Ratio of early warning system and risk based capital in insurance companies registered at OJK 2016-2020

ABSTRACT

562%, PT Assuransi Jiwa BCA at 543.4%, PT Zurich Topas Life at 508%, PT Lippo Life Assurance at 468.3%, PT Sunlife Financial Indonesia at 430%, PT Astra Aviva Life at 422%, PT Avrist Assurance by 337%, PT Asuransi Allianz Life Indonesia at 327.6%, PT Asuransi Jiwa Generali Indonesia at 319%, PT Heksa Solution Insurnce at 315.1%, and PT AXA Mandiri Financial at 312 (Source : www.lifepal.co. id) Islamic insurance companies have special characteristics so that the analysis of financial performance is carried out using special ratios. To determine the financial performance of insurance companies can be through the solvency ratio. The calculation of the solvency of insurance companies is known as Risk Based Capital (RBC). RBC is the ratio of capital adequacy to risk borne. In Indonesia, the minimum solvency level limit for insurance companies has been stipulated in PMK No 53/PMK.010/2012 by 120%. The RBC value of at least 120% means the company needs to have a minimum wealth of more than 20% of the company's obligations including financing the company's insurance risk (Sujana and Sinarwati, 2017).
Based on the data above, RBC can be an indicator that shows the company's ability to pay claims. The lower the company's RBC, it means that the insurance company's ability to pay claims due is relatively weak. Lifepa stated that this data is based on an analysis of the financial statements of 50 insurance companies registered with the Financial Services Authority. Lifepal stated that this data is based on an analysis of the financial statements of 50 life insurance companies registered with the Financial Services Authority (OJK). PT Hanwha Life Insurance Indonesia is the insurance company with the highest RBC level. Even so, Hanwha Life posted a loss of IDR 5 billion. The value of the loss even increased from the same period the previous year of Rp.718.5 million. In its research, Lifepa also described 20 insurance companies that scored the highest net profit in the first quarter of 2020. In this category, PT Prudential Life Assurance was recorded as the company that earned the highest profit in 2020 of Rp.1.135 trillion.
Supported growth of insurance entities with an increase in the number of assets and income in each period, requires companies to optimize their company's performance so that they can meet criteria as a good insurance company. However, this does not guarantee that the insurance company has a good performance in managing its finances. Considering in 2017, the Financial Services Authority (OJK) has revoked the business license of PT Asuransi which has a low RBC, or the company's solvency ratio or RBC is not in accordance with the minimum limit of 120% and the company is reportedly having difficulty paying claims . The financial performance of insurance companies is considered as one of the important factors in increasing the trust of prospective policyholders. Islamic insurance companies need to prove by optimizing asset management and premium income so that they can maintain the company's financial stability. In addition, to see the company's financial condition, it is necessary to analyze financial performance. Financial performance is a reflection of the company's financial statements which contain forecasts regarding the assets, liabilities, capital and profits of the company (Agustina, 2012). Knowledge of the financial condition of the insurance company is considered important, because the company sells insurance products for risk losses in a policy. Financial performance shows the company's achievements in one period which is analyzed from the financial statements (Puspitasari, 2015).
The results of the EWS and RBC ratio analysis can be used as a description of the company's financial activities. Evaluation The company's financial performance can be used as a guide for future decision making. Besides In addition, the results of the analysis of the company's financial performance are also useful for calculating the risk of failure in wealth management, imbalances in the company's balance sheet and preventing the occurrence of inability to pay by insurance companies. The slowdown in the company's financial performance will have an impact on the company's financial health and the growth of the industrial sector in general. Islamic insurance companies need to make efforts to improve financial performance by maintaining company profits and solvency. Many studies on the financial performance of insurance companies have been carried out, but have different results. Utami and Khoiruddin (2016) analyzed the effect of early warning system financial ratios as proxied by liquidity ratios, own retention ratios, expense ratios, and company size on the solvency level of sharia life insurance companies for the period 2010 -2013. to the level of solvency. Research conducted by Putri, Sugeng and Harjum (2015) regarding the level of solvency as measured by the ratio of the level of adequacy of funds, the ratio of premium receivables to surplus, claims expense ratio, agents balance to surplus ratio, liquidity ratio and the ratio of changes in surplus. Based on this research, only the ratio of the level of adequacy of funds has a significant effect on the solvency of insurance companies listed on the IDX.
Research conducted by Alamsyah and Adi (2017) regarding premium income, investment return ratios, profits, and claims on RBC of general insurance companies in Indonesia, shows that only the claims ratio and investment return ratio have a positive effect on RBC. Ambarwati and Fatin (2018) said in their research on the effect of firm size, investment returns and profitability on the solvency of Islamic insurance companies in Indonesia, that firm size has a bearing on solvency. Research conducted by Hasbi and Suryawardani (2018), that the ratio of EWS and RBCl is not only to determine the performance and health of the company but also affects the solvency of the company. In this study, it is proven that the ratio of changes in surplus, the ratio of management costs, and the ratio of premium receivables to surplus have an effect on solvency.
In addition to the level of solvency, the financial performance of insurance companies can also be seen through the analysis of financial ratios. Analysis of the financial ratios of Islamic insurance companies is known as the Early Warning System (EWS) ratio. The EWS ratio has been applied in Indonesia and is contained in the Statement of Indonesian Accounting Standards (PSAK) to determine the health of insurance companies. The EWS ratio has included the ratio of liquidity, solvency, and profitability which aims as an early warning on the company's financial condition.
The results of a study conducted by Sulasmiyati et al., (2019) in their research revealed that the early waning system ratio had a positive and significant effect on risk based capital at PT. Asei Reasurasni Indonesia (Persero). The results of research conducted by Andari (2018) and Saputra (2019) in their research revealed that the Early waning system ratio which consists of the level of fund adequacy, claims expense ratio, and liquidity ratio has a positive effect on Risk Based Capital. In contrast to the results of research conducted by Sukiati and Leviany (2019) in his research reveals that the early warning system ratio has no 2. LITERATURE REVIEW effect on risk based capital in life insurance companies. The differences in the results of previous studies regarding the factors that can affect the level of solvency of insurance companies, make researchers interested in studying more deeply how the level of solvency in life insurance companies in Indonesia. This study chose the object in the life insurance sector because from the data on the growth of the number of companies and assets of life insurance companies experiencing rapid development. This study will provide an overview of the solvency condition of life insurance companies by taking into account the financial health of life insurance companies in Indonesia. Solvency level measurement is used as an effort to ensure that the company's financial management has been carried out optimally.

Risk Based Capital (RBC)
Budiarjol (2015) stated that the Risk Based Capital Health Ratio a ratio of the net worth or Net Worth of the company concerned, which is calculated based on standard accounting rules divided by net worth which is recalculated taking into account the possible deteriorating risks. The inclusion of these risks reflects the uncertainty faced by the company in its daily activities, for example the possibility of a short-term fall in asset values due to investment in riskier instruments, as well as the possibility of increasing debt levels due to unfavorable developments in the future in terms of interest rates, death rates, termination rates and so on.

Early Warning System (EWS)
The Early Warning System (EWS) ratio is a benchmark for calculating the National Association of Insurance Commissioners (NA/C) to determine the financial performance and soundness of sharia insurance companies. EWS can be used as an early detection of financial and operating risks of insurance companies in the future. This ratio has been modified by other countries as needed. In Indonesia, the EWS method has been recognized and regulated in the Statement of Financial Accounting Standards (PSAK) No. 28 concerning Loss Insurance Accounting. The EWS ratio includes liquidity, solvency and profitability ratios. EWS is a system for calculating the financial ratios of Islamic insurance companies based on the company's financial statements and as an identification of financial problems (Munawir, 2007). The results of the EWS ratio can provide an early warning of risky financial conditions in the future. With the EWS, supervisory and preventive actions can be taken against failures that may be experienced by insurance companies. The use of the EWS ratio will make it easier to build and supervision of the insurance industry by the authorities. An early warning system is used to detect early on the condition and financial performance of insurance companies so that management can immediately make improvements. The early warning system becomes a benchmark in assessing the financial performance and health level of insurance companies.

Normality test
This study uses a quantitative approach whose measurement uses primary data. The quantitative approach is the definition of objective statistical and data measurement through scientific calculations derived from the financial statements of insurance companies. This study aims to explain the effect of the independent variable, namely the Early Warning System Ratio which consists of the Adequacy Fund Ratio , Claims Expenses Ratio, and Liquidity Ratio with the dependent variable being Risk Based Capital. In this study, the sample used was the insurance company with the highest RBC throughout 2016 -2020 which was registered with the Financial Services Authority (OJK). Adpun in determining the sample using purposive sampling technique. The number of samples used in this study were 20 insurance companies registered with the OJK and issuing the largest RBCs in 2016 -2020.
Based on the results of the tests that have been carried out on the software eviews version 10, it is known that the probability value of Jarque Bera residual research data which includes: Fund adequacy ratio, claims expense ratio, liquidity ratio and risk based capital is 0.667643 and the probability value is greater than 0.716182 > 0.05, it is stated that the research data is normally distributed.
Based on table 1, it can be seen the value of the variance inflating factor (VIF) for the three variabel bebas yaitu Rasio t ingkat kecukupan dana (TKD ), R ratio Beban klaim (RBK) dan R ratio Liquidity (LKD) each is 1.005236. The VIF value for the three independent variables is less than 10, so it can be stated that the regression model is free from problems multicollinearity.
Based on table 2, it can be seen that the probability value of the White Test (Obs*R-Squared) is 0.2768. The probability value is greater than 0.05 so that it can be stated that the regression model is free from heteroscedasticity problems or in other words, the research data consisting of: Fund adequacy ratio (TKD), Claim Expense Ratio (RBK) and Liquidity Ratio (LKD) have a large variance. the same (homogeneous) so that it meets the requirements of the classical assumption.

Autocorrelation Test
Autocorrelation is a condition where there is a correlation between the residual values in one observation with other observations in the regression model. This autocorrelation test aims to test whether in the linear regression model there is a correlation between the confounding error in period t and the error in period t-1 (previous). The prerequisite that must be met is the absence of autocorrelation in the regression model. The test method used in this research is the Breusch Godfrey Serial Correlation LM Test. The autocorrelation test using the Eviews application program obtained the following results: Based on table 3, it can be seen that the probability value of the Breusch Godfrey Serial Correlation LM Test (Obs*R-Squared) is 0.2144. The profitability value is greater than 0.05 so that it can be stated in the regression model that there is no autocorrelation problem. This shows that there is no correlation between the residual values in one other observation in the regression model or in other words there is no correlation between the nuisance error in period t and the error in period t-1 (previously).

Panel Model Data Regression Analysis
The analytical method used to perform statistical analysis is panel regression analysis. Panel data is a combination of cross section data and time series ( Time Series ) so that it has implications for the large number of observations. Panel regression has three models, namely the Common Effect model, the Fixed Effect model, and the Random Effect model . The analysis of the three panel models is as follows :

Fixed Effect Model
The fixed effect model assumes that differences between individuals can be captured in their intercept differences. Therefore, each 0 is treated as an unknown parameter and will be estimated. To estimate the intercept that varies between individuals, the Dummy variable technique is used, so the fixed effect model is often called the least square dummy variable (LSDV) model. The results of data processing using the eviews program obtained a fixed effect model as follows: Based on table 4. the coefficients for the Fixed effect regression model are obtained so that the following equation can be arranged: Based on these equations, a panel model for each company can be arranged below:

Regression Coefficient Capital Adequacy Ratio (TKD) Or Slope Structure capital
The regression coefficient of the Capital Adequacy Level (TKD) or a slope of 0.319755 indicates that if the other independent variables have a fixed value and the Capital Adequacy Level (TKD) has increased by 1% then Risk Based Capital (RBC) will have an increase of 0.319755% regression coefficient The Capital Adequacy Level (TKD) has a positive value indicating that the Capital Adequacy Level (TKD) has a positive effect on Risk Based Capital (RBC).

Regression Coefficient of Claim Expense Ratio (RBK) Or Firm Size Slope
The regression coefficient of the Claim Load Ratio (RBK) or a slope of 0.753918 indicates that if the other independent variables have a fixed value and the Claim Load Ratio (RBK) has increased by 1% then Risk Based Capital (RBK) will have an increase of 0.753918% regression coefficient The Claim Expense Ratio (RBK) is positive indicating that the Claim Expense Ratio has a positive effect on Risk Based Capital (RBC).

Liquidity Ratio (LDK) Regression Coefficient Or Slope leverage
The Liquidity Ratio (LDK) regression coefficient or a slope of 0.395414 indicates that if the other independent variables have a fixed value and the Liquidity Ratio (LDK) increases by 1%, then Risk Based Capital (RBS) will increase by 0.395414%. positive indicates that the Liquidity Ratio (LDK) has a positive effect on Risk-Based Capital (RBS).

Common Effect Model
The common effect model assumes that the slope and intercept are constant between individuals and time. This model combines time series and cross section data in the form of a pool where the estimation technique uses the Ordinary Least Square (OLS) approach. The results of processing research data using the Eviews application program obtained the following common effect model: Based on table 4.10, the coefficients for the Common Effect regression model can be obtained so that the following equation can be arranged:

Random Effect Model
The random effect model uses residual variables to accommodate differences in individual characteristics and time. Thus, in the random effects model there are two residual components, namely the residual cross section (μi). The results of data processing using the eviews application program obtained a random effect model as follows: Based on table 6. the coefficients for the Random Effect regression model are obtained so that the following equation can be arranged:

Panel Model Test
There are three Step in choose l estimation method in data panel that is testing model common effects and model l fixed effect (Chow test), testing model fixed effect and model l random effect (Hausmann Test), and testing the random effect model and the common effect model (Breusch-Pagan LM Test). The three stages can be further explained as described in the following:

Chow Test
This test was conducted to compare the common effect model with the fixed effect model through the F-test. If the results show that the common effects model is accepted, then the common effects model will be analyzed. But if the fixed effects model is accepted, then the fixed effects model will be analyzed. Data processing using the Eviews Version 10 application program obtained the following Chow Test results: Based on table 7 above, the Fcount value is 340.092810 with a probability of 0.0000. The probability value is less than 0.05, so Ho is rejected, meaning that a good panel model to be used in this study is the fixed effect model.

Hausmann Test
This test was conducted to compare the fixed effect model and the random effect model through the Chi Square test. If the results show that the fixed effects model is accepted, then the fixed effects model will be analyzed. But if the random effects model is accepted, then the random effects model will be analyzed. Data processing using the Eviews application program obtained the following Hausmann Test results: Based on table 8, the Chi-Square statistics value is 680.185620 with a probability of 0.0000. If the probability value is less than 0.05, then Ho is rejected, meaning that a good panel model to use is the fixed effect model.

T Test (Partial)
The Effect of Rational Adequacy of Funds (TKD) on Risk Based Capital (RBC) Based on table 4. the tcount value for testing the H1 hypothesis is 3.200318 with a significance of 0.0025 where the tcount value with a significance level of 5% where df = n -k = (65 -3) = 62, the Ttable value is 1.998 tcount = 3.200318 > Ttable = 1998 With a significance level of 0.0025 < 0.05, then H01 is rejected and Ha1 is accepted, meaning that the ratio of the level of fund adequacy partially has a positive and significant effect on risk based capital. This shows that if there is an increase in the ratio of the level of fund adequacy, it will result in an increase in risk based capital and vice versa, a decrease in the ratio of the level of adequacy of funds will result in a decrease in risk based capital.

The Effect of Claim Expense Ratio (RBK) on Risk Based Capital (RBC)
Based on table 4. the tcount value for testing the H2 hypothesis is 3.550742 with a significance of 0.0009, the t-count value with a significance level of 5% where df = n -k = (65 -3) = 62, the Ttable value is 1.998 tcount value = 3.550742 > ttable = 1.998 With a significance level of 0.0009 < 0.05, then H02 is rejected and Ha2 is accepted, meaning that the claim expense ratio partially has a positive and significant effect on risk based capital. This shows that if there is an increase in the claim expense ratio, it will result in an increase in risk based capital. and vice versa, a decrease in the claim expense ratio will also result in a decrease in risk based capital.

The Effect of Liquidity Ratio (LDK) on Risk Based Capital (RBC)
Based on table 4. the Tcount value for testing the H3 hypothesis is 3.217542 with a significance of 0.0024 the tcount value with a significance level of 5% where df = n -k = (65 -3) = 62, the ttable value is 1,998, tcount = 3.217542 > Ttable = 1,998 With a significance level of 0.0024 < 0.05, then H03 is rejected and Ha3 is accepted, meaning that the liquidity ratio partially has a positive and significant effect on risk based capital. This shows that if there is a liquidity ratio, it will result in an increase in risk based capital and vice versa, a decrease in the liquidity ratio will result in a decrease in risk based capital.

Coefficient of Determination Test R2
To determine the effect of the independent variables on the dependent variable, the coefficient of determination is used together. The coefficient of determination is the percentage of the influence of the independent variable on the dependent variable. The value of R2 lies between 0 and 1, where if the value of R2 is getting closer to the value of 1, it means that the influence of the independent variable on the dependent variable is getting stronger, and vice versa. Analysis of the coefficient of determination using the common effect model obtained the following results Based on table 9, the joint effect is obtained by the coefficient of determination (Adjusted R Square) of 0.681477. This means that the effect of the fund adequacy ratio (X1), claims expense ratio (X2), and liquidity ratio (X3) on risk-based capital (Y) is 0.681 x 100% = 68.1%. While other variables that affect risk based capital (Y) but were not examined in this study were e = 0.319 x 100% = 31.9%.

The Effect of Fund Adequacy Ratio, Claim Expense Ratio, and Liquidity Ratio on Risk Based Capital
Based on the results of the tests that have been carried out, the F count value is 292.4296 and the significance value is 0.00000. in table F with a significance level of 5%, where df = n -k -1 (65 -3 -1) = 61, the Ftable value is 2.76. The value of Fcount 292.4296 > Ftable 2.76 with a significance level of 0.00000 < 0.05 then H04 is rejected and Ha4 is accepted, meaning that the ratio of fund adequacy level, claim expense ratio and liquidity ratio simultaneously has a positive and significant effect on risk-based capital. This shows that an increase in the capital adequacy ratio, claims expense ratio and liquidity ratio will result in an increase in risk-based capital and vice versa.

F Test (Simultaneous)
The F test is used to test the magnitude of the effect of all independent variables simultaneously on the dependent variable. This test is done by comparing the value of Fcount and Ftable, the value of Fcount can be obtained using the fixed effect model. Based on table 4. the Fcount value is 292.4296 and the significance value is 0.00000. in table F with a significance level of 5%, where df = n -k -1 (65 -3 -1) = 61, the Ftable value is 2.76. Fcount 292.4296 > Ftable 2.76 with a significance level of 0.00000 < 0.05 then H04 is rejected and Ha4 is accepted, meaning that the ratio of fund adequacy level, claims expense ratio and liquidity ratio simultaneously has a positive and significant effect on risk based capital. This shows that an increase in the capital adequacy ratio, claims expense ratio and liquidity ratio will result in an increase in risk based capital and vice versa.
The results of research conducted by l Sudjana (2018) in his research reveal that the claim expense ratio and liquidity ratio have a significant effect on life insurance companies. The results of research conducted by Andari (2018) and Saputra (2019) in their research reveal that the Early Warning System Ratio which consists of the level of fund adequacy, the claim expense ratio, and the liquidity ratio has a positive effect on Risk Based Capital. The results of research conducted by Putril (2013), in his research revealed that the ratio of the level of adequacy of funds has an influence on RBC in insurance companies. The results of research conducted by Ratna (2017) in her research reveal that the early warning system ratio has a positive effect on risk-based capital in Islamic insurance companies. The results of research conducted by Kadek (2018) in his research reveal that the early warning system has a positive effect on risk-based capital in insurance companies listed on the Indonesian stock exchange for the period (2012 -2017).

The Effect of Claim Expense Ratio on Risk Based Capital
Based on the results of the tests that have been carried out, the tcount value for hypothesis testing H2 is 3.550742 with a significance of 0.0009 the t -count value with a significance level of 5% where df = n -k = (65 -3) = 62, the t table value is 1,998 t value count = 3.550742 > t table = 1.998 With a significance level of 0.0009 < 0.05 Then H0 2 is rejected and Ha 2 is accepted, meaning that the claim expense ratio partially has a positive and significant effect on risk based capital. This shows that if there is an increase in the claim expense ratio, it will result in an increase in risk based capital. and vice versa, a decrease in the claim expense ratio will also result in a decrease in risk based capital. The results of research conducted by Sudjana (2018) in

The Effect of Fund Adequacy Ratio (TKD) on Risk Based Capital
Based on the results of the tests that have been carried out, the tcount value for testing the H1 hypothesis is 3.200318 with a significance of 0.0025 where the tcount value with a significance level of 5% where df = n -k = (65 -3) = 62, the ttable value is 1.998 tcount = 3.200318 > t table = 1.998 With a significance level of 0.0025 < 0.05 So H01 is rejected and Ha1 is accepted, meaning that the ratio of the level of fund adequacy partially has a positive and significant effect on risk based capital. The results of research conducted by Sudjana (2018) in his research reveal that the claim expense ratio and the liquidity ratio have a significant effect on life insurance companies. The results of research conducted by Andari (2018) and Saputra (2019) in their research reveal that the Early Warning System Ratio which consists of the level of fund adequacy, the claim expense ratio, and the liquidity ratio has a positive effect on Risk Based Capital. The results of research conducted by Putri (2013), in her research revealed that the ratio of the level of adequacy of funds has an influence on RBC in insurance companies. The results of research conducted by Ratna (2017) in her research reveal that the ratio of the early warning system has a positive effect on risk-based capital in Islamic insurance companies. The results of research conducted by Kadek (2018) in his research reveal that the early warning system has a positive effect on risk-based capital in insurance companies listed on the Indonesian stock exchange for the period (2012 -2017). This shows that if there is an increase in the fund adequacy ratio, it will result in an increase in risk-based capital and vice versa, a decrease in the fund adequacy level ratio will result in a decrease in risk-based capital.
his research reveal that the claim expense ratio and liquidity ratio have a significant effect on life insurance companies. The results of research conducted by Andari (2018) and Saputra (2019) in their research reveal the Early waning system ratio which consists of the level of fund adequacy, claims expense ratio, and liquidity ratio has a positive effect on Risk Based Capital . The results of research conducted by Putri (2013), in her research revealed that the ratio of the level of adequacy of funds has an influence on the RBC of the insurance company. The results of research conducted by Ratna (2017) in her research reveal that the ratio of the early warning system has a positive effect on risk-based capital I in Islamic insurance companies. The results of the research conducted by Kadek (2018) in his research revealed that the early warning system had a positive effect on risk based capital in insurance companies listed on the Indonesian stock exchange for the period (2012 -2012). 2017).
Claim expense ratio calculated by comparing l between claims incurred and premium income. Based on the results of these calculations, the results obtained that there was a significant decrease and increase for each company during the research observation period. This is an indication that the company has not been able to manage the claims that have occurred. So a high enough claim can lead to a high value of the load ratio claim. Some companies show that a decrease in the claim expense ratio results in an increase in RBC, the value of the claim expense ratio has not met the minimum normal limit of l 100%. Therefore, an in-depth analysis is needed regarding the high value of claims which experienced by the company. This is necessary so that the company is able to meet the normal limits of the claim expense ratio so that it confidence and can attract new customers. So that company l premium income will increase and solvency reserves can increase.

The Effect of Liquidity Ratio on Risk Based Capital
Based on the results of the tests that have been carried out, the tcount value for testing the H3 hypothesis is 3.217542 with a significance of 0.0024 the tcount value with a significance level of 5% where df = n -k = (65 -3) = 62, the ttable value is 1,998 tcount = 3.217542 > Ttable = 1.998 With a significance level of 0.0024 < 0.05, then H03 is rejected and Ha3 is accepted, meaning that the liquidity ratio partially has a positive and significant effect on risk-based capital. This shows that if there is a liquidity ratio, it will result in an increase in risk-based capital and vice versa, a decrease in the liquidity ratio will result in a decrease in risk-based capital. The results of research conducted by Sudjana (2018) in his research reveal that the claim expense ratio and liquidity ratio have a significant effect on life insurance companies. The results of research conducted by Andari (2018) and Saputra (2019) in their research reveal that the Early Warning System Ratio which consists of the level of fund adequacy, claims expense ratio, and liquidity ratio has a positive effect on Risk Based Capital. The results of research conducted by Putri (2013), in her research revealed that the ratio of the level of adequacy of funds has an influence on RBC in insurance companies. The results of research conducted by Ratna (2017) in her research reveal that the ratio of the early warning system has a positive effect on risk-based capital in Islamic insurance companies. The results of research conducted by Kadek (2018) in his research reveal that the early warning system has a positive effect on risk-based capital in insurance companies listed on the

CONCLUSION
Indonesian stock exchange for the period (2012 -2017). The more liquid the insurance company is, the better the company's solvency level will be. Therefore, insurance companies need to increase and maintain their liquidity ratios, in order to maintain the trust of insurance participants. If the company's performance is good, the interest of prospective insurance participants will increase which will result in an increase in company income.
Based on the results of the research and discussion that the author has stated in the previous chapter, it can be concluded that. The ratio of the level of adequacy of funds partially has a positive and significant effect on risk l based l capital . This means that as the ratio of the level of adequacy of funds increases, the risk based will also increase capital. Claims expense ratio partially has a positive effect on risk based capital. This means that the higher the claim expense ratio, the higher the risk based capital. Liquidity ratio partially positive effect on risk based capital. This means that the higher the liquidity ratio, the higher the risk based capital. The ratio of the level of adequacy of funds, the ratio of claims expense, and the ratio of liquidity simultaneously affect the risk l based l capital. This means that the higher the capital adequacy ratio, the expense ratio of risk based will also increase capital.