Post-Establishment Loan Performance of Ultra Micro Holding

Aniesya Sefia Anggraeni, Mohammad Syamsul Ma'arif, Nimmi Zulbainarni

School of Business, Bogor Agricultural University, SB IPB Building

*Email: [email protected], [email protected], [email protected].id

Keywords

ABSTRACT

Total Assets, Tangibility, Liquidity, Debt to Equity Ratio

· This study has several research objectives, namely (1.) identifying the determinants of UMi Holding loan distribution; (2.) analyze the financial performance consisting of the holding holding company, namely BRI, and two holding subsidiaries, namely Pegadaian and PNM. Financial performance analysis is carried out by comparing the financial performance data of each entity before holding, namely in 2013-2021 and financial data after holding, namely 2022; The results of this study show that there are total assets (company size), tangibility, liquidity, and debt to equity ratio that affect the distribution of UMi Holding loans, in addition, the financial performance of UMi Holding entities has increased, especially in BRI which has experienced a significant increase in performance. Henceforth, practical and academic recommendations are presented at the end of the study.

INTRODUCTION

Not all individuals have access to the financial services industry in the form of savings or loans, which results in the inability to become bank customers (unbanked). Generally, these individuals come from low-income or non-working groups, who do not have complete identity documents, who do not have collateral, such as wet market traders, craftsmen, freelancers, and so on. On the other hand, financial institutions face obstacles in reaching and serving businesses at the bottom layer. This is due to the non-commercial status of this group, characterized by the absence of ability to manage capital, or assets that can be used as collateral to borrow from banks, which makes this group not bankable. Financial institutions generally assume that serving low-income people is uneconomical. For example, banks do not have the ability to establish a large number of branches to serve low-income people scattered throughout the country.

To bridge the gap in financial access for individuals from low-income groups, the Government has developed an Ultra Micro finance system (UMi). With this system, low-income people are prepared first, through business assistance, before entering the financial services industry ecosystem, as bank customers. Financial products are made in such a way that they are in accordance with the financial conditions or limitations of the community, for example daily loan products without collateral, loans with subsidies, and so on. The UMi scheme is expected to accelerate the process of financial inclusion and literacy of the UMi segment, and is able to increase the empowerment and development of UMi business business.

The UMi ecosystem, with three financial institution entities namely BRI, Pegadaian, and PNM  has the potential to become a large and sustainable UMi ecosystem, and can help in improving the quality of life of around 29 million UMi business owners in the years to come. In addition, the merger of these three entities can serve as a catalyst for the business development of the UMi segment, thus enabling transformation into commercial customers and increasing business competitiveness. Merger of business entities is one of the strategies implemented by the company to increase competitive advantage and expand market share and improve company performance Stevanie & Mindosa, 2019) (Zuhri et al., 2020).

The merger of companies, such as UMi Holding, requires the right strategy, in order to be able to increase lending, especially for the UMi business segment. Several previous studies examined strategies in increasing loan disbursement, the findings of the study stated that some strategies that can be done are by integrating financial institutions, improving facilities and infrastructure, increasing promotion, and unsecured loans. Research and studies on loan disbursement strategies from three companies with different business entities are still not available, so that through this study information can be obtained about the company's performance before and after the merger, as well as strategies to increase loan distribution.    (Ramadhanty & Oktafia, 2021;     Steppani     & Wijayanti, 2021;     Yuliningtyas     & Purwanto, 2017)

Research on the determinants of bank lending uses several variables such as  bank size,    (Anise     and    to the.    , 2020;     Boadi    , 2016; Imran &     Nishat    , 2013; Nail &     Lahrichi    , 2022;     Yin , 2021)macroeconomics, and bank-specific determinants. These studies can be a reference to determine the factors that influence loan distribution. On the other hand, this can also be a  research gap to conduct research on UMi Holding.  Currently, UMi Holding has been more than one year old. Until now there has been no research on the distribution of UMi Holding loans, so this study will conduct a study of the determinants that affect loans at UMi Holding and loan distribution strategies after the establishment of UMi Holding.

One of the establishment of UMi Holding is to accelerate the process of financial inclusion and literacy, especially in the UMi segment in Indonesia. UMi Holding is expected to play a role in empowering and developing the business of 25 million UMi businesses by 2025. The current problem is that 52% of UMi's 54 million businesses do not have access to funding sources from formal financial institutions (Coordinating Ministry for Economic Affairs, 2021). Funding needs are often obtained from sources that can burden them, such as loan sharks and fintechs that charge high interest costs. In 2025, it is targeted to overcome 52% of the problems of UMi people who cannot get access to loans. The four main sectors targeted are farmers, market traders, stall owners, and freelancers.

The merger of these three state-owned companies, of course, must pay attention to the company's financial performance after the formation of the holding. The performance of the company before the formation of the holding is in Table 1.

Table 1 Company performance before the formation of the holding

BRI
Posts	Value
Loans provided	859.6
Third Party Funds	969.8
Current Profit	34.03
NPL Gross	2,62
LDR	88,64
KPMM	22,55
Pawnshop
Posts	Value
Loans provided	50.37
Liability	42.26
Equity	23.06
Net profit	3.108
Capital rental income thdp total assets	27,09%
Total debt to equity	1,83
Madani National Capital
Posts	Value
Total Assets	25.92
Profit	977
Equity	2.849
Debt to Equity Ratio	8,1

BRI is a bank with the largest assets and network in Indonesia that focuses on financing micro, small and medium loans. In 2019, Bank BRI disbursed loans of Rp 859 trillion and raised funds from the public of Rp 969 trillion. The ratio of non-performing loans was maintained at 2.62% and the capital adequacy ratio was above the national banking average of 22.55%. In PT Pegadaian, loans disbursed by pawnshops have continued to increase in the last 5 years, with a loan position in 2019 of Rp 50 trillion. Pegadaian has consistently been able to generate profits in 5 years and in 2019 it was recorded at Rp 3.1 trillion. Meanwhile, PNM showed positive performance indicated by significant asset growth, with total assets in 2019 reaching Rp 25.9 trillion, or experiencing an annual growth of 432% in the last 5 years.

Seeing the performance of three companies that are quite good in 2019, it is necessary to analyze the company's performance after the establishment of UMi Holding. Based on the description above, several problems that will be discussed in this study are (1.) What are the factors that affect the disbursement of UMi Holding loans?; (2.) How is the financial performance of companies (BRI, Pegadaian and PNM) before and after the establishment of UMi Holding?; and (3.) What is the strategy needed to increase loan disbursement after the establishment of UMi Holding?

   Kurniati and Asmirawati (2022)  Conducting a study of the merger of several companies that went public, the results showed that there were differences between the company's performance before and after the acquisition. According to several previous studies, merging companies will increase business diversification, cost efficiency, and better financial condition of the company. Other results obtained by the merger of companies did not have a significant impact on the company.    (Kumar &     Bansal    , 2008)    Borodin    and    to the.     (2020) and Stevanie and  Mindosa (2019)

Research on the factors that determine bank loans has been conducted by several researchers, including Boadi (2016), Imran (2013), Naili (2022), Yin (2021), and Anis (2020). In their research, several variables were used such as bank size, macroeconomic factors, and bank-specific determinants. The results of the study can be used as a reference in determining the factors that affect bank loans. However, there is a research gap that can be explored, namely the determinants of loans in Ultra Micro Holding (UMi Holding). UMi holding itself is a merger of entities that have been more than one year old, but until now no research has been conducted on its performance.

METHODS

The data used in this study are primary data and secondary data. Primary data was obtained from interviews with BRI, Pegadaian and PNM companies as well as panel data obtained from financial statements for the 2013-2022 period. The 2013-2021 data is company performance data before the formation of UMi Holding, while 2022 is data after the formation of UMi Holding. Secondary data are obtained from annual reports, Bloomberg, company websites, and literature studies.

Researchers group data processing and analysis based on their usefulness in answering research objectives. The data analysis tools used in this study are: (1.) Panel data regression analysis, to determine the factors that affect the disbursement of UMi Holding loans; (2.) Descriptive statistical analysis, to see the financial performance of UMi Holding entities before and after holding.

The first stage of analysis of the factors affecting the disbursement of UMi Holding loans was analyzed using the panel data regression analysis method. Regression analysis of panel data is part of the collection of two types of data, namely time series data and cross section data. The following are the variables to be studied:   (    Baltagi    and al., 2009)

Table 2 Variable determinants of loan disbursement

Variable	Symbol	Formula
Loan disburesement	LOAN	Total disbursement
Return on Asset	ROA	Return on Asset
Return on Equity	ROE	Return on Equity
Asset	ASSETS	Assets
Growth	Heal up	Asset Growth
Tangiabilitas	SO	Fixed Assets/Total Assets
Liquidity	CYLINDER	Current Assets/Current Debt
Loan default	NPL	Ratio of bad loans/total disbursements
Debt to Equity Ratio	THE	Total debt/equity ratio

The primary data obtained will then be divided into two parts, namely independent  variables and dependent variables (loan distribution) to then be included in the regression model. The model used to analyze the factors affecting loan disbursement before and after the formation of the holding is as follows:

Information:

	:	Constant
	:	Regression coefficient
LOANit	:	Total disbursement
ROAit	:	Return on Asset
ROEit	:	Return on Equity
ASSET	:	Assets
GROit	:	Company growth
TANit	:	Asset structure (tangibility)
LIQit	:	Liquidity
NPLit	:	Non-Performing Loan
DERIT	:	Debt to Equity ratio
EIT	:	Error term

The second stage is an analysis using descriptive statistical methods to determine the effect of the company's holding on financial performance before and after the formation of UMi Holding. The research was conducted using a qualitative approach with primary data from the 2013-2022 financial statements. The variables to be studied include the following table:

Table 3 Financial performance variables

Variable	Symbol	Formula
Loan disburesement	LOAN	Total disbursement
Return on Asset	ROA	Return on Asset
Return on Equity	ROE	Return on Equity
Asset	ASSETS	Assets
Growth	Heal up	Asset Growth
Tangiabilitas	SO	Fixed Assets/Total Assets
Liquidity	CYLINDER	Return on Asset
Total Disbursement	DIS	Total Disbursement
Loan default	NPL	Ratio of bad loans/total disbursements
Debt to Equity Ratio	THE	Total debt/equity ratio

RESULTS

Descriptive Analysis of Bank BRI

The descriptive statistical analysis was carried out using a qualitative approach to primary data on the financial statements of the three UMi Holding entities for the 2013-2022 period with the help of Stata 7.0. This analysis was conducted to see the company's financial performance before and after the formation of UMi Holding.

Table 5 Descriptive statistics of Bank BRI's financial condition

Variable	Obs	Mean	Std. dev.	Min	Max
ROA	10	3.7%	0.009487	2.0%	5.0%
ROE	10	18.6%	0.072449	8.0%	34.0%
Assets (Rp Trillion)	10	1222.777	420.416	606.37	1865.639
Heal up	10	13.40%	0.065184	4.00%	28.00%
SO	10	1.90%	0.007379	1.00%	3.00%
CYLINDER	10	86.1%	0.028067	82.0%	89.0%
DIS (Rp Trillion)	10	782.8	246.2202	431	1139
NPL	10	2.3%	0.00499	1.6%	3.0%
THE	10	0.242	0.028983	0.200	0.280

Table 5 is the result of descriptive statistical analysis on BRI companies as the parent of UMi Holding. There are nine variables used as material for analyzing the company's financial performance ranging from  Return on Asset (ROA), Return on  Equity (ROE), company assets (ASET), asset growth (GRO), tangiability (TAN), liquidity (LIQ), total distribution (DIS), Non-Performing Loan  (NPL), and Debt to Equity Ratio (DER ). ROA data shows that from 10 observational data (2013-2022) an average value of 3.7% was obtained for 10 years with a minimum value of 2% and a maximum of 5%. ROE data shows that from 10 observational data (2013-2022) an average value of 18.6% was obtained for 10 years with a minimum value of 8% and a maximum of 34%. The company's assets were obtained on average for 10 years of IDR 1,222.7 trillion, a minimum value of IDR 606.3 trillion and a maximum of IDR 1,865 trillion. The standard deviation of the company's assets is quite high when compared to other data, because  the gap  between the lowest and highest data is quite far. The growth of assets obtained averaged 13.4%, the minimum value was 4%, and the maximum was 28%. Tangibility values are obtained on average 1.9%, minimum values 1% and maximum 3%. The liquidity value obtained is an average of 86.1%, the minimum value is 82% and the maximum is 89%. Total distribution was obtained on average Rp 782 trillion, with a minimum value of Rp 431 trillion and a maximum of Rp 1,139 trillion. The average NPL value obtained is quite low at 2.3%, the minimum value is 1.6% and the maximum is 3%. Finally, the Debt to Equity Ratio  data obtained an average value of 0.24, a minimum value of 0.2 and a maximum of 0.28.

Figure 1 BRI ROA and ROE Performance

If you look at BRI's profitability performance (Figure 1), there was an increase after the formation of UMi Holding. ROA and ROE values showed a pattern of decline in 2013 of 5% and 34%. This value has further decreased until 2021 to 2% and 8%. From this pattern, we can see that after the formation of UMi Holding, there was an increase in profitability, in 2022 to 3% and 17.51%. This shows that with the establishment of UMi Holding, BRI has increased profitability. This can be seen from Figure 2, where the total distribution shows an increasing trend since the last 10 years while the NPL value has fluctuated. However, the NPL pattern before the formation of UMi Holding showed an upward trend. In 2021, it is the highest NPL value in the last 10 years with a value of 3%. After the establishment of UMi Holding, the NPL value became better, decreasing to 2.67%. This shows that credit defaults after the establishment of UMi Holding show a healthier pattern. It was recorded that in 2022, the total distribution reached IDR 1,139 trillion.

Figure 2 BRI's lending and NPL performance

Figure 3 represents asset growth performance (%) and total assets. Total assets have shown an increasing trend since 2013 and have increased after the formation of UMi Holding, this is due to the merger of assets from the three holding entities. Meanwhile, if you look at the growth of its assets, it fluctuates, but shows a pattern of decline until 2021. The highest asset growth in 2014 with a total growth of 28% while the lowest in 2021 with a growth of 4.2%, while in 2022 there was an asset growth of 11%.

Figure 3 Performance of BRI's asset growth and total assets

Figure 4 represents DER performance, tangiability, and liquidity. DER performance is a ratio that shows the relationship between the amount of loans from creditors and own capital (Lasmarito, 2020). BRI has a fairly low DER value since 2013.

Figure 4 DER performance, tangiability, and liquidity of BRI

In 2022 there was a decrease in DER to 0.21. This is still within the safe limit set by BRI where the safe limit of the ratio is 7-10 times (Bank BRI Annual Report 2022). BRI's liquidity value in 2022 is 84%, an increase from 2021. Even since the last three years, BRI's liquidity value has shown a downward trend. Liquidity is a parameter of a bank's ability to settle its short-term obligations. While the tangiability value is a measure of the utilization of long-term assets used in company operations. The more tangiable a company is, the higher the company's chances of issuing debt securities.    (Jonathan & Barus, 2020)    (    Aldy     et al., 2018)

Descriptive Analysis of PT Pegadaian (Persero)

Table 6 is the result of descriptive statistical analysis on Pegadaian as a member of UMi Holding. There are nine variables used as material for financial performance analysis, the same as those used by BRI.

Table 6 Descriptive statistics of financial condition of PT Pegadaian (Persero)

Variable	Obs	Mean	Std. dev.	Min	Max
ROA	10	4.80%	0.009189	3.00%	6.00%
ROE	10	13.10%	0.028067	8.00%	18.00%
ASSETS (Rp Trillion)	10	53.22	14.95406	33.4	73.3
Heal up	10	5.50%	0.072457	-2.00%	22.00%
SO	10	15.20%	0.015492	13.00%	17.00%
CYLINDER	10	169.50%	0.122316	150.00%	187.00%
DIS (Rp Trillion)	10	134.9	27.44728	102.1	179.7
NPL	10	1.20%	0.004216	1.00%	2.00%
THE	10	1.909	0.38997	1.5	2.8

ROA data shows that from 10 observational data (2013-2022) an average value of 4.8% was obtained for 10 years with a minimum value of 3% and a maximum of 6%. ROE data shows that from 10 observational data (2013-2022) an average value of 13.10% was obtained for 10 years with a minimum value of 8% and a maximum of 18%. The company's assets were obtained on average 10 years of Rp 52.33 trillion, a minimum value of Rp 33.4 trillion and a maximum of Rp 73.3 trillion. The standard deviation of the company's assets is quite high when compared to other data, because  the gap  between the lowest and highest data is quite far. The growth of assets is obtained on average 5.5%, the minimum value is -2%, and the maximum is 22%. Tangibility scores were obtained on average 15.2%, minimum values 13% and maximum 17%. The liquidity value obtained is an average of 169.5%, the minimum value is 150% and the maximum is 187%. Total distribution was obtained on average Rp 134.9 trillion, with a minimum value of Rp 102.1 trillion and a maximum of Rp 179.7 trillion. The average NPL value obtained is quite low at 1.2%, the minimum value is 1% and the maximum is 2%. Finally, the  value of Debt to Equity Ratio obtained an average value of 1.90, a minimum value of 1.5 and a maximum of 2.8.

Figure 5 ROA and ROE Performance of PT Pegadaian (Persero)

If you look at the profitability performance of Pegadaian (Figure 5), it is the same as BRI, namely there was an increase after the formation of UMi Holding. ROA and ROE values showed a pattern of decline in 2013 with values of 5.70% and 15%. This value further decreased in 2021 to 2.83% and 8%. From this pattern, it can be seen that pre-establishment of UMi Holding there was an increase in profitability, in 2022 to 4.8% and 12%. This shows that with the establishment of UMi Holding, Pegadaian has increased profitability. This can be seen from Figure 6 where the total distribution shows an increasing trend since the last 10 years while the NPL value has fluctuated. However, the NPL pattern before the formation of UMi Holding showed an upward trend. In 2019, it was the highest NPL value in the last 10 years with a value of 1.75%. After the establishment of UMi, the NPL value became better, which fell to 1.21%. This shows that credit defaults after the establishment of UMi Holding show a healthier pattern. It was recorded that in 2022, the total distribution reached IDR 179.1 trillion.

Figure 6 Credit disbursement performance and NPL of PT Pegadaian (Persero)

Figure 7 represents asset growth performance (%) and total assets. Total assets show an increasing trend since 2013, while if you look at the growth of assets fluctuate, but show a declining pattern until 2021. The highest asset growth in 2019 with a total growth of 22.50% while the lowest in 2020 with a growth of -2.29%. After the establishment of UMi Holding in 2022, there was an asset growth of 4.68%.

Figure 7 Performance of asset growth and total assets of PT Pegadaian (Persero)

Figure 8 represents DER performance, tangiability, and liquidity. DER performance is a ratio that shows the relationship between the amount of loans from creditors and own capital. Pawnshops have a fairly low DER value since 2013.   (    Saputri     et al., 2022)

Figure 8 DER performance, tangiability, and liquidity of PT Pegadaian (Persero)

In the year the value of DER Pegadaian is 0.21. This is still within the safe limit set by Pegadaian where the safe limit of the ratio is 7-10 times (Pegadaian Annual Report 2022). The liquidity value of Pegadaian in 2022 is 150%, decreasing from 2021 and 2020. Liquidity is a parameter of a bank's ability to settle its short-term obligations. While the tangiability value is a measure of the utilization of long-term assets used in company operations. The more tangiable a company is, the higher the company's chances of issuing debt securities.    (Jonathan & Barus, 2020)    (    Aldy     et al., 2018)

Descriptive Analysis of PT Permodalan Nasional Madani (Persero)

Table 7 is the result of descriptive statistical analysis of PNM companies as members of UMi Holding. The variables used are the same as BRI and Pegadaian as material for financial performance analysis. The ROA value shows that from 10 observational data (2013-2022) an average value of 2.2% was obtained for 10 years with a minimum value of 0.7% and a maximum of 5.9%. The ROE value shows that from 10 observational data (2013-2022) an average value of 11.1% was obtained for 10 years with a minimum value of 2% and a maximum of 40.1%.

Table 7 Descriptive statistics of financial condition of PT Permodalan Nasional Madani (Persero)

Variable	Obs	Mean	Std. dev.	Min	Max
ROA	10	2.2%	0.015041	0.7%	5.9%
ROE	10	11.1%	0.109927	2.0%	40.1%
ASSETS (Rp Trillion)	10	19.99	15.82512	5.1	45.9
Heal up	10	29.14%	0.177102	3.60%	58.70%
SO	10	4.33%	0.024107	0.90%	8.10%
CYLINDER	10	234.6%	1.407124	113.2%	510.8%
DIS (Rp Trillion)	10	19.051	20.40108	2.29	57.79
NPL	10	2.24%	0.013352	0.70%	4.20%
THE	10	5.573	1.98921	2.48	8.64

The company's assets were obtained on average 10 years of Rp 19.99 trillion, a minimum value of Rp 5.1 trillion and a maximum of Rp 45.9 trillion. The standard deviation of the company's assets is quite high when compared to other data, because  the gap  between the lowest and highest data is quite far. The average asset growth was obtained at 29.14%, the minimum value was 3.60%, and the maximum was 58.70%. The tangibility value was obtained on average 4.33%, the minimum value was 0.90% and the maximum was 8.1%. The liquidity value was obtained on average 234.6%, the minimum value was 113.2% and the maximum was 510.8%. Total distribution was obtained on average Rp 19,051 trillion, with a minimum value of Rp 2.29 trillion and a maximum of Rp 57.79 trillion. The average NPL value obtained is quite low at 2.24%, the minimum value is 0.70% and the maximum is 4.20%. Finally, the Debt to Equity Ratio  data obtained an average value of 5.57, a minimum value of 2.48 and a maximum of 8.64.

Figure 9 ROA and ROE Performance of PT Permodalan Nasional Madani (Persero)

If you look at PNM's profitability performance (Figure 9), there is a decline after the formation of UMi Holding. The value of ROA and ROE showed a pattern of decline in 2013 with values of 1.85% and 7.91% and experienced a significant increase in 2019 with values of 5.90% and 40.09%, then decreased again until 2022. From this pattern, we can see that after the formation of UMi Holding, there was a decrease in profitability, in 2022 to 2.73% and 13.66%. This shows that with the formation of UMi, PNM has not increased profitability. This can be seen from Figure 10 where the total distribution shows an increasing trend since the last 10 years while the NPL value has fluctuated. However, the NPL pattern before the formation of UMi showed a downward trend. In 2015 it was the highest NPL value in the last 10 years with a value of 4.19%. After the establishment of UMi Holding, the NPL value became better, decreasing to 0.72%. This shows that credit defaults at UMi Holding show a healthier pattern. It was recorded that in 2022, the total distribution reached IDR 57.79 trillion.

Figure 10 Credit disbursement performance and NPL of PT Permodalan Nasional Madani (Persero)

Figure 11 represents asset growth performance (%) and total assets. Total assets showed a downward trend in 2014 and increased with the highest asset growth in 2018 with a total growth of 58.71%, but decreased in 2022 with a growth of 4.92%.

Figure 11 Performance of asset growth and total assets of PT Permodalan Nasional Madani (Persero)

Figure 12 represents PNM's DER performance, tangiability, and liquidity. DER performance is a ratio that shows the relationship between the amount of loans from creditors and own capital (Lasmarito 2020). PNM has a fairly low DER value since 2013 and the lowest value was in 2015. In 2022, there was a decrease in DER to 0.21 from the previous year. This is still within the safe limit set by PNM where the safe limit of the ratio is 7-10 times (PNM Annual Report 2022). PNM's liquidity value in 2022 was 183.72%, down from 2021.

Figure 12 DER performance, tangiability, and liquidity of PT Permodalan Nasional Madani (Persero)

Liquidity is a parameter of a bank's ability to settle its short-term obligations. While the tangiability value is a measure of the utilization of long-term assets used in company operations. The more tangiable a company is, the higher the company's chances of issuing debt securities.    (Jonathan & Barus, 2020)    (    Aldy     et al., 2018)

Descriptive Analysis of Ultra Micro Holding

Table 8 is the result of descriptive statistical analysis of all UMi Holding entities. The ROA value shows that from 30 observational data (2013-2022) an average value of 3.5% was obtained for 10 years with a minimum value of 0.7% and a maximum of 6%. The ROE value shows that from 30 observational data (2013-2022) an average value of 14.2% was obtained for 10 years with a minimum value of 2% and a maximum of 4.01%. The company's assets were obtained on average 10 years of IDR 431,995 trillion, a minimum value of IDR 5.1 trillion and a maximum of IDR 1865,639 trillion.

Table 8 Descriptive statistics of the financial condition of Ultra Micro Holding

Variable	Obs	Mean	Std. dev.	Min	Max
ROA	30	3.5%	0.015642	0.7%	6%
ROE	30	14.2%	0.081673	2%	4.01%
ASSETS	30	431.995	615.337	5.1	1865.639
Heal up	30	16,01%	0.150567	-2,00%	58,70%
SO	30	7,14%	0.061082	0,90%	17%
CYLINDER	30	163,40%	1.000728	82%	510,80%
DIS	30	312.262	368.7996	2.29	1139
NPL	30	1.92%	0.009786	0.7%	4.2%
THE	30	2.57	2.530731	0.2	8.64

The standard deviation of the company's assets is quite high when compared to other data, because  the gap  between the lowest and highest data is quite far. The growth of assets obtained averaged 16.01%, the minimum value was -2%, and the maximum was 58.70%. The tangiability value was obtained on average 7.14%, the minimum value was 0.90% and the maximum was 17%. The liquidity value obtained was an average of 163.40%, a minimum value of 82% and a maximum of 510.8%. Total distribution was obtained on average Rp 312,262 trillion, with a minimum value of Rp 2.29 trillion and a maximum of Rp 1,139 trillion. The average NPL value obtained is quite low at 1.92%, the minimum value is 0.70% and the maximum is 4.2%. Finally, the  value of Debt to Equity Ratio (DER) obtained an average value of 2.57, a minimum value of 0.2 and a maximum of 8.64.

Statistical Analysis of Panel Data Regression

The banking sector is an important sector in the Indonesian economy. Banking becomes an intermediary for those who need funds, because banks have adequate sources of reserves. In disbursing credit, banks need to pay attention to several things, especially in terms of the risk of default (   (Asteria et al., 2017) Non-Performing Loan). The higher the NPL value, the higher the default burden borne by the bank. According to lending, the effect is quite significant in the short term on NPLs. In this study, several variables were used that became determinants in loan distribution. Table 9 is a descriptive statistic of the variables used.   Mukhlis     (2011)

Table 9 Descriptive statistics of determinants of loan disbursement

Variable	Obs	Mean	Std. dev.	Min	Max
ROA	30	0.035567	0.015642	0.007	0.06
ASSETS	30	431.9955	615.3371	5.1	1865.639
Heal up	30	0.160133	0.150567	-0.02	0.587
SO	30	0.071433	0.061082	0.009	0.17
CYLINDER	30	1.633967	1.000728	0.82	5.108
DIS	30	312.262	368.7996	2.29	1139
NPL	30	0.019233	0.009786	0.007	0.042
THE	30	2.574667	2.530731	0.2	8.64

The data used is aggregate panel data from all UMi Holding entities consisting of eight independent variables and one bound variable with the help of Stata 7.1. The data used is 10 years of historical data, from 2013 to 2022.  Based on descriptive statistics, the highest standard deviation value belongs to the variables total assets (ASSETS) and total distribution (DIS) with values of 615 and 368 respectively. This is due to the difference in market share of the three UMi Holding entities. BRI has the highest loan disbursement market share of up to Rp 1,139 trillion. As for other companies, the total distribution is still below Rp 200 trillion, especially PNM which is still far below Pegadaian. Likewise, with the company's total assets, BRI has total assets reaching Rp 1,865 trillion, this amount is very different when compared to the other two entities which are still below Rp 100 trillion.

This study tested the results of the chow test, there were eight independent variables and one dependent variable used. Variable Y  is a dependent variable in the form of total distribution, X1  is Return on Assets (ROA), X2  is Return on Equity  (ROE), X3 is total assets (ASSETS), X4 is asset growth (GRO), X5 is tangiability (TAN), X6 is  liquidity (LIQ), X7 is  Non-Performing Loan  (NPL), and X8 is Debt to Equity Ratio (DER). The chow test  is conducted to find out whether the best model is the Common  Effect Model (CEM) or Fixed Effect Model (FEM). From this result, it can be seen that the probability value is 0.11, if the probability value is more than 0.05, the CEM model is chosen, and if it is less than 0.05, the FEM model is chosen. The results of the chow test show that the best model is to use CEM.

Furthermore, a langrange multiplier  test is carried out to find out the best model, whether Common Effect Model (CEM) or Random Effect Model  (REM). The results show that the probability is more than 0.05. So the best model is the CEM model. The normality test was performed using the saphiro wilk test, the results showed that  the p-value for all variables was more than 0.05, so the data was normally distributed. Meanwhile, the results of the heteroscedasticity test conducted by the Breusch Pagan method, showed that the value of  the p-value was more than 0.05, so it can be concluded that the data did not experience heteroscedasticity. Furthermore, the results of the multicollinearity test show that the VIF value is below 10. These results show that among the variables used there is no multicollinearity. Furthermore, in the autocorrelation test that has been done, the output of the p-value  result is 0.1723 which means more than 0.05, meaning that in this model there is no autocorrelation problem.

Regression analysis was carried out on aggregate data from the three UMi Holding entities (BRI, Pegadaian and PNM). Regression analysis to find determinants of loan disbursement is not carried out on each entity, this is due to limited time and available data, so regression analysis is carried out in aggregate to meet statistical requirements. The loan disbursement data used is overall loan data, the data is not focused on distribution to the Ultra Micro business segment because the portion of distribution to the Ultra Micro business segment is not so large. So that this determinant analysis is to see the factors that affect the overall loan distribution in the three UMi Holding entities. Analysis of factors affecting loan disbursement in terms of financial aspects. In this analysis, several financial variables that can affect loan disbursement are used, namely total assets, profitability (ROA and ROE), asset growth, Tangibility, liquidity, Non-Performing Loan  (NPL), and Debt to Equity Ratio (DER). 

Table 10 Regression Analysis Results

The results of regression analysis are shown in Table 10, where of the eight variables there are four variables that have a high enough level of significance to loan distribution. The variable total assets (ASSETS) have a very significant effect with a confidence value of  95%. Indicated by  a low p-value (0.000) and a coefficient value in the direction of the increase in loan distribution. With the increase in asset value 1, it will increase the distribution by 0.59. The second variable is tangibility (TAN) with  a p-value  of 0.019 and a positive coefficient. The third variable is Liquidity (LIQ) which is significant at  a confidence  value of 90% and a coefficient of -7.9 or has a negative direction towards total lending. The last variable is the Debt to Equity Ratio (DER) p-value   of 0.017 and a coefficient of -7.1

The Total Asset variable is a representation of Bank Size    (    Boadi    , 2016) . The regression results show that with an increase in asset value, loan disbursement will increase. These results are in line with research Naili dan Lahrichi (2022) variable bank size which is reflected by the total asset log has a positive influence on loans. Banks with large assets tend to have strong sources of capital, and this can increase lending (Murningsih et al. 2020). With the increase in lending, it is expected that profitability will increase from bank interest.

The next variable that has a significant effect is tangibility, where tangibility is the ratio between fixed assets and total assets (Rifiana 2021). Tangibility is a measure of the utilization of long-term assets used for company operations. Increasingly tangible company, then the company's potential to obtain capital is very large. Companies with a higher composition of fixed assets will tend to be able to obtain loans with low interest rates. As we know, that BRI does    (    Aldy     et al., 2018) right issue In 2021 to obtain funding sources, by issuing 28.6 billion shares. So that the total funds raised are Rp 95.9 trillion (CNBC, 2021). The results of this study show that with the increase in bank tangibility, it tends to be able to increase lending. In this case, the higher the company has a fixed asset value, it reflects the higher the company will be in disbursing loans.

The third influencing variable is liquidity. Liquidity is the ability of banks to meet their debt obligations and be able to meet credit requests submitted without suspension. The regression results show that the liquidity value is opposite to the total loan disbursement. The lower the company's liquidity value, the higher the loan distribution. Liquidity is certainly related to margin, in this case with a decrease in liquidity, it has the potential to reduce profitability. Although the NPL value in UMi Holding is still relatively good, it is still important in maintaining credit quality, so that high loan disbursement will also obtain high profitability. In principle, with the increase in lending, reserves in banks will fall, so liquidity will fall.

Likewise, the variable Debt to Equity Ratio (DER) has a negative influence on total loan distribution. The value of the debt to capital ratio is high indicating that the company is in a bad state. According to the British Business Bank (2023) a good DER value is between 1-1.5. This is in line with the negative relationship between equity and credit risk. The higher the composition of debt, the higher the credit risk. So in this case, companies if they have a low DER value tend to dare to disburse higher loans. Some of the factors that affect DER are, sales growth rate, in this case how big the loan disbursement, sales stability, industry characteristics, asset structure, management attitude, and lender attitude.    Berrios (2013)    (    Alps    , 2018;     Sudan    , 2015)

CONCLUSION

Based on the results of the analysis that has been done, we found that the determinants that affect the distribution of UMi Holding loans based on the analysis are, the variables of total assets (company size), tangibility, liquidity, and debt to equity ratio. The variables of total assets and tangibility indicate a positive direction towards loan distribution. Furthermore, the financial performance of UMi Holding entities has increased, especially in BRI which has experienced a significant increase in performance. Of the nine financial variables that have been analyzed, it can be seen that all variables show the results of improvement after the establishment of UMi Holding. Two holding entities, namely BRI and Pegadaian experienced good growth after the establishment of the holding. However, a re-evaluation of PNM is needed. Because after the establishment of UMi Holding, the company should experience improved performance because operations became more efficient.

For this reason, BRI as the parent of UMi Holding needs to re-evaluate the system of each UMi Holding entity. This can be seen from the results of the analysis where BRI and Pegadaian experienced good growth after the establishment of the holding. However, PNM experienced a decline, where after the establishment of UMi Holding, the company should experience improved performance because operations became more efficient.

Further research is recommended to use a longer observation period and more complete data and more specific variables in determining the determinants of loan distribution, these variables are intended to collect more specific data so that later better loan distribution strategies will be obtained.

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