Analysis of The Financial Performance of National Rural Banks (BPR) Before and During COVID-19 Pandemic

ANALYSIS OF THE FINANCIAL PERFORMANCE OF NATIONAL RURAL BANKS (BPR) BEFORE AND DURING COVID-19 PANDEMIC

Riwandari Juniasti

Universitas Kristen Indonesia, Indonesia

KEYWORDS

Financial Performance; BPRs rural bank; Bank Perkreditan Rakyat

ABSTRACT

Until now, the condition of the COVID-19 pandemic in Indonesia is still ongoing, this has caused the performance of BPRs to be disrupted. This study aims to analyze whether there are differences in the performance of BPR before the COVID-19 pandemic and during the COVID-19 pandemic at BPR during the period June 2018 to September 2021. BPR's performance is measured by six financial ratios, consisting of the ratio of return to return on assets (ROA), capital adequacy ratio (CAR), non-performing loan ratio (NPL), operating expenses to operating income (BOPO), loan to savings ratio (LDR), and Cash Ratio (CR). This research method uses a quantitative approach with a comparative nature. This type of data collection uses secondary data in the form of BPR financial reports sourced from www.ojk.co.id. The data analysis method used a paid sample-test analysis with the help of the SPSS version 25 program. The results of the study found that (1) there were differences in ROA before the COVID-19 pandemic and during the COVID-19 pandemic. (2) There were differences in CAR before the COVID-19 pandemic and during the COVID-19 pandemic. (3) There was a difference in BOPO before and during the COVID-19 pandemic. (4) There was no difference in NPL before and during the COVID-19 pandemic. (5) There was no difference in LDR before and during the COVID-19 pandemic, and (6) there is no difference in the Cash Ratio (CR) before and during the COVID-19 pandemic.

INTRODUCTION

COVID-19 or coronavirus disease is an infectious disease caused by a new coronavirus called SARS-Cov-2. The World Health Organization (WHO) first learned about this virus on December 31, 2019 in Wuhan, China (WHO, 2020). WHO officially declared the corona virus (COVID-19) as a pandemic on March 9, 2020. Because this virus has spread widely in the world (COVID-19 Task Force, 2020). The spread of COVID-19 has spread to various countries, including Indonesia. The first case of COVID-19 in Indonesia was discovered on March 2, 2020. This COVID-19 pandemic not only had an impact on health but also hampered the country's economic growth, especially Indonesia. So that the Indonesian government needs to regulate various policies in order to stabilize the Indonesian economy.

One sector that is the focus of the government in dealing with economic problems is banking, because it is related to the important function of banking as a mediating institution between parties who have excess funds and parties who need funds, as well as a provider of payment transaction services. One of the banks that plays a major role in the economic activities of the community and small businesses is the Rural Bank or better known as BPR, this is because BPR has a strategic position in supporting small and micro businesses through credit facilities. BPR is a type of bank in Indonesia, whose activities are to collect public funds in the form of savings and deposits and distribute them in the form of credit.

On average, BPRs focus on lending to MSMEs. The main source of income for rural banks is from lending activities to MSMEs. Weak public purchasing power affects MSMEs, which causes MSMEs to falter in their business so that it becomes difficult to repay loans to BPRs. The pandemic conditions also caused BPRs to be more careful in lending, so this also had an impact on the level of lending at BPRs and resulted in the NPL of BPRs increasing. In the midst of the difficulties of the pandemic, based on the Quarterly 3 2021 Banking Profile Report issued by the Financial Services Authority (OJK), BPR performance is well maintained with credit growth growing higher than the previous year, and supported by a fairly strong capital ratio, which is around 32.01 %,

The outbreak of this virus has an impact of a nation and Globally (Ningrum et al, 2020). The presence of COVID-19 as a pandemic certainly has an economic, social and psychological impact on society (Saleh and Mujahiddin, 2020). Covid 19 pandemic caused all efforts not to be as maximal as expected (Sihombing and Nasib, 2020).

The problem that has arisen due to the COVID-19 pandemic in the banking sector is that debtors, including micro, small and medium enterprises (UMKM) debtors, find it difficult to carry out their credit obligations so that it interferes with banking performance (Disemadi and Shaleh, 2020). This is also supported by Saparinda (2021) that with the COVID-19 outbreak, all industrial sectors and are affected, both in the banking sector, some of the impacts of COVID-19 on the banking industry in Indonesia, among others. Credit/financing growth in the banking industry has slowed or decreased. With a decrease in credit in banks, it will certainly affect the financial performance of banks

In tackling the impact of COVID-19 on the financial sector, the government issued various policies, one of which was monetary policy. Through Bank Indonesia, the government provides policies related to banking during the COVID-19 pandemic, including:

a) BI has injected liquidity into the money market and banking, approximately 633.24 trillion has been issued, including the purchase of SBN from the secondary market, provision of banking liquidity with SBN Repo, foreign exchange swabs, and a reduction in the Statutory Reserves (GWM).

b) Restructuring of credit or financing and determining the quality of banking assets, financing companies, and micro companies in one pillar (Saparinda, 2021)

Although financial sector services are still being implemented, several policies that have been issued by the government are suspected to affect financial performance, especially during the pandemic. The issuance of POJK 11/POJK.03/2020 regarding credit slack can be used by the public during the pandemic, but banks and financial institutions will be affected by declining revenues from their main activities. This is as found by Sholihah (2021) that the average level of efficiency in the banking sector has decreased significantly during the Covid19 pandemic.

Furthermore, Soko and Harjanti's research (2022) shows that there are differences in ROA and PER before and during the COVID-19 pandemic in banking sector companies listed on the Indonesia Stock Exchange (IDX) in 2019 and 2020. Research by Kusuma and Widiarto (2022) shows that there are differences in financial performance as measured by ROA, NPM, and stock prices before and during the pandemic in financial sector companies (insurance and banks). While financial performance as measured by liquidity surprisingly did not experience any difference before and during the pandemic meanwhile, research by Sullivan and Widoatmodjo (2021) shows that the results of research from 43 banks show that CAR, NPL, BOPO there are significant differences in bank performance before and during a pandemic,

Research at BPR also shows that credit performance has changed during the covid 19 period, the percentage of NPL before the pandemic was unhealthy increased, then there was a change in ROA and BOPO values as found by Muhammad Rosidi and Zaky Zakiya (2022). Another research is the study of Ach Yasin and Ladi Wajuba (2021), which resulted in LDR and CAR during the pandemic which were still quite healthy both before the pandemic and during the pandemic, in contrast to ROA, BOPO and NPL during the pandemic because BPRs were unable to obtain maximum profit due to distribution credit decreased, but third party funds increased so that it put more pressure on ROA, BOPO tended to rise even though it was still healthy.

The results of the previous studies above do not look consistent, because some bank performance indicators differ significantly between before and during the covid 19 pandemic, but on the other hand it was also found that several bank performance indicators (liquidity and LDR) did not experience significant differences between before and during the covid 19 pandemic. This is what underlies researchers to examine the impact of the COVID-19 pandemic on BPRs in Indonesia by taking BPR performance data from June 2018 to September 2021.

The COVID-19 pandemic has affected the slowdown in Indonesia's economic performance, including the performance of rural banks. As it is known that the main contribution of BPR income is credit income, but on the other hand, micro business actors as the main market share of BPR have decreased performance as a result of the covid 19 pandemic, ROA, CAR, BOPO, NPL, LDR, and Cash Ratio before and during the covid 19 pandemic. The research model can be developed:

Figure 1. Framework

Source: Processed by Researchers

With this in mind, the hypotheses proposed in this study are as follows:

H1: There is a significant difference in ROA performance and during the COVID-19 pandemic

H2: There is a significant difference in CAR performance before during the COVID-19 pandemic

H3: There is a significant difference in BOPO performance before and during the COVID-19 pandemic

H4: There is a significant difference in NPL performance before and during the COVID-19 pandemic

H5: There is a significant difference in LDR performance before and during the COVID-19 pandemic

H6: There is a significant difference in the performance of the Cash Ratio before and during the COVID-19 pandemic

RESEARCH METHOD

This research methodincluding a comparative study, because it compares the performance of BPR before the covid 19 pandemic and during the covid 19 pandemic. There are six dependent variables in this study, namely (ROA, CAR, BOPO, NPL, LDR, CR), and covid 19 as independent variables. This type of data collection uses secondary data in the form of BPR financial ratios sourced from: www.ojk.co.id from June 2018 to September 2021. The data analysis method used in this research is paired sample t-test analysis with the help of SPSS version 25 program.

RESULT AND DISCUSSION

Results

Table 1. Results of Descriptive Statistics of ROA

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	1.9171	7	.18652	.07050
Pair 1	before the pandemic	2.3614	7	.17506	.06617

Based on the data in Table 1, the results of descriptive statistics show that the average ROA before the COVID-19 pandemic was 2.361% and the average ROA during the COVID-19 pandemic was 1.917%. This value indicates that the BPR's ability to generate returns on assets used was better before the COVID-19 pandemic.

Table 2. ROA Difference Test Results

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	-44429	15587	05891	-58844	-30013	-7541	6	000

Based on the data in Table 2, the results of the different test (Test Value of paired sample t-test) obtained are Sig. (2-tailed) from the comparison of the ROA value before and during the COVID-19 pandemic, it was 0.000. Refers to the basic reference for decision making, if the value of Sig. (2-tailed) < 0.05, then there is a significant difference in ROA. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in ROA. Based on this rationale, it can be concluded that there is a significant difference in ROA before the pandemic and during the COVID-19 pandemic.

Table 3. CAR Descriptive Statistics Results

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	31.6600	7	1.34535	.50849
Pair 1	before the pandemic	23.9400	7	2.29444	.86722

Based on the data in Table 3, the results of descriptive statistics show that the average CAR before the COVID-19 pandemic was 23.940% and the average CAR value during the COVID-19 pandemic was 31.660%. This value shows that BPR's capital is greater during the COVID-19 pandemic than before the pandemic. This can happen because the owners of the BPR make additional capital to anticipate the impact of the CAR.

Table 4. CAR Different Test Results

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	7.72000	2.70465	1.02226	5.21862	10.22138	7.552	6	000

Based on the data in Table 4, the results of the different test (Test Value of paired sample t-test) were obtained. Sig. (2-tailed) from the comparison of the ROA value before and during the COVID-19 pandemic, it was 0.000. Refers to the basic reference for decision-making, if the value of Sig. (2-tailed) is < 0.05, then there is a significant difference in ROA. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in ROA. Based on this rationale, it can be concluded that there are significant differences between CAR before the pandemic and during the COVID-19 pandemic.

Table 5. BOPO Descriptive Statistics Results

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	84.3029	7	.66297	.25058
Pair 1	before the pandemic	81.6957	7	.59284	.22407

Based on the data in Table 5, the results of descriptive statistics show that the average BOPO value before the COVID-19 pandemic was 81.696% and the average BOPO value during the COVID-19 pandemic was 84.302%. This value shows that BPR's operational costs are greater during the COVID-19 pandemic than before the pandemic. This shows that BPRs are less efficient during a pandemic.

Table 6. BOPO Different Test Results

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	2.60714	86378	32648	1.80828	3.40601	7.986	6	000

Based on the data in Table 6, the results of the different test (Test Value of paired sample t-test) were obtained. Sig. (2-tailed) from the comparison of the BOPO value before and during the COVID-19 pandemic, it was 0.000. Refers to the basic reference for decision making, if the value of Sig. (2-tailed) < 0.05, then there is a significant difference in ROA. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in BOPO. Based on this rationale, it can be concluded that there are significant differences in BOPO before the pandemic and during the COVID-19 pandemic.

Table 7. Results of Descriptive Statistics of NPL

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	5.6100	7	.70285	.26565
Pair 1	before the pandemic	5.2771	7	.30543	1.1544

Based on the data in Table 7, descriptive statistical results obtained that the average NPL value before the COVID-19 pandemic was 5.270% and the average NPL value during the COVID-19 pandemic was 5.610%. This value shows that bad loans at BPR were relatively the same before the COVID-19 pandemic and during the pandemic.

Table 8. Results of NPL Difference Test

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	33286	83646	31615	-44073	1.10645	1.053	6	333

Based on the data in Table 8, the results of the different test (Test Value paired sample t-test) obtained are Sig. (2-tailed) from the comparison of the NPL value before and during the COVID-19 pandemic, it was 0.333. Refers to the basic reference for decision making, if the value of Sig. (2-tailed) < 0.05, then there is a significant difference in NPL. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in NPL. Based on this rationale, it can be concluded that there is no difference in NPL before the pandemic and during the COVID-19 pandemic.

Table 9. Results of LDR Descriptive Statistics

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	77.1614	7	1.95957	.74065
Pair 1	before the pandemic	77.7371	7	.93143	.35205

Based on the data in Table 9, the results of descriptive statistics show that the average LDR before the COVID-19 pandemic was 77.737% and the average LDR during the COVID-19 pandemic was 77.161%. This value indicates that BPR lending and Third Party Funds were relatively the same before the COVID-19 pandemic and during the pandemic.

Table 10. LDR Difference Test Results

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	-57571	2.28469	86353	-2.68870	1.53727	-667	6	530

Based on the data in Table 10, the results of the different test (Test Value paired sample t-test) obtained are Sig. (2-tailed) from the comparison of the LDR values before and during the COVID-19 pandemic, it was 0.530. Refers to the basic reference for decision making, if the value of Sig. (2-tailed) < 0.05, then there is a significant difference in LDR. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in LDR. Based on this rationale, it can be concluded that there is no difference in LDR before the pandemic and during the COVID-19 pandemic.

Table 11. Results of CR. Descriptive Statistics

Paired Sample Statistics
		mean	N	Std. Deviation	Std. Error Mean
Pair 1	pandemic period	15.1500	7	2.29793	.86854
Pair 1	before the pandemic	16.2571	7	1.31739	.49793

Based on the data in Table 11, the results of descriptive statistics show that the average value of CR before the COVID-19 pandemic was 16.257% and the average value of CR during the COVID-19 pandemic was 15.150%. This value shows that the liquidity level of BPR is relatively the same before the COVID-19 pandemic and during the pandemic.

Table 12. CR. Difference Test Results

Paired Samples Test
Paired Differences
					95% Confidence Interval of the Difference
		Mean	Std. Deviation	Std. Error Mean	Lower	Upper	t	df	Sig. (2-tailed)
Pair 1	Pandemic period – before pandemic period	-1.10714	2.51534	95071	-3.43333	1.21916	-1.165	6	288

Based on the data in Table 12, the results of the different test (Test Value paired sample t-test) obtained are Sig. (2-tailed) from the comparison of the CR value before and during the COVID-19 pandemic, it was 0.288. Refers to the basic reference for decision making, if the value of Sig. (2-tailed) < 0.05, then there is a significant difference in CR. On the other hand, if the result of Sig. (2-tailed) > 0.05, then there is no significant difference in CR. Based on this rationale, it can be concluded that there is no difference in CR before the pandemic and during the COVID-19 pandemic.

Discussion

Based on the results of the research above, the six research variables have different results. This study examines whether there are differences in the performance of national BPR companies before the pandemic and during the COVID-19 pandemic. The data used is the financial report for the June 2018 period, which is when a pandemic has not occurred until the September 2021 financial report when a pandemic occurs. The company's financial performance is used to measure the financial ratios. There are six financial ratios used, namely return on assets (ROA), capital adequacy ratio (CAR), non-performing loan ratio (NPL), operating expenses to operating income (BOPO), loan to savings ratio (LDR), Cash Ratio (CR). The results of the six variables are that in ROA there are significant differences before the covid 19 pandemic and during the covid 19 pandemic. The results of the research are in line with Soko and Harjant (2022) who show that there are differences in ROA before and during the Covid pandemic. -19. The same results were also found by the research of Kusuma and Widiarto (2022) which showed that there were differences in financial performance as measured by ROA before and during the pandemic in financial sector companies (insurance and banks). Then the findings of Sullivan and Widoatmodjo (2021) stated that CAR and BOPO there were significant differences in bank performance before and during the pandemic, while LDR there were insignificant differences in bank performance before and during the pandemic. Furthermore, the results of hypothesis testing prove that NPL, LDR and CR do not have significant differences before and during the covid 19 pandemic. This result is in line with the research of Kusuma and Widiarto (2022) which showed that bank liquidity did not experience differences before and during the pandemic. The findings of Seto and Septianti show that there is no significant difference between the NPL and LDR of banking in Indonesia before and during the COVID-19 pandemic.

These results explain that BPR management needs to pay more attention and be innovative in increasing credit distribution during the pandemic because it is proven that ROA has experienced significant differences between before and during the pandemic. This can be done by making a more flexible credit policy specifically during the pandemic and providing more competitive loan interest rates in the region as an effort to increase business volume for debtors. Accordingly, BPRs also need to be more efficient in managing companies during the pandemic because company revenues decline during the pandemic, so that the target of increasing capital in BPRs organically can be achieved in accordance with the targets set by each BPR.

CONCLUSION

Based on the paired sample t-test with the help of the SPSS version 25 program, it is known that the results of the study show that (1) there is a significant difference in ROA before the COVID-19 pandemic and during the COVID-19 pandemic, (2) there is a significant difference in CAR before and during the COVID-19 pandemic, (3) there is a significant difference in BOPO levels before and during the COVID-19 pandemic, (4) there is no difference in NPL between before and during the COVID-19 pandemic, (5) there is no difference in LDR between before and during the COVID-19 pandemic, (6) There is no difference in CR between before and during the COVID-19 pandemic.

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