Transforming Social Assistance into Entrepreneurial Empowerment: UMi as a Public Sector Innovation in Indonesia

Abstract

The Ultra-Micro (UMi) financing program represents a significant public sector innovation in Indonesia’s approach to poverty alleviation and financial inclusion. Initially conceived as a social assistance initiative, UMi has evolved into a strategic government intervention designed to transform impoverished individuals into entrepreneurs. This shift reflects a policy innovation that redefines the role of the state from passive welfare provider to active enabler of economic participation. Despite ambitious goals, its implementation and impact face scrutiny. This study employed an exploratory qualitative approach through individual interviews with elite participants and debtors of UMi. The data used triangulation from documentation, observation, and in-depth interviews with key informants, selected through purposive sampling. Findings indicate that the program’s implementation—anchored in government regulations and executed through non-bank financial institutions (NBFIs)—demonstrates innovative service delivery. In this study, UMi exemplifies how public sector innovation—through policy reform, institutional collaboration, and community engagement—can drive inclusive economic growth. The study provides valuable insights for policymakers, practitioners, and scholars seeking to advance financial inclusion and sustainable economic development.

1. Introduction

Financial inclusion has come to be recognized as a fundamental pillar of inclusive development, especially in economies striving to bridge social and economic disparities (Ozili, 2020; Soumare et al., 2016). The provision of accessible, affordable, and appropriate financial services to underserved populations has been shown to positively impact livelihoods, particularly among low-income and vulnerable communities. A growing body of research highlights how access to financial products such as savings, credit, and insurance can serve as a catalyst for social mobility and economic empowerment, reinforcing the role of financial inclusion as a development imperative.

In Indonesia, financial inclusion has been placed high on the national agenda. Government-led initiatives have significantly expanded access to financial services across diverse socioeconomic groups. As of 2021, the country recorded a financial inclusion rate of 83.6%, reflecting consistent progress from previous years (Soesilo, 2021). However, despite these gains, Indonesia still trails behind several regional peers like Thailand and Malaysia, suggesting that there is ample room for improvement in ensuring equitable access, particularly among the most economically disadvantaged.

A pivotal facet of this financial inclusion strategy is the concerted effort to address the needs of the impoverished and vulnerable entrepreneurs, especially microbusiness owners. As highlighted by the Central Bureau of Statistics of Indonesia (2024), there has not been a discernible reduction in the number of people living in poverty. Alternatively, one might assert that it is very slight. As of March 2024, the impoverished population in Indonesia totaled 25.22 million individuals, reflecting a decline of 0.68 million (0.33 percentage points) from March 2023 and a reduction of 1.14 million (0.54 percentage points) from September 2022 (

Table 1. The Number (in Million) and Percentage of Poor Population, September 2020–September 2024.

Year	2020		2021		2022		2023		2024
Month	March	September	March	September	March	September	March	September	March	September
Total Number	26.42	27.55	27.54	26.50	26.16	26.36	25.90	N/A	25.22	24.6
Percentage	9.78%	10.19%	10.14%	9.71%	9.54%	9.57%	9.36%	N/A	9.03%	8.57

Source: National Socio-Economy Survey (Susenas), March 2023 and March 2024.

):

What complicates this picture is the persistent level of poverty, especially in rural and eastern regions of the country. Based on recent data from the Central Bureau of Statistics (BPS), as of March 2024, over 25 million Indonesians remained below the poverty line. Although the figures represent a slight year-on-year decline, the distribution of poverty remains uneven. The majority of the impoverished population is concentrated in Java, while the eastern provinces report higher poverty rates proportionally. These figures reflect the complex and layered nature of poverty in Indonesia, which extends beyond income deprivation to include limited access to healthcare, education, and decent living conditions.

The BPS also reported that the highest poverty rate was in Maluku and Papua, with 19.39 percent. Meanwhile, the lowest was in Kalimantan, at 5.44 percent. However, in numbers, most of the poor population is concentrated primarily on Java Island (13.24 million people), with the lowest concentration in Kalimantan (0.94 million people). Ukanwa et al. (2022) define poverty as encompassing not only financial deprivation but also the adversities that further compound it, such as inadequate or non-existent healthcare, low educational attainment, and diminished standards of living. It can even be described as health and well-being under serious threat Si et al. (2018). According to Matos and Hall (2021), policymakers have long stressed the significance of entrepreneurship in underdeveloped regions as a means of enhancing societal welfare.

The urgency to address this matter arises, as these individuals are potentially susceptible to poverty and this group is the main target of the government’s program to achieving Sustainable Development Goals (SDGs) through financial inclusion and access to finance. The SDGs establish a framework addressing critical global issues such as poverty reduction, hunger, gender inequality, and the reduction in inequalities. The most substantial portion of micro, small, and medium enterprises (MSMEs) in Indonesia are ultra-micro enterprises, which are operated by this vulnerable group. Nevertheless, in emerging economies, MSMEs face insufficient support and frequently cease operations within the initial years due to factors such as inadequate funding, lack of expertise, and small scale (Anwar et al., 2018), even though MSMEs are expected to make significant contributions to the SDGs in the global economy (Khattak, 2020).

Within this context, ultra-micro and informal enterprises have become focal points in the government’s broader push for inclusive growth. These businesses, often led by individuals with little or no access to formal banking, form the majority of Indonesia’s micro, small, and medium enterprises (MSMEs). Despite their potential, many of these enterprises struggle to survive, hindered by limited capital, weak business literacy, and structural barriers. While MSMEs are widely viewed as engines of job creation and innovation, their capacity to contribute meaningfully to national development goals remains constrained without sustained support.

To address this crucial gap, the Indonesian government introduced the UltraMicro Financing (UMi) program. Initially conceived as an extension of social protection policies, UMi has gradually evolved into a more proactive instrument of economic empowerment. Unlike conventional banking schemes, UMi is designed to serve those who are considered “feasible but not bankable”—entrepreneurs with potential but lacking the collateral or financial history to qualify for formal credit. Managed through non-bank financial institutions (NBFIs) such as Pemodalan Nasional Madani (PNM), Pegadaian/Pawnshop, Bahana, and cooperatives, and coordinated by the government’s investment center (PIP), UMi serves as a bridge between social assistance and economic self-sufficiency.

This approach reflects a notable shift in the state’s role-from welfare provider to active facilitator of economic participation. However, while the program’s design appears inclusive on paper, its implementation has revealed notable inconsistencies. Field reports and anecdotal evidence suggest disparities in funding allocation and accessibility, particularly for entrepreneurs in remote or underserved areas. This uneven distribution raises important questions about the program’s governance, coordination, and capacity to adapt to local needs. The present study engages with these issues through a qualitative inquiry into UMi’s practical implementation, focusing on PNM, pawnshops, Bahana, and Cooperatives, as a NBFIs and PIP as the coordinator fund for ultra-micro businesses. Moreover, the urgency of refining UMi’s delivery mechanism is reinforced by the country’s development targets. As Indonesia positions itself to transition into an upper-middle-income nation by 2035 (Chrisendo et al., 2021; Sudaryanto et al., 2021; World Bank, 2020; Maryanti et al., 2023), the role of ultra-micro enterprises in driving grassroots economic resilience becomes increasingly critical. Studies have shown that over 70% of small businesses in emerging markets lack sufficient access to finance (Adeola et al., 2021)—the elevated extreme poverty rates in rural areas, coupled with the multifaceted challenges inherent in these regions (Laborde et al., 2021), pose an obstacle that disproportionately affects rural and female entrepreneurs. Drawing on interviews with policymakers, institutional stakeholders, and UMi beneficiaries, the research seeks to unpack the structural and operational challenges that limit the program’s reach and effectiveness. Two central research questions guide the inquiry: (1) What challenges emerge during the allocation and disbursement of UMi financing? and (2) How is the UMi financing strategy equitably distributed among ultra-micro business actors to optimize its effectiveness.

The findings contribute to a deeper understanding of how public sector innovation—when grounded in community engagement, institutional collaboration, and responsive policy design to the Indonesian context—can serve as a meaningful tool for inclusive development. In particular, the study highlights how programs like UMi must evolve not only in terms of funding volume, but also in their capacity to deliver equitable, locally tailored support. Ultimately, the success of Indonesia’s financial inclusion agenda will depend on how well it can integrate such grassroots enterprises into the broader economic ecosystem, not merely as recipients of assistance, but as active contributors to sustainable growth.

2. Literature Review

2.1. Ultra-Micro Enterprises in Indonesia

The contribution of MSMEs to Indonesia’s GDP reached 61.07 percent, with MSMEs providing approximately 89 percent of private-sector employment (ADB, 2018; Adhikary et al., 2021). Furthermore, MSMEs play a critical role in pursuing SDGs, which aim to end poverty and social inequality and protect the environment (Pomare, 2018). Despite their pivotal role, MSMEs face challenges hindering their expansion and productivity. As mentioned by Adam et al. (2021); Hamidi and Salahudin (2021) emphasize that limited access to financial resources and institutions remains a fundamental obstacle to MSMEs’ productivity growth. The Ministry of Cooperatives and SMEs reported that over the past decade, approximately 98% of businesses are classified as MSMEs as follows: ultra-micro (69.03%); micro (29.69%); small (1.19%); and medium (0.09%); while less than 1% are classified as large businesses (0.01%). Moreover, based on the report in 2022 from the Institute for Economic and Social Research (LPEM FEB UI, 2022) titled “MSMEs Technology Intervention Needs: A Survey of 37.370 MSME Actors in Indonesia,” underscores the dominance of ultra-micro businesses within Indonesia’s MSME landscape at 69.8 percent, with micro-enterprises following at 23.6 percent. In summary, MSMEs, particularly at the bottom layer (micro and ultra-micro), are society or business actors who are asymmetric towards information. This is the MSMEs financing gap theory. Asymmetric information is one of the fundamental issues in the credit market and the labor market (Mhlanga, 2021). Asymmetric information rises when lenders do not have sufficient information to provide a financially viable loan.

The fundamental concept of UMi management financing, which aims to target poor people whom banks do not reach to realize financial inclusion which can be explained as follows: Firstly, the non-business-owning impoverished are categorized into communities whose businesses are unfeasible and need to meet the prudential financing requirements (unbanked/not bankable). This group is the government’s target for social assistance through various programs. Secondly, there are groups of individuals whose enterprises are not feasible but are nevertheless bankable in satisfying prudential financing requirements. Government intervention is limited to the KUR, UMI, Social Assistance (Bansos), and other program credit. In theory, new government intervention is expected if market conditions encounter asymmetric information. Typically, it is recommended that the government provide loan guarantees for the underprivileged populace and the impoverished, as the indigents lack the assets necessary to guarantee a loan to a bank (Ika, 2021).

2.2. Ultra-Micro Financing (UMi Financing) Program

Ultra-micro financing, a form of public sector innovation in Indonesia, is playing a crucial role in boosting entrepreneurship. It leverages non-bank financial institutions to distribute funds, targeting a segment of the population often overlooked by mainstream financial services. This government initiative provides financial assistance to the lowest level of micro-businesses, those not yet served by traditional banking. What started as a social assistance initiative has evolved into a strategic government intervention, designed to transform impoverished individuals into entrepreneurs. Since 2017, the government has been implementing the ultra-micro financing program through the PIP, utilizing a revolving fund model managed by the Government Investment Center (PIP) under the Ministry of Finance, and distributed through non-bank financial institutions. The program’s primary aim is to boost entrepreneurship and improve access to finance for ultra-micro businesses, offering a promising outlook for the future.

PIP was established in accordance with MoF Regulation Number 52/MoF-R.01/2007, issued on 16 May 2007, which outlines the structure and operational guidelines of PIP. UMi financing as “financing of funds sourced from the Government or jointly with the Regional Government (RG) and other parties to provide financing facilities to micro businesses” based on the MoF Regulation No. 193/MoF-R.05/2020. Following an improvement in performance, the Minister of Finance officially designated the PIP as a full BLU on 27 March 2009.

UMi provides a maximum financing facility of IDR 20 million per customer and is channeled by NBFIs (Ika, 2021). The distribution pattern used is two schemes, namely, a direct scheme (one-step loan) to state-owned enterprises, such as PNM and pawnshops, and an indirect distribution scheme (two-step loan) to Bahana. Some of them are Shariah Cooperatives. The funding comes from the state budget (APBN), local administrations’ contributions, and domestic and international financial institutions provided by UMi, offering not only financial assistance in the form of credit but also training and mentoring support for ultra-micro enterprises operators carried out by distributors.

Furthermore, there are two distribution schemes that micro business actors can choose from, namely, the group lending scheme and the individual lending scheme. The group lending scheme adopts the Grameen Bank scheme, which has been successful in Bangladesh. The distributor implements a joint responsibility mechanism in which the inability of one group member to make payments requires the willingness and capability of the other group members to assume responsibility. Meanwhile, the individual lending scheme is designed for debtors of the group loan scheme who have witnessed growth in their firm (upgrade).

UMi’s financing has been distributed in various economic sectors, including retail commerce, the manufacturing industry, fisheries, agriculture and plantations, and service. BLU PIP data shows that from 2017 to 2021, UMi financing funds channeled to the retail trade sector had the highest contribution of 94.48%, followed by the fisheries, agriculture, and plantation sectors by 3.51%, the manufacturing industry sector by 1.09%, and the service sector at 0.92%. From this data indicate that UMi financing directed to the retail trade sector has the most significant contribution. In contrast, the fisheries, agriculture, and plantation sectors receive less than 15 percent.

3. Methods

3.1. Research Design

This study adopted an exploratory qualitative study approach through individual interviews with elite informants and debtors of UMi. To ensure data accuracy and reliability, the research employed triangulation across multiple methods and data sources. These were used to corroborate interview data and enrich contextual analysis, and in-depth interviews were analyzed simultaneously to cross-verify findings. Member checking was also conducted by sharing interview transcripts and summarized findings with selected participants for validation and feedback. Informants were encouraged to provide clarifications or additional context to ensure accurate interpretation of their perspectives. Their expertise and practical experience were fully utilized to enrich the analysis and strengthen the credibility of the study’s conclusions.

3.2. Research Subjects

This study used a purposive sampling in the selection of key informants and it based on the information power as a guiding principle, which puts emphasis on the depth of information rather than number of participants. As described by (Malterud et al., 2016, p. 1756) in Moser and Korstjens (2018) that information power is built on to avoid “producing that which is already known”. These elite informants were drawn from government and are positioned as policymakers and institutional stakeholders. As Saunders and Townsend (2016) indicate, qualitative work in the organization studies context generally uses 15–60 interviews. While the study comprised ten elite informants and four UMi debtors, they were a diverse selection of policymakers and practitioners. Their stakeholder status meant that they hold formal positions in the community, had experience and involvement in the development, implementation, coordination, management, supervision and distribution of funds for UMi programs. They have knowledge relevant to the study, be willing to share this knowledge, communicate well, and be unbiased or able to reflect upon their own biases (McKenna & Main, 2013). In addition, the UMi debtors, which are all situated in Java (where the density of beneficiaries and credit distribution is highest), were selected according to scale of business, duration of business operation, sector and use of loan. They possess the most insight into fund utilization and its impact on their operations. The debtors were identified to ensure participant validity utilizing an initial screening questionnaire to verify eligibility criteria, requesting proof of fund receipt (e.g., a photocopy of the financing letter or a chronological account), and inquiring about the business scale and duration of operation. The researchers excluded business proprietors who did not receive these benefits, prioritizing those with experience in managing and utilizing UMi funds.

In line with the principle of information power, insights gleaned from ten elite informants and four debtors offered significant explanatory richness in relation to the aims of the study. The number of informants interviewed was ten elite informants as shown in

Table 2. Informant profile.

No.	Code	Elite Informant	Position	Years of Experiences	Date
1.	A1	Directorate General of Treasury of the Ministry of Finance of the Republic of Indonesia	Head of the Sub-Directorate of Regulations and Policy Standardization	10	8 August 2023
2.	A2	BLU-PIP	Director	15	23 August 2023
3.	A3	BLU-PIP	Head of information technology division 1	10	23 August 2023
4.	A4	BLU-PIP	Head of information technology division 1	7	23 August 2023
5.	A5	Pawnshop	Head of the Implementing Unit	9	8 September 2023
6.	A6	Pawnshop	Head of the Micro Product Division	12	8 September 2023
7.	A7	A state-owned venture capital company (Bahana)	President Director	20	20 September 2023
8.	A8	Bahana	Business Officer	10	20 September 2023
9.	A9	Bahana	Business Officer	8	20 September 2023
10.	A10	Saving and Loan Cooperative (Komida)	Director	11	6 October 2023

Source: Author’s own work.

.

3.3. Data Collection

Primary data was collected using face-to-face, semi-structured interviews conducted with ten elite informant and four of UMi’s debtors for an information-rich inquiry and more comprehensive understanding of the role that each subject plays in the sustainability of the UMi program’s growth strategy. Moreover, this study also used relevant secondary data such as academic publications and documents. Documents used in triangulation include: policies document, Ministry of Finance regulations (PMK No.193/2020, No.52/2007), PIP annual and performance reports (2017–2024), NBFI internal training manuals, BPS poverty and MSME datasets, and media releases related to ultra-micro financing outcomes to support the textual data from interviews. The analyzed content of the policy and mechanisms materials from various textual reports related to the UMi financing distribution and targets and those associated with the actual funds received and disbursed. The secondary data we collected from 2017 to 2024 indicates that the government has implemented micro financing for MSMEs, known as Ultra Micro Financing (UMi), since 2017. In-depth interviews were conducted from 8 August 2023 up to 18 November 2023. Each source is generally interviewed for around 60 to 90 min and the interviews were conducted in the Indonesian language. We employ several methods to capture the information with the informant’s consent, such as jotting down handwritten notes or capturing the interview outcomes on video. Subsequently, the outcomes of the interview are transcribed and validated by researchers.

3.4. Data Analysis

This study employed an inductive analytical approach, wherein the researcher sought to describe and categorize patterns that emerged from the data throughout the analysis process (Spradley, 1979). In addition, content analysis—a well-established research method in the social sciences—was used to examine data within its contextual framework (Krippendorff, 2018), particularly to interpret secondary data and information obtained from relevant agencies. Selected interview excerpts were also incorporated as supporting evidence (Wolcott, 2008).

Recognizing that qualitative research findings are susceptible to bias and misinterpretation, this study ensured trustworthiness through strategies that addressed transferability, credibility, dependability, and confirmability. The researchers repeatedly reviewed the interview recordings to verify and refine the accuracy of the information. Following a grounded reasoning logic, inductive coding and iterative theme development allowed data patterns to emerge naturally from participants’ narratives rather than from predefined theoretical constructs, enabling a grounded interpretation of how policy and institutional mechanisms shape program implementation (Charmaz, 2006).

To validate the findings, the researchers conducted member checking by returning preliminary analyses to the informants for confirmation, ensuring that participants’ perspectives were accurately represented. Consistent with content-driven (inductive) approaches, thematic analysis was conducted manually using intercoder agreement. This choice reflected the researchers’ focus on interpretive depth over hypothesis testing and the manageable volume of data. The coding framework was refined iteratively among the authors to maintain transparency and analytical rigor. After thoroughly reading the transcripts, the researchers extracted significant statements, formulated meanings, and organized similar ideas into thematic clusters. These clusters were then synthesized into overarching themes and subthemes aligned with the study’s objectives.

Consensus among authors was reached through collaborative discussion. An independent coder, familiar with the research topic, was also engaged to enhance objectivity. Both the researchers and the independent coder worked separately to ensure that interpretations faithfully reflected participants’ viewpoints rather than the researchers’ assumptions. All interview recordings, transcripts, and analytical summaries have been securely retained for reference. In terms of saturation, redundancy and thematic saturation were achieved after the tenth elite informant and the fourth debtor, indicating that additional interviews were unlikely to yield new or meaningful information. Data saturation was reached when no new conceptual insights or themes emerged from subsequent interviews (Guest et al., 2006). In line with (Malterud et al., 2016), the sample size was guided by the principle of information power, emphasizing the depth and relevance of each informant’s contribution rather than the total number of participants.

4. Results

4.1. Theme 1: Mechanism for Distribution and Management of Disbursement of UMi Financing Program

The UMi financing distribution mechanism works through direct and indirect distribution patterns.

4.1.1. Subtheme 1.1: Linkage Institutions as Accelerators of Financial Distribution

Based on the results of interviews with the UMi finance regulator, the distribution mechanism is based on Ministry of Finance Regulation (MoF-R) No.193.05/2020, as argued by the informants in this study. Several informants disclosed the following:

The basis of the mechanism is in MoF-R No.193.05/2020, for example, to whom it is distributed; that is why it can appear: it can be cooperatives, it can be PNM, and pawnshop.

(A1, A2, A3, A4, A5, A6)

The debtor’s criteria refer to the MoF-R; indeed, the definition of an ultra-micro business actor is not explicitly stated because the MoF-R says it is ultra-micro financing, so whoever is being financed is a micro business, whose business is generally not stable.

(A7, A8, A9)

In Article 20 MoF-R 193/2020, the government also regulates the mechanism for distributing UMi to debtors in detail, both individual debtors and groups.

PIP is obligated to establish partnerships with NBFIs, including PNM and Pegadaian, through intermediaries such as cooperatives and their distributor Bahana. The other informants added “when PIP lacked the capability to evaluate cooperatives, we requested the assistance of Bahana in order to conduct the evaluation”. (A3, A4) Because the present distribution is through NBFIs, with restricted NBFI requirements as a distributor and an annual distribution target, the majority of distribution is through PNM.

(A1)

In selecting a linkage institution, there are criteria in the MoF-R that NBFIs already have experience in financing MSMEs by the ultra-micro criteria.

(A10)

According to the findings from the interviews, NBFIs and linkage institutions have emerged as crucial players in accelerating financial distribution.

4.1.2. Subtheme 1.2: Blended Learning Approach of Mentoring Models

Concerns persist regarding the equitable distribution of UMi financing, particularly in regions characterized by a high concentration of impoverished communities. A2 added that in practice, we implement one of the MoF-R-regulated mentoring models, specifically the blended learning approach. And in order to organize it, we initially invited our debtors to seminar activities. We have partially curated these 50 individuals with the concept of one-on-one meetings. As the one-on-one meeting concept is carried out, data must also be recorded, such as how many assets and what the current turnover is, so that we can analyze deeper.

Meanwhile, A10 revealed that Bahana as a distributor carries out a feasibility assessment of prospective linkage institutions based on at least two criteria regulated in the MoF-R. A10 also added that so, everyone, whether PNM, Pegadaian or Bahana through the linkage institution, all have to report their recipients through SIKP which is managed by PIP, PIP is also related to other credit programs but the management is not carried out by PIP but directly by the MoF.

4.1.3. Subtheme 1.3: Forming a Group Using a Joint Responsibility Mechanism

UMi debtors revealed that Komida employed a joint responsibility method for distribution, which fosters mutual assistance among individuals. Meanwhile, debtor added that I, as group leader, must be willing and able to take responsibility if a group member has difficulty making payments. The group loan program at UMi is a scheme adopted from the Grameen Bank program, which was established by Dr. Muhammad Yunus in the 1970s and has since succeeded in Bangladesh. As mentioned by Santoso et al. (2020), the Grameen Bank implements a structure of ‘a joint liability’ and ‘group lending’. As revealed by several informants, combining mentoring and joint responsibility implementation, which has been tried previously on NBFIs such as Komida, PNM, and Pawnshop, is a highly effective strategy for reducing the number of NPLs. Forming a group using a joint responsibility mechanism is the key to success, as it ensures that group members are willing and able to assume responsibility for one another.

The results of this study are supported by the findings of several other studies, such as Armendáriz de Aghion and Morduch (2000), Besley and Coate (1995), Ghatak and Guinnane (1999), Stiglitz (1990), and Wydick (1999), who proposed that group lending with joint liability is key to the success of the microfinance sector. In addition, Stiglitz (1990) and Wydick (1999) also argued that group lending employs peer monitoring to transfer control and responsibility to consigners (pairs), and peer monitoring significantly impacts the performance of borrowing groups using intra-group insurance, which increases repayment rates without alternative methods (e.g., collateral). The microfinance industry in less developed nations employs joint liability group lending practices to mitigate challenges, thereby enhancing lending opportunities and diminishing the risks faced by lenders (Kar & Rahman, 2018). It can address significant disparities in information between lenders and borrowers. Responsibilities and expectations stemming from mutual trust within a social network bolster standards pertaining to the necessity of assisting one another in realizing a vision as a synthesis of views. This mutual trust smoothens information exchange inside the social structure to encourage the development of activities in the community. In line with previous studies, Putnam (2015) emphasized that social networks facilitate cooperation and communication, hence promoting mutual trust among societal members. Consequently, participation inside this network fosters continuous cooperation.

4.2. Implementation of UMi Financing Distribution

Since UMi was launched in August 2017, the UMi program has grown considerably regarding the number of borrowers and total loans disbursed. Based on UMi SIKP data dated 31 August 2023, accumulated from 2017 to 2023, the realization of UMi’s cumulative financing distribution has exceeded the set target, with accumulated debtors amounting to 8.87 million micro businesses with a value of IDR 32.31 trillion (see

Table 3. Realization of ultra-micro financing based on UMi SIKP data dated 31 August 2023.

Region	Period 2023		Period 2017–2023
	Debtors	Distribution (IDR)	Debtors	Distribution (IDR)
Sumatra	290.7 thousand	1.4 trillion	1.9 million	7.3 trillion
Kalimantan	2.3 thousand	116.8 billion	181.1 thousand	699.1 billion
Java	963.5 thousand	3.7 trillion	5.7 million	20.2 trillion
Sulawesi	105.1 thousand	449.1 billion	554.6 thousand	2.1 trillion
Maluku, North Maluku, Papua, West Papua	2.3 thousand	11.5 billion	28.5 thousand	116.9 billion
Bali, Nusa Tenggara	71.7 thousand	304.9 billion	485.2 thousand	1.8 trillion
Total	1.46 million	6.08 trillion	8.87 million	32.31 trillion

Source: Document (BLU-PIP, 2023).

). This achievement is higher than the accumulated target.

UMi financing recipients are dominated by women at 96.03%, with men at 3.97%. The Java region dominates the UMi distribution, which reached IDR 20.2 trillion to 5.7 million debtors, followed by the Sumatra region, which reached IDR 7.3 trillion to 1.9 million debtors, and the Sulawesi region, which reached IDR 2.1 trillion to 554.6 thousand debtors. The Maluku, North Maluku, Papua and West Papua regions were the smallest recipients of UMi distribution with a realization of IDR 116.9 billion to 28.5 thousand debtors.

Geographically, the number of UMi debtors and loan distribution is still concentrated on the island of Java, which is around 72% of all UMi debtors throughout Indonesia. To realize UMi financing for the 2017–2023 period, West Java province dominates UMi distribution, which reached IDR 6.75 billion to 1.87 million debtors. East Java province reached IDR 6.14 billion to 1.79 million debtors, and Java province is currently reaching IDR 20.2 trillion to 5.7 million debtors. As in previous research, Adam et al. (2021) stated that between August 2017 and May 2020, the proportion of UMi loans disbursed and borrowers on the island increased.

Meanwhile, between 2017 and 2023, the distribution of UMi loans and borrowers remains predominantly focused on the island of Java, with Java accounting for the largest share compared to other provinces, namely, 5.7 million debtors and loans reaching 20.2 trillion IDR. The concentration of UMi in Java could be considered reasonable if we focus on the program’s target of reaching ultra-micro businesses owned and operated by the poor and vulnerable in the country. Data on March 2024 depict that most of the poor population is concentrated primarily on Jawa Island (13.24 million people). Moreover, the high distribution on the island of Java is in line with its population (BLU-PIP, 2023).

On the other hand, Maluku, North Maluku, Papua, and West Papua are the regions that received the smallest UMi distribution, with a realization of IDR 116.9 billion to 28.5 thousand debtors (see Table 3). According to BPS data, as of March 2024, the highest poverty rate was in Maluku and Papua, with 19.39 percent in both urban and rural areas.

Table 4. The number of debtors and distribution of UMi by Province, 2017 and 2023.

Province	Period 2017–2023		Province	Period 2023
	Debtors	Distribution (in Billion IDR)		Debtors	Distributions (in Billion IDR)
West Java	1,872,319	6755.4	East Kalimantan	44,451	184.1
East Java	1,791,435	6145.3	Bali	33,179	135.2
Central Java	1,259,369	4441.2	Bangka Belitung	30,502	119.1
Special Capital Region of Jakarta	303,550	1139.3	Riau Islands	27,941	117.9
Special Region of Yogyakarta	75,241	267.5	Maluku	16,635	63.7
West Kalimantan	59,933	240.3	Papua	6.827	30.4
West Sulawesi	47,440	182.4	North Maluku	3.262	13.3
Bengkulu	47,148	193.7	West Papua	1.794	9.5

Source: Document PIP, October 2023.

depicts the number of debtors and distribution of UMi financing per province for 2017–2023.

Based on data as of 31 October 2023, from PIP as BLU coordinator of UMi distribution, simultaneously, the program grew from an initial forty-six participating NBFIs (two direct and forty-four indirect mechanisms) to seventy-two NBFIs (thirty-two direct and forty indirect mechanisms direct Bahana) which reaches 514 cities and districts. (See on

Table 5. UMi Disbursement by Participating NBFIs under Linkage Schemes, 2017–2023 (in IDR).

NBFIs	% Debtors	Debtors	% Distribution	Distribution (in Trillion IDR)
One Step
PNM	79.8	7,079,637	77.3	24.96 T
Bahana	14.4	1,277,834	15.1	4.86 T
Pawnshop	5.5	492,066	7.3	2.34 T
Other	0.2	20,194	0.4	0.13 T
Two Step
LINKAGE/Bahana	% Debtors	Debtors	% Distribution	Distribution (in Trillion IDR)
Komida Cooperative	50.2	649,223	46.7	2.32 T
Sidogiri	15.3	198,221	14.1	702 M
Sharia Cooperative Tamzis Bina Utama	5.5	71,444	5.7	284.3 M
Sharia Cooperative BMT Bina Ummat Sejahtera	5.9	76,745	5.5	275 M
Sharia Cooperative Nusa Ummat Sejahtera	1.6	20,576	4.5	223.3 M
Sharia Cooperative Abdi Kerta Raharja	4.2	54,685	3.9	193.7 M
Other Linkage	17.2	222,048	19.5	968.7 M

Source: Documentation from (BLU-PIP, 2023).

). UMi financing is distributed through a direct mechanism (one-step) through conventional or sharia financing. Distribution of UMi financing with a Sharia contract is carried out through 40 Sharia Cooperatives. Under the direct and indirect linkage schemes of Bahana coordination, another agency, including Komida, has implemented UMi with almost the same rules and mechanism as PNM.

Particularly for Microfinance Institutions (MFIs) and Cooperatives that do not yet meet the criteria as distributors, PIP uses Bahana as an analyst to assess the suitability of MFIs/Cooperatives. To mitigate PIP risk, the first phase of distribution was carried out through Bahana and as a medium for transferring knowledge from Bahana to MFIs and cooperatives, which become Linkage Institutions (LI).

According to Adam et al. (2021), the direct mechanism has been more successful than the indirect channel in reaching out to UMi borrowers and disbursing loans. The direct mechanism includes PNM and Pegadaian. This success can be linked to the involvement of PNM. In 2017–2023, approximately 77.3 percent of total UMi distribution and 79.8 percent of debtors were managed by PNM. Thus, PNM’s achievement is that it is still the largest group-based ultra-micro financing company in the world. As mentioned by an elite informant, since the current distribution is through NBFIs, there are limited NBFIs requirements as a distributor, and there is an annual distribution target; most distribution is through PNM.

Table 6. Realization of ultra-micro financing distribution by BLU PIP for the 2017–2022.

Year	Target Debtor	Debtors	Percentage	Distribution (in Billion IDR)
2017	30,000	307,033	102.3	753.24
2018	500,000	557,112	111.4	1564.29
2019	600,000	809,926	135.0	2719.92
2020	800,000	1,765,974	220.7	6013.34
2021	1,800,000	1,958,224	108.8	7034.63
2022	2,000,000	2,010,589	100.5	8135.42
TOTAL	6,000,000	7,409,440		26,220.83

Source: Documentation from (BLU-PIP, 2023).

depicts that the acceleration in achieving the distribution target by BLU PIP occurred between 2017 and 2022. The increase in the number of debtors occurred by around 118%, namely from 307,033 debtors to 2,010,589 debtors; this also occurred in terms of the number of distributions from IDR 753.24 million to IDR 8135.42 billion.

4.3. Theme 3: Challenge of UMi Financing Implementation

Implementing UMi financing distribution encounters numerous obstacles; as a result, not all ultra-micro enterprises in Indonesia operate efficiently, and some fail. The informants in the study disclosed this information.

4.3.1. Subtheme 3.1: Collaboration and Government Support

Numerous sectors in Indonesia exhibit significant skepticism towards banking, particularly the agricultural sector. Agribusiness in Indonesia faces numerous difficulties and challenges that require quick resolution by the government, particularly concerning the systems and control of agribusiness, including financial institutions. (Observation: A1, A2, A3, A4).

Collaboration and government support regarding the direct distribution and implementation of UMi financing constitute a further challenge. A7, A8 disclosed that “the government’s role has yet to reach ultra-micro business actors directly, such as PIP, which does not have its products distributed directly to end users or direct business actors”. A2 stated that the number of UMi distributors was limited. Another stated that at least the Cooperative (Komida) is in the 12 largest provinces, including West Java and East Java. This is an obstacle because the companies or institutions we agent are limited in number, and the area they work in is also limited.

One of the obstacles is the limited number of distributors and also the large number of Regional Governments (RG), because the RG is involved in financing UMi.

(A3)

There needs to be more NBFI capacity outreach to distribute financing throughout Indonesia, especially in remote areas such as Eastern Indonesia.

4.3.2. Subtheme 3.2: The Mindset of Business Actors

Another informant revealed that implementing financing UMi experienced challenges, including the mindset of individuals who are still traditional, less innovative, and less dynamic, resulting in an inability to scale up due to a dearth of qualified human resources. Persuading debtors to attain the maximum limit is challenging due to their concerns regarding the ability to make regular payments. The advancement of MSMEs is hindered by the hesitance of Indonesians to engage in financial risk-taking. Not all individuals possess an inclination toward risk-taking as a result of their entrepreneurial spirit. (Observation: Four UMi Debtors.) This finding also supports Jacobs et al. (2011) that not all business actors follow this phase of business growth because the process of growing business units from small to larger scale is considered complex. Davidsson et al. (2005) and McMahon (1998) also argued that business actors’ disinterest in business capital reflects their reluctance to develop their business or, in particular terminology, it is also called a reluctance to move up in class.

The observation indicated that the goal of developing MSMEs to “move up in class” has not yet been accomplished, as seen by the reluctance of ultra-micro enterprises to advance. Apart from that, one of the main factors is that most debtors use their business only to increase their income and survive. As mentioned by Tewari et al. (2013) that many ultra-micro business actors do not have aspirations to grow and develop because they are in effectively self-employment situations. This phase is referred to as the survival stage, during which the revenue of the business starts to increase but is still insufficient to meet all operational expenses.

The interviews revealed that the UMi program from the central government was only able to reach a small number of ultra-micros, who then continued to repeatedly become program beneficiaries. In other words, the same program tends to be repeatedly accessed by the same debtors. Moreover, various reports state that very few micro and small-scale ones still have the vision to develop their businesses to “move up in class”. In addition, the low uptake of microcredit distribution in remote areas and the use of credit for additional capital or household consumption, not for investment in business development. This influences the slow pace of the government’s efforts to widely increase the scale of MSMEs.

4.3.3. Subtheme 3.3: The Quality of Mentoring

Another observation indicates that the spirit of commerce among the impoverished is unevenly distributed, highlighting the need for further improvements in various aspects including in terms of mentoring. Observations from the debtors indicate that account officers (AOs) are unable to propose solutions due to a lack of business acumen. They are merely providing support while someone shares their company-related difficulties with them. Several of UMI’s debtors confirmed that they are solely AOs and not business officers; they lack the capacity to offer solutions for enterprises run by entrepreneurs. AOs are responsible only for notifying debtors of upcoming due dates.

The observation of UMI’s debtors revealed that mentoring challenges include limited human resources for mentors or debtors, both in terms of numbers and specific skills needed to assist ultra-micro businesses in highly heterogeneous local contexts. Several debtors also stated that many businesses in remote locations still struggle with internet access and low digital literacy, which hinders digital mentoring. They also noted that many micro-businesses are focused on the trade sector, and mentoring is inadequate in addressing the agricultural production sector, crafts, and other sectors, each of which presents different challenges.

4.4. Theme 4: Strategy to Encouraging the Distribution and Implementation for Underprivileged Communities

This part will present the findings by examining the observation and notable statements from interviews, focusing on the strategy that promotes the distribution and implementation of initiatives for underprivileged communities:

4.4.1. Subtheme 4.1: Strengthening the Role of Intermediation: Quality and Quantity of Financing Distribution to Various Priority Regions and Sectors

One strategy for ensuring inclusive and sustainable economic growth involves enhancing the allocation of financial resources to areas and sectors that have been selected as priorities by the government, focusing on both the quantity and quality of funding. As a result of the documentation analysis and interview findings, it has been revealed that networking for new NBFIs is something that is needed now considering the potential large number of NBFI spread throughout Indonesia. Furthermore, another source disclosed that there are plans to augment the number of RG in order to facilitate the establishment of NBFIs in areas where they currently do not match the necessary criteria to operate as distributors. PIP has the ability to collaborate with RG in order to provide coverage for the entire or a portion of the interest UMi distribution that is distributed to the community. This NBFI network aims to expand the distribution of UMi finance, ensuring that it reaches a broader range of micro business players in need of financial access. It can be concluded that the sustainability of these mediators can be enhanced through the incorporation of distribution mediators, which also extends their reach and strengthens them with capital. It is acknowledged that collaboration is necessary. As such as the results of observations and discussions that PIP can collaborate with the RG, enabling it to function as an entrepreneur due to the RG’s ownership of regional companies. This allows for access to the regional budget and facilitates engagement through a regional company, as it possesses village-owned enterprises (BUMDes). The government should enhance promote the expansion of mentorship partnerships with various ministries/institutions, distributors, and business incubators, both within universities and conventionally, in order to reach a greater number of business actors.

4.4.2. Subtheme 4.2: Strengthening Cross-Sectoral Synergy and Collaboration Such as the Central Government, Regional Government, Distribution Agency and the Community

The function of the central government is, of course, to improve regulations and provide guidance and supervision. In addition, the central government can serve as a supervisory board in overseeing the execution of UMI financing and assuring debtor assistance, which has been an added value in UMi financing and can truly be optimized as a source of information on economic development in each region, as stated by a number of respondents. The process and results of the implementation of assistance still need to be informed optimally at the regional level, where the Regional Office of the Directorate General of Treasury together with State Treasury Services Office assigned to carry out monitoring and evaluation of UMi financing (A1). Meanwhile the informant added that it is necessary to create a three-party cooperation mechanism in optimizing financing programs for the poor by involving UMi distributors, RG, and Non Govermental Organizations (NGOs)…” UMi financing distribution needs to be in accordance with targets, in line with the large potential in this ultra-micro sector”.

4.4.3. Subtheme 4.3: Improving the Quality of Inclusive and Sustainable Entrepreneurial Mentoring Programs

Mentoring has been widely recognized by business actors as an essential component alongside financial, technical, and regulatory support. On the financial side, one key strategy involves allocating credit through joint responsibility mechanisms that promote collective accountability among borrowers. A range of technical support measures can also be applied, including training in product design, accounting and bookkeeping, marketing, promotion, and the use of digital technologies such as e-commerce and other online platforms. From a regulatory perspective, it is equally important to simplify licensing procedures, facilitate access to business permits, foster linkages between ultra-micro and larger enterprises through subcontracting or partnerships, and encourage collaboration among ultra-micro enterprises themselves. By equipping underprivileged communities with financial knowledge, they are better positioned to secure funding, manage income fluctuations, mitigate risks, and invest in housing, education, and training.

Various mentoring programs under UMi—organized by linkage institutions and non-bank financial institutions (NBFIs)—aim to enhance debtors’ business capacity and reduce the risk of non-performing loans (NPLs). However, according to several informants, mentoring activities often remain limited to debtor supervision rather than substantive business coaching. While educational and health-related assistance has contributed to poverty reduction, many aspects of mentoring still require improvement, particularly in strengthening human capital. Competency training for account officers (AOs) and trainers—implemented as “Training of Trainers” programs across districts and cities—is crucial to standardize mentoring materials and improve coaching effectiveness. AOs serve as the key interface between NBFIs and ultra-micro debtors, handling loan identification, evaluation, disbursement, monitoring, and collection for extremely small enterprises.

Informants also emphasized the need to enhance mentoring approaches that enable entrepreneurs to scale their businesses effectively. Many noted that credit access alone is insufficient; borrowers require structured guidance and hands-on assistance. For instance, Komida’s mentoring program has shown positive results when account officers doing the contextualized guidance like connecting sanitation loans with health education led to better repayment discipline and diversifying income-generating activities. On the other hand, in some rural locations mentoring did not result in any outcomes where account officers were not business trained and could not really advise on market expansion or digital marketing. Such a range in outcomes emphasizes the necessity for competency-based training packages and mentorship framework around NBFIs.

Some informants highlighted that mentoring should extend beyond business matters to include social and household development. For example, Komida identified that nearly 30% of its members lacked adequate sanitation facilities and responded by providing sanitation loans. Training programs were also tailored to address financial literacy, family financial management, and children’s education. Moreover, health education was integrated into mentoring sessions to promote well-being among low-income households. As one informant noted, PIP and UMi share a broader mission that goes beyond economic empowerment—seeking to improve quality of life holistically for underprivileged communities.

These findings align with prior research by Van Rooyen et al. (2012) and Bhuiya et al. (2018), who found that access to microfinance during health emergencies enhances individuals’ capacity to afford healthcare and improves health outcomes. Similarly, studies by Akhter and Cheng (2020); Mizanur Rahman and Ahmad (2010) demonstrated that microfinance programs have significantly improved the livelihoods of rural borrowers, leading to higher household incomes, increased spending, greater workforce participation, and better educational outcomes for children. Komida has established sustainable and innovative strategies and programs, such as providing access to education, health, social protection, and adequate sanitation for poor and vulnerable groups, that remain fundamental. In line with the SDGs, they can help alleviate poverty, support communities, and mitigate environmental pollution. Effective mentoring practices, as described by multiple informants, include group mentoring with joint responsibility mechanisms, practical learning sessions, one-on-one meetings, and the use of simple digital tools through blended learning. Collectively, these approaches strengthen inclusive and sustainable entrepreneurship among ultra-micro business actors.

4.4.4. Subtheme 4: Preparation of Sustainable Concepts and Policies

The findings of the interviews indicate that the UMi financing program has proven to not only empower existing NBFIs but also increase NBFI’s capabilities through enhancement in the form of assistance by NBFIs who already have experience. “We utilize existing institutions through empowerment by appointing them as linkage distributors, and then we increase their capabilities through enhancement with assistance from the main distributors. For example, cooperatives in various regions receive guidance from Bahana regarding increasing their capacity to distribute UMi financing”. (A1).

Another informant added that “Mapping is needed to encourage MSMEs to move up in class, so not all of them. For example, for ultra-micro and micro businesses, a capital scheme can be developed that differentiates “survivalist” and growth-oriented types of business” (A1). Meanwhile, A2 argued that “should be reconsidered with a more holistic strategy aimed at accessing the productive sector. For instance, mitigating hazards in the industrial sector such as providing liquidity assistance with low interest rates, subsidizing credit interest to cooperatives, and easy mechanisms. PIP can collaborate with the off taker such as purchasing agricultural products from farmers during harvest season. If the off-taker is already established in that particular business, they will be familiar with the associated risks”. Another informant added that “for the trade sector, further information about the products sold is provided. Must focus more on domestically produced goods or reduce foreign-made goods”. Meanwhile A3 added that “Increase the loans by differentiating the stimulants for traders and farmers. This is so that our mediators are stimulated toward the productive sector”.

5. Discussion

The Ultra-Micro Financing (UMi) program represents a significant public sector innovation in Indonesia’s approach to poverty alleviation and financial inclusion. Initially conceived as a social assistance initiative, UMi has evolved into a strategic government intervention aimed at transforming low-income individuals into entrepreneurs by providing financial services that address the needs of those excluded from formal banking. This shift reflects a policy innovation that redefines the role of the state from passive welfare provider to active enabler of economic participation.

Yet, the implementation of UMi financing distribution faces several challenges, resulting in varying levels of efficiency among ultra-micro enterprises across Indonesia, with some even failing to sustain their operations. Insights from the informants highlighted these obstacles in detail. The beneficiaries interviewed represented diverse micro-enterprise backgrounds—predominantly women (around 80%) engaged in petty trade, food processing, and small-scale service activities, with an average business experience of three to five years. Most participants had completed only secondary education or less.

Their prior exposure to other credit schemes, such as the Program Keluarga Harapan (PKH) or the KUR, significantly shaped their perceptions of UMi’s procedures and mentoring processes. Several respondents, for example, regarded UMi financing as a continuation of social assistance rather than as entrepreneurial capital. This perception helps explain the behavioral tendencies and repayment patterns observed among some borrowers, reflecting a lingering welfare-oriented mindset rather than a fully entrepreneurial one.

Moreover, the geographic concentration of UMi financing in Java highlights challenges in equitable innovation diffusion. This concentration is understandable, given Java’s status as Indonesia’s most populous and economically dynamic region (Pravitasari et al., 2020). As noted by Rumbogo et al. (2023), urban populations enjoy greater access to formal financial services than their rural counter-parts, highlighting the need for strategies that ensure equitable financial access in remote areas. In this study, most qualitative interviews were conducted in Java, aligning with the program’s current distribution pattern—over 72% of total debtors are located on the island (BLU-PIP, 2023). This focus was intentional, allowing the research to capture insights from the program’s most active operational hubs.

Provinces with high poverty rates, such as Maluku and Papua, remain underserved. These regions are significantly less motivated to initiate their own businesses compared to people in regions with a developed financial system. This calls for adaptive governance strategies that redistribute resources and tailor interventions to local contexts. Despite a reported 633% increase in UMi debtors in 2023 (BLU-PIP, 2023), equitable access remains a challenge. Strengthening cross-sectoral collaboration—between central and regional governments, distributors, and civil society—can enhance the program’s reach and effectiveness. This collaborative approach also demonstrates the government’s commitment to advancing micro, small, and medium enterprises (MSMEs) as a foundation for inclusive economic growth. PIP continues to play a vital role as the fund coordinator responsible for mobilizing and distributing resources across all provinces in Indonesia.

Mentoring and coaching, while present, require further innovation to become truly inclusive and sustainable. Authors such as Parvin et al. (2020) and Barinua and Ibe (2022) argued that mentoring and coaching are critical for developing sustainable human resources and empowering micro-entrepreneurs. In practice, Account Officers (AOs) serve as frontline agents responsible for identifying clients, assessing creditworthiness, monitoring repayments, and providing on-site guidance. Their dual administrative and advisory role positions them as key intermediaries between non-bank financial institutions (NBFIs) and ultra-micro borrowers. The study found that many AOs lack sufficient business training, limiting their effectiveness as entrepreneurial mentors. However, on the other hand, mentoring programs in several chanellers such as Komida also demonstrated success when account officers provided contextualized guidance—such as linking sanitation loans with health education—which led to improved repayment discipline and diversification of business activities. Successful mentoring practices involve using group mentoring or joint responsibility mechanisms, direct practice methods, the one-on-one meeting concept, and simple technology like blended learning has been implemented as described by several informants. Conversely, in rural areas where AOs lacked business training, mentoring efforts produced limited results, as officers were unable to advise on market expansion or digital marketing. This disparity highlights the urgent need for competency-based training and a structured mentorship framework within non-bank financial institutions (NBFIs) to ensure more consistent and impactful support for ultra-micro entrepreneurs. The development of blended learning models, integration with digital platforms, and partnerships with universities and incubators can elevate the quality of support provided. These enhancements represent organizational innovation within public institutions and their partners.

AOs play an important role in building an ecosystem that supports the growth and sustainability of MSMEs. In many channeling institutions, AOs not only provide credit supervision but also deliver training on financial management, operational planning, and business strategy—helping strengthen the human resource capacity of ultra-micro entrepreneurs. Enhancing the quality of mentoring and coaching can generate positive spillover effects beyond immediate financial outcomes. As Santoso et al. (2020) noted, microcredit can increase per capita income and enable access to additional social benefits such as better housing, healthcare, and education. Micro-finance also plays a key role in risk management, particularly during times of emergency. As stated by one of the informants, several channeling or linkage institutions offer mentoring programs for debtors, which have primarily focused on addressing extreme poverty by enabling individuals to secure funding for investments that can generate income, pursue higher education and skills training, or improve housing conditions. The program’s implementation—anchored in government regulations and executed through non-bank financial institutions (NBFIs)—demonstrates service delivery innovation, as mentioned by the informants that they implement initiatives, such as mentoring programs, to educate the community about activities that directly contribute to enhancing the quality of life of the community. By integrating mentoring programs and financial literacy initiatives, UMi not only provides access to capital but also builds entrepreneurial capacity among marginalized communities. These efforts align with broader goals of sustainable development, particularly SDG 1 (No Poverty) and SDG 8 (Decent Work and Economic Growth).

This study further demonstrates that access to ultra-microfinance has a positive impact on poor and vulnerable communities, reinforcing the principle that all individuals should have equitable access to financial services. UMi financing enables beneficiaries to manage financial risks, increase income, and make productive investments—leading to improvements in housing, health, and education. It also enhances resilience by providing households with financial security, empowering them to take calculated risks and pursue long-term opportunities. As El-Zoghbi (2019), argues, access to responsible credit can strengthen household resilience without undermining financial stability.

From a policy perspective, the findings have significant implications for the public sector’s role in fostering inclusive growth and women’s economic empowerment. The study underscores the importance of social capital in building trust, cooperation, and collective action—key enablers of entrepreneurship. As shown by Badaruddin et al. (2021), social capital is crucial in empowering rural communities through shared networks and mutual trust. The joint responsibility mechanism in group lending further strengthens collective accountability and resilience (Paul et al., 2016; Flap & Boxman, 2017). Conceptually, social capital integrates economic and sociological perspectives by explaining how trust and cooperation within social structures facilitate entrepreneurship (Coleman, 1988). It supports enterprise growth through social networks (Prayitno et al., 2019), training and skills development (Roxas & Azmat, 2014), and the empowerment of women (Haugh & Talwar, 2016; Saadi et al., 2016).

This research also advances the theory of financial inclusion by illustrating how UMi financing integrates previously excluded entrepreneurs into formal financial systems. By addressing asymmetric information and credit constraints, state-backed microfinance institutions such as PNM, Pegadaian, and Komida demonstrate the effectiveness of public–private linkages in extending credit to unbanked populations. Furthermore, the study broadens entrepreneurship theory by highlighting that social support, mentorship, and capacity-building are often more critical to entrepreneurial success than capital access alone.

UMi’s strong emphasis on women entrepreneurs underscores the importance of gender-responsive innovation and the value of community participation. Gender-responsive innovation is crucial for creating a more equitable and sustainable world. This approach not only promotes fairness and equality but also yields better outcomes, enhances societal well-being, and increases economic growth. As Indarti et al. (2019) observed, women’s participation in economic programs contributes significantly to community development and aligns with the broader framework of social capital (Aritenang, 2021; Badaruddin et al., 2021; Yuliastuti et al., 2017). Policymakers can strengthen financial accessibility and sustainability for women-led enterprises by integrating gender equity and social capital considerations into financial inclusion strategies.

Finally, long-term strategies are crucial for elevating the most underprivileged groups out of poverty. Extremely low-income households often use UMi loans for basic consumption rather than productive investment, as they lack functional and entrepreneurial skills. If UMi financing is allocated to extremely low-income households, it is promptly used to meet their consumption needs. Extremely underprivileged households possess inadequate functional skills and entrepreneurial abilities. Consequently, the yields from their income-producing endeavors are exceedingly minimal. Health-related expenses and household costs exacerbate the economic conditions of the underprivileged. Consequently, a strategy to address poverty is essential. Initially, loans can be substituted by facilitating access to nine vital commodities for resale in partnership with the Logistics Affairs Agency of Indonesia. Financing alone cannot resolve structural poverty; integrating financial assistance with human capital development can drive sustainable transformation. In sum, UMi exemplifies how public sector innovation—through policy reform, institutional collaboration, and community engagement—can drive inclusive economic growth. Future strategies should focus on expanding the innovation ecosystem, improving mentoring quality, and ensuring equitable access to financial services across all regions.

6. Conclusions

Indonesia, in its pursuit of sustained local economic growth, has consistently highlighted the pivotal role of ultra-micro enterprises as key drivers of social and economic development. Representing the largest segment of MSMEs, ultra-micro businesses have become a central focus in achieving the SDGs, particularly through financial inclusion and expanded access to financial services. In Indonesia’s broader socioeconomic transition, UMi complements national poverty alleviation efforts that indirectly contribute to reducing inequality. While the Ministry of Finance does not set explicit Gini reduction targets for UMi, the program supports redistribution by increasing the productive assets of ultra-micro entrepreneurs. Data from BPS show that Indonesia’s Gini coefficient declined modestly from 0.384 in 2020 to 0.375 in 2023, suggesting that inclusive financing initiatives like UMi contribute to narrowing income disparities by expanding opportunities for women and rural entrepreneurs.

Several implications for practice emerge from the study. First, policymakers must prioritize improving the accessibility of UMi financing. This can be achieved through collaboration between the Ministry of Finance and the Ministry of Communication and Information to accelerate the development of telecommunications infrastructure in remote UMi target areas. Such collaboration would strengthen digital financial infrastructure by deploying mobile and fintech agents in rural areas to facilitate loan processing and digital education.

Second, the capacity of local distribution institutions must be enhanced through targeted training and mentoring for cooperatives and community-based organizations. Recruitment and field mentoring should involve local resident’s familiar with local languages and customs. Financing schemes—including credit ceilings, tenors, and collateral requirements—should be adapted to reflect the conditions of ultra-micro enterprises typical of Papua and Maluku, such as traditional fishermen and local artisans. Implementing performance-based incentives for local distributors that successfully reach new beneficiaries could further expand UMi’s penetration.

Third, continuous monitoring and evaluation of distribution performance are needed, segmented by region and beneficiary characteristics such as gender, sector, and indigenous status. A real-time monitoring dashboard with detailed mapping of UMi coverage by village and district would improve transparency and data-driven decision-making. By implementing localized policies, inclusive technologies, and participatory approaches, the reach of ultra-micro financing in under-served regions like Maluku and Papua can be significantly enhanced, promoting equitable and sustainable access to formal financial services.

To further strengthen UMi’s impact in remote regions, several additional policy actions are proposed. First, develop local intermediation by accrediting community-based cooperatives as regional distributors, supported by targeted training from PIP and Bahana. Second, incentivize regional governments to co-finance digital infrastructure that enables mobile-based lending and financial literacy programs. Third, apply differentiated interest subsidies, providing greater support for high-poverty or geographically isolated areas. Finally, create an integrated monitoring system combining gender, sectoral, and regional indicators to track progress in real time.

This research focuses on underprivileged communities and a limited number of micro-entrepreneurs, which may restrict the generalizability of findings. Future studies could expand the scope to include additional sectors and provinces, thereby deepening the understanding of UMi’s role in sustaining MSMEs and stimulating regional economic growth. Moreover, further research should assess how to improve the quality and scalability of coaching and mentoring programs, which were identified as key success factors in this study.

7. Limitations and Further Implications

This study has several limitations. First, although the qualitative sample was information-rich, its geographic and demographic coverage was limited, focusing primarily on stakeholders based in Java. Second, the study did not include non-beneficiaries as a comparative group, which may restrict the generalizability of findings. Third, the absence of longitudinal data limits the ability to assess the long-term effects of UMi financing on poverty reduction and inequality. Future research incorporating mixed methods and broader regional participation is recommended to validate and extend these results.

While the study captured some diversity among UMi borrowers in terms of business size and operational duration, it did not analyze key socio-demographic characteristics such as age, education level, and sectoral involvement. These dimensions will be integrated into future studies through more detailed profiling and coding to explore how demographic factors influence access to finance, business growth, and mentoring outcomes. To strengthen the empirical foundation, future research may also employ a structured survey of both UMi beneficiaries and non-beneficiaries to complement qualitative insights with quantitative benchmarks related to business performance, financing access, and income change. Future data collection could also be extended to Eastern Indonesia—particularly Maluku and Papua—to examine regional variations in institutional capacity, governance, and social context.

The study further acknowledges that the lack of a comparative sample of non-beneficiary ultra-micro entrepreneurs stems from its exploratory focus on program mechanisms and institutional coordination. Future research should integrate a comparative impact analysis involving both UMi participants and non-beneficiaries with similar socioeconomic profiles to better identify the causal effects of UMi participation on entrepreneurial empowerment.

Finally, Islamic finance principles have increasingly influenced microfinance practices in Indonesia. Several UMi distributors operate under Sharia-compliant schemes—such as Sharia cooperatives (e.g., BMT Bina Ummat Sejahtera, Tamzis Bina Utama)—which apply mudarabah and murabahah contracts emphasizing profit-and-loss sharing. Although these practices are ethically aligned with Islamic finance principles, systematic analysis of their role as facilitators of inclusive microfinance remains limited. Accordingly, this study recognizes Islamic finance as an emerging yet underexplored dimension of Indonesia’s ultra-micro financing ecosystem, warranting deeper examination in future research.