Background: Micro Finance Institutions (MFIs) have been used as a tool for poverty alleviation in many developing economies globally, including Malawi. However, their sustainability in many countries has been dependent solely on loan repayment, donor aid, and subsidies. Aim: This study aimed at investigating the factors that influence the sustainability of MFIs in Malawi. Methods: A cross-sectional survey was conducted from November to December 2020 among the MFIs employees in the central region of Malawi. Convenience and purposive sampling techniques were used to collect data online using a google form sent via social media platforms. Data were analyzed using IBM SPSS software with Statistical significance placed at 0.05. Results: 120 respondents completed the survey representing 79.3% response rate, of which 63% were male. The majority of the respondents fell within the age group of 31 - 40 years, representing 58%, having attained universities and vocational colleges’ education level, representing 32.8%. With an experience of above 16 years, representing 41.2% of which were branch managers, representing 49.6%. The results of the ordinary least square regression indicated that reporting and loan management system (RLMS) (β = 0.200, P = 0.021), corporate-governance (β = 0.257, P = 0.004), and commercialization (β = 0.161, P = 0.047) were positively significantly influencing the sustainability of MFI. On the other hand, loan design/type (β = -0.211, P = 0.006), loan portfolio management (β = -0.179, P = 0.050) were found to be negatively impacting the MFI. Lastly, variables of over-indebtedness (B = 0.077, P = 0.426), loan disbursement (β = 0.121, P = 0.104) were found statistically insignificant. Conclusion: Our study argues that through commercialization, standardized reporting, and effective loan portfolio management systems, stakeholder-based approach to corporate governance, and favored board independence through scale and cost management is critical to improving MFIs financial sustainability.

1. Introduction

Microfinance has been globally accepted as one of the credible tools to alleviate poverty and financial inclusion in developing nations (Chmelíková & Redlichová, 2020; Sun et al., 2020) Further, it plays an essential role in the provision of “micro” financial services to the financially excluded population, particularly the poor and the informal sector located at the Base of Pyramid (BoP) (Kasenge, 2011). Microfinance refers to the provision of financial services including micro-savings, micro-credit, working capital loans, consumer credit, pensions, micro-insurance, and transfer of payment services and remittances to the indigent population who live below the poverty line surviving on less than $1.25. Sataloff, Johns, & Kost, n.d. reiterated that MFIs could be non-governmental organizations (NGOs), savings and loan cooperatives, credit unions, government banks, commercial banks, or non-bank financial institutions. Likewise, Mutambanadzo, Bhiri, & Makunike (2013) described microfinance as the supply of financial services to an impoverished population who traditionally lack permission to financial services from conventional MFIs. The World Bank report of 2012 states that more than 75% of the poor populations globally who earn less than $2 per day are unbanked or do not use a formal financial institution due to their lack of stable income and absence of collateral (Kasenge, 2011).

Despite the fact that MFIs are very helpful to the less privileged population, many of these institutions face challenges that affect their operational and productivity (Ousoombangi, 2018). Sustainability is one of the major challenges faced by MFIs (Muhammad, 2010). Sustaining the operational and the administration of the MFIs over a long period of time is becoming a pretty tough, challenging, and general concern for MFIs in developing nations, such as Pakistan as well as Malawi (Zeller & Sharma, 2000; Muhammad, 2010). Among other factors, non-performing loans by their clients affect the profitability of the MFIs resulting in failure to sustain and maintain themselves over the period of time (Zeller & Sharma, 2000).

However, apart from the profits they make, most of the MFIs in developing and the sub Saharan Africa (SSA) including Malawi get the supports annually worldwide in financial aid, donations, grants, and subsidies from donors, governments(public) and government agencies, Non Governmental Organizations (NGO) and private firms (Brau & Woller, 2004; Hashemi, 2007; Hermes & Hudon, 2019). Despite the support towards the MFIs however, evidence on the ground reveals that most of these institutions do not sustain their business operations such as outreach and sustainability goals (Dannroth, n.d.). As such most of these institutions have lost their business capital and are ceasing to operate. From the available literature, reasons that have been reported to influence the sustainability of MFIs in Malawi seem positively and negatively to be speculative and myopic since they do not reflect a holistic picture of the situation on the ground (MFTransparency, 2011). Given the absence of comprehensive understanding of critical issues or factors that challenge operations of MFIs and the failure of the strategies that have been put in place to sustain their operations this paper attempted to carry out a comprehensive study to address the existing knowledge gap and provide insights on its significance on how to achieve.

The study aimed at exploring the key factors that affect the sustainability of MFIs in Malawi. The study sought to address the main goal by answering the following research questions: 1) What are the factors that influence the sustainability of microfinance institutions in Malawi? 2) What are the effective strategies for achieving microfinance sustainability in Malawi? Our study contributes to the literature gap as well as informing policy makers involved in MFI and those associated with fighting against poverty in developing countries.

2. Methodology

2.1. Research Variables

2.1.1. Dependent Variable

This study regards sustainability (Loan Performance) of MFIs as the dependent variable (see Figure 1) using a 5 Likert scale question ranging from Strongly Disagree to Strongly Agree.

2.1.2. Independent Variable

In this study, the independent variables were the standardized reporting and loan performance monitoring system, loan disbursement, loan design/type, loan portfolio management, corporate governance, commercialization, and over-indebtedness (see Figure 1). A 5 Likert scale question also measured these variables ranging from Strongly Disagree to Strongly Agree.

2.1.3. Control Variables

To start with the demographic characteristics process on the factors affecting the sustainability of microfinance institutions-data were collected on gender, age group, company operations, working experience, education, and positions.

2.2. Study Design and Setting

This study was conducted in Lilongwe, Dedza, Ntcheu, Mchinji, Dowa, Kasungu, Salima, Nkhotakota, and Ntchisi districts situated in the central religion of Malawi (Figure 2). Malawi is a landlocked country located in the southern part of Africa bordering Zambia to the west, Mozambique to the south-west, and Tanzania to the north (Figure 2). The vast majority of the country’s population depends on agriculture and most of these live under the poverty line whose income usually depend on loans for farming and conducting small scale business (Munthali & Wu, 2020b, 2020a). The study adopted a cross-sectional survey design in which data was collected using a Google form that was sent online via social media platforms like WhatsApp, Facebook, and email on the first week of September 2020 to 31st December 2020. We targeted only the Microfinance employees in the Central region of Malawi.

2.3. Population and Sampling

We purposively selected the central region part of Malawi to collect data due to the fact that the region has the highest number of MFI in Malawi. This provided us an opportunity to collect more data from a larger population. Further, some researchers have strong connections with people in the central region, and this made the process of data collection much easier. There are a total of 32 microfinance institutions in Malawi which operate in all regions according (Registrar, 2019). Furthermore, with the existing COVID-19 restrictions, purposive and convenience sampling through online modes have been proved to be more effective ways of sampling and collecting data during this period (Song, Liu, He, Cai, & Xu, 2020). With this limited population, we targeted all the institutions knowing that these institutions do not have many employees as respondents in this study.

2.4. Data Analysis

IBM SPPS version 25 was used to analyze the data. Descriptive statistics were presented in the form of Frequencies, Mean, and Standard Deviation. Frequency tables were generated, and further performed regression analysis with p-value put at 0.05 as significance so as to find the study model’s predictability. An ordinary least square model was used to find factors that affect the sustainability of MFI. The model was developed as.

Y=F(X1,X2,X3,X4,X5,X6,X7,?,ei)Y=F(X1,X2,X3,X4,X5,X6,X7,?,ei)

where Y = Loan performance was the dependent variable, and X1, X2, X3, X4, ???, = were the independent variables.

2.5. Consent and Clearance

Before the questionnaire was sent, an official communication was granted from the president of the association of microfinance in Malawi, who facilitated the questionnaire’s sharing. Respondents were informed in advance that this study was voluntary and had full rights of withdrawal at any time. Informed consent was collected from all the participants before filling the form.

2.6. Validation and Reliability

The instrument was sent to other experts in the field who commented on its viability, collecting the essential information, and all the comments were taken into consideration before the final data collection. Furthermore, we pretested the instrument by sending it to 10 people who filled it, and we tried to check the errors.

3. Results

3.1. Social Demographic Characteristics

Out of 150 targeted members, 120 participated in the survey representing 79.3% response rate. The social demographic characteristics of the respondents are presented in Table 1. The results indicate that the majority of the respondents were male, representing 63% (n = 75) while the female was 37% (n = 44). In terms of age, the majority fell within the age-group category of 31 - 40 years 58% (n = 69), followed by those within 21 - 30 years 35.3% (n = 42). Furthermore, on the number of years the companies have been in operation, the results indicated that the majority have been in operation more than 16 years, representing 41.2% (n = 49), followed by those in operation between 11 - 15 years representing 29.4% (n = 35) and 6 - 10 years representing 24.4% (n = 29). On working experience, the result reveals that the majority of the respondents had been working with microfinance institutions between the range of 6 - 10 years, representing 43.7% (n = 52), followed by 11 - 20 years and 0 - 5 years, both representing 20.2% (n = 24), and finally those above 21 years representing 16% (n = 19). In terms of education, the study shows that the majority of the respondents, 32.8% (n = 39), have both vocational certificates and bachelor’s degree obtained from different colleges and universities, followed by those having MSCE 18.5% (n = 22) and lastly, those having master’s degree 16% (n = 19). Most of these were branch managers 49.6% (n = 59), and by loan officers 25.2% (n = 30).

3.2. Econometric Model Results

We conducted a linear regression analysis to determine the impact of variables such as 1) social demographic (gender, age, experience, operations, education, and positions); as well as 2) independent variables like the reporting and loan performance monitoring system, loan disbursement, loan design/type, loan portfolio management, corporate governance, commercialization, and over-indebtedness on the dependent variable sustainability (loan performance) of MFIs. Table 2 shows the results of the analysis.