The effect of loan-loss provision, non-performing loans and third-party fund on capital adequacy ratio

Article history: Received: September 25, 2020 Received in revised format: September 3


Introduction
In the era of globalization, it is marked by the increasing number of people who use bank services in economic activities and for the purpose of saving money. One primary function of banks is to provide methods of payment to facilitate transactions. For example, bank liabilities such as deposit claims and banknotes have been used either as a medium of exchange in retail markets or as collateral for secured credit in the interbank markets (Park, 2020). In buying and selling activities, the public uses bank services to facilitate the payment process if transactions are done remotely, both transactions between regions and transactions between countries. In addition, the bank also prepares various products to meet customers' financial needs . Given its tremendous potential in the financial sector and customers' key role in its success, many researchers have investigated customer adoption of mobile banking and payment services (Choi et al., 2020). UU No.10 of 1998 concerning Banking, a bank is a business entity that seeks to collect funds from the public in the form of deposits and channel them back to the community through credit to improve the living standards of the Indonesian people (Menteri Negara 944 Sekretaris Negara, 1998). The main activity of the bank is raising funds and channeling funds from customers through lending. To ensure the safety of customer funds deposited at the bank, the bank must have good performance. The major role of banks is to play the financial intermediation function between funding needs and funding surpluses (Ozcalici & Bumin, 2020).
Customers can see the bank's performance by looking at the level of financial ratios presented in the financial statements published by each bank. In presenting financial statements, banks use the Guidelines for the Statement of Accounting Standards established by the Indonesian Institute of Accountants (IAI) and pay attention to the provisions relating to Government Regulations and Bank Indonesia Regulations . Banks measure and classify financial instruments according to the provisions of the Statement of Financial Accounting Standards (IFRS) 55. The Statement of Financial Accounting Standards (IFRS) 55 is adopted from the International Accounting Standards (IAS) 39 (Friedhoff et al., 2013). On October 24, 2016, the Financial Accounting Standards Board (DSAK) issued a Draft Statement of Exposure Statement on Financial Accounting Standards (IFRS) 71 replacing IFRS 55 to improve the concept of hedging (Hedging) and improve the concept of classification and measurement of financial instrument values. The Statement of Financial Accounting Standards (IFRS) 71 was adopted from the International Financial Reporting Standards (IFRS) No. 9 (Soans, 2018) and approved on July 26, 2017. IFRS 71 will begin to be used effectively in 2020. The calculation of loan-loss provision using the incurred loss method (Camfferman, 2015) used in IFRS 55 is carried out by recognizing losses when a default event occurs or a loss has actually occurred. However, the expected loss method that is adopted by IFRS 71 can begin to recognize losses if there is a risk of default even though failure has not actually occurred. This can allow the greater number of loan-loss provision formed by banks if using the expected loss reserve method.
Bank Indonesia Regulation Number 14/15 / PBI 2012, loan-loss provision is an allowance for funds that is formed if the carrying value of financial assets after impairment is less than the initial carrying amount (BI, 2012). Loan-loss provision is formed from the total non-performing loans. The level of problem loans can be indicated by the ratio of Non-Performing Loans (NPLs). If the bank fails to pay at a high rate, it is feared that when IFRS 71 is used effectively it can pose a risk of reducing the bank's Capital Adequacy Ratio (Capital Adequacy Ratio). The ratio of non-performing loans to gross loans (NPLs) from the euro area fell to 3.4% in 2019 Q3 following a downward trend since it peaked at around 8% in 2012. However, large dispersions remained throughout the euro area countries (NPLs) ratios ranging from 0.9% and 37.4%) place serious constraints on bank lending capacity, jeopardize financial stability and delay economic growth (Karadima & Louri, 2020).
The bank's capital adequacy ratio is a ratio that is highly considered because from this ratio the customer can consider the level of security and the bank's ability to return customers' funds. If bank regulations are effective, the depositing institution must be able to withstand unexpected losses. Bank capital plays an important role in achieving this goal. Bank capital contributes to financial market stability by protecting individual institutions from individual failures and reducing the risk of interbank spills (Baldwin et al., 2019). The improvements made in IFRS 71 are expected to improve the quality of lending, as well as make banks better prepared to deal with macroeconomic risks such as inflation and other risks. Banking regulation is mainly aimed at mitigating systemic risk resulting from bank failures, therefore, protecting the interests of savers and maintaining the overall health of the financial economy (Abou-El-Sood, 2016). In accordance with the background of the problems that have been described before, the purpose of this study is to determine the effect of partially or jointly (simultaneously) the independent variable loan-loss provision, Non-Performing Loans (NPLs) and Third-Party Fund (TPF) to the dependent variable Capital Adequacy Ratio (CAR). Variable loan-loss provision is determined in connection with the use of the expected loss method in IFRS 71 which allows the number of reserves to be higher (Engelmann, 2018). The Non-Performing Loans (NPLs) variable is determined because what can affect the amount of loan-loss provision is the number of problem loans that can be indicated by this ratio. The variable amount of Third Party Funds (TPF) is determined because from this source the bank gets funds to be channeled back through credit. While the Capital Adequacy Ratio (CAR) variable is determined to be the dependent variable because of the importance of this ratio level to show the performance of a bank (Mulyanto Nugroho & Pristiana, 2020). Capital Adequacy Ratio is a ratio that shows the level of ability of banks to cope with credit risk using their own capital. (Baldwin et al., 2019) CAR ratio can be calculated using the following formula: Bank Indonesia Regulation Number 15/12 / PBI 2013 (Bank Indonesia, 2013), banks must provide the minimum capital according to the risk profile as follows: loan-loss provisions is calculated by calculating reserves formed from the credit risk of securities instruments and other credit distribution compared to total productive assets. Meanwhile, to calculate the Non-Performing Loans (NPLs). (Boumparis et al., 2019) can be calculated using the following formula: Variable Third Party funds are calculated by increasing the number of demand deposits, savings and deposits because according to (Kasmir, 2014) the collection of funds by banks can be divided into 3 types. On this basis, including third-party reviews such as guarantees and commenting is one way to ensure the credibility of environmental reporting (Nishitani et al., 2019). To illustrate how this third-party fund calculation can be seen in the formula below:

TPF = Demand Deposit Account + Savings + Deposit
This study uses a sample of banks owned by the central government namely Bank Mandiri, Bank Negara Indonesia (BNI), Bank Rakyat Indonesia (BRI), and Bank Tabungan Negara (BTN). The sample of state-owned banks was chosen because these banks participated in helping government policies, one of which was the provision of people's business credit. This can increase the risk of increasing the level of NPLs because the provision of public business credit has a high risk of default if the people's business is not successful. This research is expected to provide useful information for subsequent research and related banks, especially to provide information on variables that need to be considered when IFRS 71 is used effectively. The formulation of the problem in this study are as follows: Based on the background of the problems that have been described, the objectives of this study are as follows:

Fig. 1. Conceptual Framework 2. Method
This research is a study that uses quantitative data in the form of numbers. Quantitative methods are especially important to explore the extent and variation of change (within and across units) induced by the implementation strategies (Smith & Hasan, 2020). The data used are secondary data in the form of time series derived from financial statements published by each stateowned bank for the period 2011 to 2018. Data processing was performed by using multiple linear regression methods using SPSS version 21 and Microsoft Excel 2010 tools (Mulyanto Nugroho, 2020). Before testing partially or simultaneously each of the independent variables on the dependent variable, the classical assumption test is performed to ensure that the data in the linear regression model are normally distributed. The classic assumption test consists of a normality test, a multicollinearity test, an autocorrelation test, and a heteroskedasticity test (Das, n.d.). The normality test in this study was carried out by the Kolmogorov-Smirnov method and confirmed by the probability plot images. A multicollinearity test was carried out by the tolerance method and VIF. Autocorrelation test is done by looking at the Durbin Watson image, while for multicollinearity test using scatterplots heteroscedasticity test method. Partial test (t-test) is a test conducted to find out the partial significance of the independent variable Loan-Loss Providing, Non-Performing Loans (NPLs), and Third-Party Funds (TPF) on the dependent variable Capital Adequacy Ratio (CAR). The independent variable is said to have a significant effect on the dependent variable if the significance level of the count is smaller than the significance level of the confidence level that is equal to 5% or 0.05 and t-value < t-table (Landau & Crc, n.d.). Simultaneous tests are carried out to find out how much influence the independent variables together have on the dependent variable. The independent variable is said to have a significant simultaneous effect on the dependent variable if the significance value of the regression model is less than 0.05 and the calculated F-value > F-table.

Result
Loan-loss providing is calculated by finding backup data that is formed from securities, credit, and other instruments. Then to find out how much loan-loss providing, the total backup data of all financial instruments is multiplied by the number of productive assets owned by each bank and used as a percentage. Loan loss provisions (LLP) are a large and important bank accrual used as an adjustment to reserves for the future credit losses of loan portfolios. Because the assessment of future loan losses inevitably involves significant subjectivity, which leads to banks' discretion in determining LLP (Kim et al., 2019). Based on the calculation of the Loan-Loss Provisions from the sources of the four published financial statements, during the period of 2011 to 2018, the highest, lowest and average loan-loss provisions information was obtained from the banks that became the study sample. This information can be seen in Table 4 below: From the Table 2 The following can be seen that the maximum loan-loss provisions (LLP) value formed by four banks owned by the central government, namely Bank Mandiri, Bank Negara Indonesia, Bank Rakyat Indonesia, and the State Savings Bank during the study period was formed by Bank Rakyat Indonesia in the third quarter of 2011 amounting to 5.23% and the minimum loan-loss providing formation value from 4 banks during the study period was formed by the National Savings Bank in the fourth quarter of 2013 amounting to 1.01% of total productive assets. The average loan-loss providing formed by the fourth is 2.56%.    Based on the above data it can be obtained that the highest CAR ratio during the study period achieved by state-owned banks was obtained by Bank Rakyat Indonesia in the 4th quarter of 2017 with a ratio of 22.96%. While the lowest CAR ratio was experienced by the State Savings Bank in the third quarter of 2014 with a ratio of 14.33%.

Partial Significance Test of Independent Variables against Dependent Variables
The partial test is conducted to find out whether or not there is a significant influence between the independent variables and the dependent variable partially (Nugroho et al., 2017). According to (Das, n.d.), an independent variable is partially said to have a significant effect on the dependent variable if the significant value of the test is less than 0.05. Meanwhile, according to 948 (Landau & Crc, n.d.), the independent variable is said to have a significant effect on the dependent variable if the value of t count> t table. The following are the results of the partial test calculations using SPSS version 21:

Table 6 Coefficients
Basic decision making can be made by comparing t-value with t-table. The calculated t-value has been listed in the SPSS output. Whereas the t-table can be searched with the following formula to be further searched for the t-table: (a/2 : n -k -1) = 0,05/ 2 : 128-3-1) = 0,025 : 124 So, the location of t-tables can be found at levels a = 0.025 and df = 124 with the number of t-tables 1,979124. From the ttable calculation using SPSS version 21, the following information can be obtained: [1] The significance value of the independent variable loan-loss provisions partially to the dependent variable is 0.226, greater than 0.05. While t-value is -1.217 smaller than t-table with the amount of 1.979124. [2] The partial significance value of the Non-Performing Loans (NPLs) partially according to Figure 3.6 is 0.008 smaller than the 0.05 significance level. The t-value is 2.702 greater than t-table of 1.979124. [3] The significance value of the independent variable Third-Parties Funds (TPF) partially shows a result of 0,000 which is smaller than 0.05 and t-value from the partial test of Third Party Funds variables (TPF of 9.754 is greater than ttable 1.979124.

Significance Test (F)
Testing (F) of the independent variable loan-loss provisions (LLP), Non-Performing Loans (NPLs), Third Party Funds (TPF) on the dependent variable bank capital adequacy ratio or Capital Adequacy Ratio (CAR) aims to find out how much influence the independent variable together with dependent variables. The independent variable is said to have a joint effect on the dependent if the significant value of the regression model is less than 0.05 or 5% and the calculated F-value is higher than the F-  So that it can be seen the number of F-value 37.358 is greater than the F-table 2.128120. The statement above is supported by the value of R square which is close to number 1 (0.803), meaning that the variable x together has a significant effect on Y. 3. In accordance with the results of the SPSS output to find out the significant effect of the variable Third Party Funds (TPF) partially on the Capital Adequacy Ratio (CAR), information can be obtained that the t-value for the third party variable of 9.754 is greater than the t- Based on the results of the study using SPSS version 21, information can be obtained that the Non-Performing Loans (NPLs) have a significant effect both partially and simultaneously on the Capital Adequacy Ratio (CAR) variable. Therefore, Bank Mandiri, Bank Negara Indonesia, Bank Rakyat Indonesia, and Bank Tabungan Negara should continue to implement policies to control the level of repayment of loans extended. This is intended so that when the Statement of Financial Accounting Standards (IFRS) 71 has been used effectively, the level of LLP and CAR can be controlled. Because LLP is formed based on problem loans, and the CAR ratio is also influenced by the NPLs. Information that the lowest capital adequacy ratio during the study period was experienced by the National Savings Bank with a ratio of 14.33% of the total Risk-Weighted Assets (RWA), occurred in the third quarter of 2014. And the highest number of NPLs was experienced by the National Savings Bank in the second quarter of the year 2014 with NPLs of 3.83%. For this reason, the National Savings Bank should start controlling lending so that the funds channeled can be collected properly, because according to the results of the study in this thesis, that the Non-Performing Loans has a significant effect on the Capital Adequacy Ratio. According to the results of the t-test, it was concluded that the loan-loss provisions variable had no significant effect on the Capital Adequacy Ratio (CAR), while simultaneously it had a significant effect on the Capital Adequacy Ratio (CAR). This is possible because during the research period, 2011 to 2018, the incurred loss reserve method was still used. If IFRS 71 has been used in 2020, it is possible that this variable can have a significant effect on CAR. This is because in 2020 banks have used the expected loss reserve method, which allows for an increase in the number of reserves in the bank. Therefore, the next researcher is suggested to be able to make this variable as a variable in research with more data and with the right calculation in order to provide information that can help those who need related information.