that the success of insurance companies is based on three main services: risk taking, financial services and intermediation [1].
Therefore, the performance measurement of insurance companies involves not only solving multidimensional problems in various performance indicators, but also addressing dynamics in investment assets. The main purpose of this study is to investigate the effect of investment assets, which are dynamic in nature, on the performance of insurance companies when the insurance management process is modeled in a dynamic two-stage network process. This introduced transfer variable of investment assets refreshes the dynamic two-stage network DEA analysis of the performance of insurance companies.
Third, this study contributes to the literature by conducting regression analyses, cluster analysis, and multidimensional scaling, all of which evaluate insurers' performance in a common framework. The next section provides an overview of studies related to insurance company performance. Financial ratios, such as return on assets, return on equity and Tobin's Q, are commonly used as performance metrics by insurance companies [11].
This situation shows the limitations of using ratio analysis as a measure of the performance of insurance companies.
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Model Building and Data Collection
- Conceptual Framework
- Checking the Model Validity
- Measuring Dynamic Two-Stage Network Efficiencies
- Data Collection
A major problem with evaluating black box performance lies in the overlooked internal structure of the insurance management process. 6] and is used to evaluate the performance of insurers, is a special case of the general model proposed in the current study. We also add investment income as one of the bottom lines to better reflect investment performance.
Importantly, investment assets represent a large portion of the total assets of insurance companies, and the ratio varies significantly from one insurer to another. All variables used in the proposed DEA model are deflated according to the 2008 Consumer Price Index to derive their current values. We test for (i) homogeneity, (ii) minimum number of DMUs, (iii) isotonicity, and (iv) significance of the variables used in the proposed model to further validate its validity.
Second, 30 DMUs are five times the total inputs and outputs of the six in this study. Since the minimum required ratio is two according to Golany and Roll [38], we emphasize that the construct validity of the dynamic two-level DEA network model used in this study is stable and reliable. According to Sun [40], such an investigation can reveal the contributions of input variables in generating output variables.
The results in Table 2 show that the level 1 input variables, namely management costs and the input fixed assets carryover variable, explain 64.6% of the variation in the output variables (ICAR). Transfers FAsset and IAsset are treated as inputs in equation (4), and their values are limited so as not to exceed the observed values. These sampled companies out of a total of 33 insurance companies in Malaysia are those with all required financial data over the entire sample period for the purpose of our analysis.
The applicability of our proposed DEA model is assessed on sampled insurance companies with and without investable assets as a transfer variable and investment income as one of the outcomes in stage 2. The summary statistics of the variables used in the proposed model are listed in Table 3. The main transfer variable draws our attention in phase 2, namely IAsset, which increased relatively significantly in the first few years; but.
Another noteworthy piece of information is the corresponding output of investment assets, IIcome, whose percentage increase fluctuated over the sample period. These stylized statistics confirm the need to include investment assets as an input carry variable that generates investment income in the investment phase.
Findings and Discussion
- Analyses on Dynamic Two-Stage Network Efficiency
- Regression Analyses
- Additional Analyses
In summary, the investment efficiency with investment variables is greater than those without, which suggests that the investment assets of the sampled insurance companies had a significant effect on increasing their efficiency during the sample period. Although the same weighting is applied to both levels of efficiency, the findings show that investment efficiency plays a key role in determining the ranking of insurance companies in terms of their overall performance. These results suggest that when assessing the performance of insurance companies, modeling investable assets as a transmission variable in a dynamic two-stage DEA network model leads to improved discriminative power of overall performance, especially investment efficiency.
Therefore, examining the determinants of insurance company performance in Malaysia is an important agenda. This research can be a policy suggestion that insurance companies in other countries can learn from. LIQ represents the liquidity ratio, which is measured as the ratio of current assets to total assets and is a.
ACT is the activity ratio, which is measured as the ratio of gross premiums received to total assets; it is indicative of whether companies have dynamic capabilities for survival and development. PROF is the profitability ratio, which is measured as the ratio of net profits to total assets; it is an indicator of whether companies have adequate income for survival and development. LEV is the leverage ratio, which is measured as the ratio of total liabilities to total assets; it is an indicator of whether companies can meet their debt obligations.
The results obtained using the three techniques consistently reveal that liquidity (LIQ), profitability (PROF) and leverage (LEV) have a significantly positive impact on the performance of insurance companies over the sample period. These results indicate that the sampled insurance companies should focus on improving their LIQ, PROF and LEV to achieve satisfactory performance. In addition to performance evaluations and regression analyses, we use another multivariate analysis for performance evaluation and comparative analysis of insurance companies in a holistic and joint environment.
Specifically, we use cluster analysis and multidimensional scaling approaches to group insurance companies based on their respective efficiency and performance-related ratios. Since the activity ratio ratio is below the conventional significance level, we only consider the efficiency of resource and investment management and liquidity, profitability and leverage ratios in the full data set, all of which contribute to the performance of companies. of insurance. Although Group 1's profitability ratio is the second lowest, its minimal leverage ratio suggests less pressure on servicing debt obligations.
Conclusions
Among these companies, A10, which achieves unity in both stages of efficiency improvement, can be the point of reference for others in the group. Our empirical research shows that insurance companies with relatively satisfactory investment efficiency have generally satisfactory efficiency. Our results show that modeling investment assets as a transfer variable in a dynamic two-stage network DEA model achieves the improved discriminatory ability of investment efficiency.
An important implication of this research result is that if insurance companies focus on the dynamics of their investment assets, they are in a better position to build business competitiveness for long-term periods. Specifically, with this model, insurance managers and policy makers can better decide the importance of investment efficiency and comprehensively understand performance measurements from multiple inputs and outputs and multi-criteria analysis, which ultimately the latter will increase their competitive advantage. The efficiency and continued success of insurance businesses requires not only rich resources such as managerial inputs, but also the financial dynamics of investment assets.
This finding is again reflected when it appears that the activity ratio has no impact on overall efficiency. The activity rate is an indicator of whether companies have dynamic capabilities to survive and develop. That is, the inclusion of transferred variables captured the dynamic performance of the sampled insurance companies during the sample period. Insurance companies that strive to outperform their counterparts must ensure that all of these factors are carefully and thoroughly assessed.
In summary, as pointed out in the introduction, this study considers a carrying variable from an accounting/financial reporting perspective, specifically the concept of continuity [43], where investment assets are accumulated and carried by a financial term. Frontier efficiency methodologies to measure performance in the insurance industry: Overview, systematization and recent developments. A two-stage DEA model to estimate the overall performance of Canadian life and health insurance companies.
Evaluating the efficiency and productivity of insurance companies with a Malmquist index: a case study for Portugal. MExp refers to the operating costs used in labor and business services; FAsset are the properties, factories, and equipment accumulated from one period to another; ICAR represents the total number of claims/benefits paid plus the funds generated that are not intended for claims/benefits; IAsset is the real value of all financial investments; PE is the premium earned and thus belongs to the insurance companies; and IIncome is the corresponding return on investment assets.
MExp refers to operating expenses used in labor and business services; Assets are property, plant and equipment accumulated from one period to another; ICAR refers to total claims/benefits disbursed plus funds generated that are not earmarked for claims/benefits; Active IA is the real value of all financial investments; PE is the advanced premium earned and thus belongs to the insurance companies; and income is the corresponding return on investment assets. The dependent variable is the overall efficiency estimated with the investment variables; LIQ represents the liquidity ratio, which is measured as the ratio of current assets to total assets; ACT refers to the activity ratio, which is measured as the ratio of gross premiums received to total assets; PROF shows the profitability ratio, which is measured as the ratio of net profits to total assets; and LEV is the leverage ratio, which is measured as the ratio of total liabilities to total assets.
