Financial Technology and Financial Performance of Micro, Small and Medium Enterprises in Kakamega County, Kenya

Financial Technology and Financial Performance of Micro, Small and Medium Enterprises in Kakamega County, Kenya

Cosmus Karisa Katana, George Mukanzi Peter, Dr. Rashid Fwamba

Department of Economics, Finance and Accounting, Kibabii University

DOI: https://doi.org/10.51244/IJRSI.2025.120500151

Received: 09 May 2025; Accepted: 13 May 2025; Published: 18 June 2025

ABSTRACT

Financial performance of Micro, Small, and Medium Enterprises (MSMEs) in developing countries remains a major concern despite their dominance in the entrepreneurial sector. Many MSMEs struggle with limited access to formal financial services and inefficient resource management. The insufficient integration of financial technology (FinTech) continues to hinder their potential to enhance efficiency, improve financial inclusion, and drive sustainable economic growth. This paper explored the relationship between financial technology and the financial performance of MSMEs in Kakamega County, Kenya. The data collected for this study was mainly primary data obtained through the distribution of structured questionnaires to MSMEs in Kakamega County. The target population was 2370 MSMEs operating in Kakamega County.  The sample size in this study was 342 respondents was obtained by using the Yamane Formula (1967) where a total of 327 were duly completed and returned, yielding a high response rate of approximately 95.6%. The data obtained was analysed using SPSS software. Findings revealed that financial technology was statistically significant on the financial performance of MSMEs in Kakamega County, Kenya. The study recommends MSME owners in Kakamega County should receive targeted training programs to enhance their understanding and usage of FinTech.

Key words: Fintech, Financial Performance, MSMEs, Technology Acceptance Model

INTRODUCTION

Background of the study

The main drivers of social and economic development in Africa region are the Micro and Small Enterprises (MSEs) (Enaifoghe & Ramsuraj, 2023). They generate employment and wealth and represent a large number of businesses in most of African countries. They are broadly considered to be vital to the competitiveness of a country. MSEs are applauded for their great role in promotion of grassroots economy and equity, which might then result in a decrease in prices, low customer base, or both. This in turn erodes existing profits and creates less incentive for people to start their own ventures (Saah, 2021). Development practitioners and Policymakers concede the leading role that ICT play in economic development and growth in the world over (UNCTAD, 2009). In developing economies, limited access by MSEs to information and communication technology is acknowledged as the main hindrance for growth of business. Information is thus viewed as aiding tool to the MSEs in strengthening their operations thus growing their businesses. Nevertheless, ICT impact on development greatly depends accessibility of the technology to firm (Ngo Ndjama & Van Der Westhuizen, 2024).

Today, technology has become widespread and even crucial in people’s daily lives in both developed and developing countries. As many as 79% of adults in developing countries own a mobile phone, and 40% can connect to the internet (Mokoena, 2019). For Indonesia itself, based on the results of the Indonesian Polling study in collaboration with the Association of Indonesian Internet Service Providers (APJII) in April 2019, the number of internet users was 171.17 million people from the total population of Indonesia, namely 264 million people or 64.8% (Endris & Kassegn, 2022). From these data, it would be seen that the public’s enthusiasm for using technology is high to facilitate their daily activities, especially in the economy. The use of technology in the economy is often referred to as financial technology.

Financial technology uses technology in the financial system that produces new products, services, innovations, and business models. It can impact monetary stability, financial system stability, efficiency, smoothness, security, and reliability of the payment system (Haider 2018). Financial technology can improve a country’s economy, which can be seen from various sides. One of them is from the micro, small and medium enterprises (MSMEs), which will be the main focus of this research (Gąsiorkiewicz et al., 2020). The reason for choosing MSMEs as this research’s primary focus is that Small Medium Enterprises (MSMEs) can absorb 60% of the workforce in a country (Hadi Putra & Santoso, 2020). The evolution of FinTech has significantly altered the traditional financial ecosystem, offering innovative solutions such as mobile banking, digital payments, and crowdfunding (Leong & Sung, 2018). In Kenya, platforms like M-Pesa have revolutionized financial transactions, particularly for MSMEs (Jack & Suri, 2023). For Indonesia alone, the number of MSME actors is 59.2 million entrepreneurs, and 3.79 million entrepreneurs have used online platforms to market their products, or 8% of the number of MSME actors in Indonesia.

Efforts to improve financial literacy and inclusion in Indonesia, particularly through MSMEs, are crucial for sustainable economic growth. MSMEs with a solid understanding of financial products and services can make informed decisions, improve financial planning, and manage market uncertainties effectively (Palmié et al., 2020). For instance, studies by Grohmann, Klühs, and Menkhoff (2018) have shown that financial technology significantly enhances financial inclusion across countries. Similarly, Le, Chuc, and Taghizadeh-Hesary (2019) found that financial inclusion positively impacts financial efficiency and sustainability. Previous studies have highlighted the importance of financial technology, for MSME performance. Grohmann, Klühs, and Menkhoff (2018) demonstrated that financial technology significantly enhances financial inclusion. Similarly, Le, Chuc, and Taghizadeh-Hesary (2019) found that financial technology positively impacts financial efficiency and sustainability. However, the specific impact of these factors on MSMEs in the culinary sector in Medan remains underexplored. Additionally, the role of financial technology in bridging this gap has not been sufficiently addressed (Kim et al., 2018; Senyo & Osabutey, 2020).

In Canada, the adoption of financial technology (fintech) by MSMEs has revolutionized financial access, enabling smaller businesses to secure financing that was traditionally limited to larger firms. Fintech solutions, such as peer-to-peer lending platforms, mobile payment systems, and digital accounting tools, have simplified financial management for MSMEs. The Canadian government has supported these developments by implementing regulatory frameworks conducive to fintech innovation. Consequently, MSMEs have witnessed improved financial performance through better access to credit, reduced transaction costs, and enhanced operational efficiency (Dabrowski, 2017).

India’s burgeoning fintech ecosystem has significantly impacted the financial performance of MSMEs, particularly through digital payment platforms such as UPI (Unified Payments Interface) and online lending solutions. The government’s push for digitalization, exemplified by initiatives like “Digital India” and the Goods and Services Tax (GST), has encouraged MSMEs to adopt fintech. These technologies have streamlined payment processes, expanded market reach, and improved credit accessibility. However, challenges like low digital literacy and infrastructural limitations in rural areas remain barriers to optimal fintech utilization (Mata et al., 2023).

In Ghana, fintech solutions have played a pivotal role in fostering financial inclusion among MSMEs, particularly in underserved regions. Mobile money services like MTN Mobile Money have enabled businesses to manage transactions efficiently without relying on traditional banking infrastructure. Moreover, digital lending platforms have bridged the financing gap for MSMEs, allowing them to access credit without stringent collateral requirements. These developments have significantly enhanced the financial performance of MSMEs by promoting liquidity, reducing operational costs, and supporting business growth(Asiedu et al., 2024).

Nigeria’s fintech landscape has grown rapidly, driven by the high demand for financial inclusion among its large population of MSMEs. Platforms such as Paystack and Flutterwave have empowered small businesses by facilitating seamless payments and e-commerce integration. Furthermore, fintech innovations in micro-lending and credit scoring have addressed the financing needs of MSMEs, enabling them to invest in business expansion and innovation (Babajide et al., 2020). Despite these advances, challenges such as cybersecurity risks and limited regulatory clarity persist in the sector.

In Tanzania, financial technology has emerged as a crucial enabler for MSMEs, particularly in the informal sector, which dominates the economy. Mobile banking and digital payment systems, including M-Pesa, have transformed how businesses conduct transactions and save money. Fintech platforms have also introduced micro-lending services, allowing small businesses to secure capital for growth. However, the uptake of fintech among MSMEs is hindered by issues like limited internet access, digital illiteracy, and trust in technology (Masialeti, 2021).

Uganda’s MSMEs have benefitted immensely from fintech advancements, particularly in areas like mobile money and digital credit. Services such as Airtel Money and MTN Mobile Money have expanded financial access to previously unbanked entrepreneurs. Fintech solutions have also supported MSMEs in improving cash flow management and accessing flexible credit. However, inadequate infrastructure and a lack of comprehensive regulatory frameworks continue to limit the full potential of fintech in boosting financial performance among Ugandan MSMEs (Turinawe, 2023). This comparative analysis highlights how fintech has become a transformative force in improving the financial performance of MSMEs across diverse regions, albeit with unique challenges and opportunities in each country.

Kenya is a leader in financial technology adoption in Africa, with MSMEs significantly benefiting from the robust fintech ecosystem. Mobile money platforms such as M-Pesa have revolutionized how businesses manage transactions, offering secure, affordable, and convenient payment solutions. These innovations have enabled MSMEs to expand their customer base by facilitating e-commerce and digital transactions. Additionally, fintech-powered lending platforms like Tala and Branch have bridged the credit access gap, providing microloans without the need for extensive documentation or collateral. This has empowered small businesses to invest in growth and operational efficiency, boosting their financial performance (Anyanga et al., 2025).

Furthermore, the Kenyan government has supported the fintech sector by implementing policies and initiatives such as the Digital Economy Blueprint, which seeks to harness technology for economic development. MSMEs in Kenya have also benefited from digital bookkeeping tools and tax compliance applications that simplify financial management and enhance transparency. However, challenges such as high transaction fees, cybersecurity risks, and inadequate digital literacy in rural areas hinder the optimal utilization of fintech by MSMEs. Despite these obstacles, Kenya continues to set an example of how fintech can drive financial inclusion and improve the financial sustainability of small businesses (MacArthur, 2021).

Problem statement

Micro, Small, and Medium Enterprises (MSMEs) are the backbone of Kenya’s economy, contributing significantly to employment and GDP (Otieno, 2021). However, their growth and sustainability are often hindered by challenges such as limited access to credit, inefficient financial management practices, and high transaction costs. In Kakamega County, these challenges are exacerbated by a lack of infrastructure, low levels of financial literacy, and minimal adoption of modern financial technologies (Vincent, 2020). Although FinTech has emerged as a potential solution to address these barriers by improving access to financial services and reducing operational costs, its adoption among MSMEs in the region remains suboptimal. Many enterprises are unaware of available FinTech solutions, while others are deterred by concerns about security, cost, and the perceived complexity of digital platforms. Without a clear understanding of the relationship between FinTech adoption and financial performance, MSMEs in Kakamega County risk being left behind in an increasingly digital economy (Dwivedi et al., 2023). This study sought to bridge this gap by investigating how FinTech impacts the financial performance of MSMEs in Kakamega County, Kenya (World Bank, 2022; KNBS, 2023).

Objective of the study

The main objective of the study was to investigate the impact of Financial Technology and the financial performance of MSMEs in Kakamega County, Kenya.

Research Hypothesis

Financial Technology has no statistically significant relationship on the financial performance of MSMEs in Kakamega County, Kenya.

LITERATURE REVIEW

Theoretical Literature

This study was grounded on two theories:

Technology Acceptance Model

The Technology Acceptance Model (TAM), developed by Fred Davis in 1989, is a theoretical framework that examines the factors influencing technology adoption (Davis, 1989). It focuses on two primary determinants: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). PU refers to the extent to which a person believes that using a technology will enhance their job performance, while PEOU relates to the degree of effort required to use the technology. Together, these factors influence an individual’s attitude toward using the technology, which then shapes their intention to adopt and use it (Otieno, 2021).

In the context of financial technology (FinTech) and its impact on the financial performance of MSMEs in Kakamega County, TAM provides valuable insights into understanding how business owners perceive and integrate digital tools like mobile payment platforms, online banking, and accounting software. For instance, the widespread adoption of mobile money services such as M-Pesa in Kenya can be attributed to their perceived usefulness in facilitating quick, secure, and cost-effective transactions, as well as their ease of use, even for individuals with limited technological skills.

The relevance of TAM lies in its ability to identify the psychological and behavioural factors that influence FinTech adoption. For MSMEs in Kakamega County, these insights can help policymakers and service providers design interventions to improve adoption rates. FinTech tools enable MSMEs to increase efficiency, reduce transaction costs, and improve customer satisfaction, leading to enhanced revenue and profitability and Simple interfaces and user-friendly features make FinTech accessible to a broader range of MSME owners, including those with low digital literacy (Vincent, 2020).

Despite its strengths, TAM has notable weaknesses when applied to the adoption of FinTech by MSMEs. The model does not account for external factors such as infrastructure challenges, cultural influences, and regulatory constraints, all of which significantly affect FinTech adoption in rural settings like Kakamega County. TAM overlooks trust issues and concerns about data privacy, which are critical for MSMEs deciding whether to adopt digital financial solutions. The model assumes a linear relationship between perceptions and adoption, neglecting the role of other variables like peer influence, organizational support, and financial constraints (Ouma et al. 2017).

To address these limitations, TAM can be integrated with other frameworks, such as the Unified Theory of Acceptance and Use of Technology (UTAUT), to include additional factors like facilitating conditions and social influence. Moreover, tailoring FinTech solutions to the unique needs of MSMEs in Kakamega County considering their local context can enhance both PU and PEOU, making technology adoption more feasible and impactful.

Diffusion of Innovations Theory

The Diffusion of Innovations (DOI) Theory, developed by Everett Rogers in 1962, explains how new technologies or innovations spread within a population or organization over time (Rogers et al., 2014). It highlights the stages through which individuals or groups adopt an innovation and the factors influencing this process. The theory identifies five adopter categories: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. It also outlines five key attributes that determine the rate of adoption: Relative Advantage, Compatibility, Complexity, Trialability, and Observability.

In the context of FinTech adoption by MSMEs, the DOI theory provides a comprehensive framework for understanding how new financial technologies spread across different business segments. While DOI offers valuable insights, it has limitations when applied to FinTech adoption among MSMEs. To begin with, this theory assumes a uniform adoption process, overlooking the diverse socio-economic conditions of MSMEs in Kakamega County. In addition, DOI does not adequately address systemic barriers such as poor internet connectivity, inadequate infrastructure, and high costs of technology, which are critical in rural settings. Lastly, the theory places emphasis on individual decision-making and may neglect organizational and community-level dynamics affecting adoption (Dwivedi et al., 2023).

DOI theory complements the Technology Acceptance Model (TAM) by focusing on the broader adoption process, including social and cultural factors. Together, these theories offer a robust framework for understanding the dynamics of FinTech adoption and guiding strategies to enhance financial performance among MSMEs in Kakamega County. For instance, targeting early adopters with tailored campaigns can accelerate diffusion, while addressing complexity and compatibility issues can improve the perceived ease of use and usefulness of FinTech tools.

conceptual Framework

Independent variable                                                                 

Dependent variable

Financial Performance

• Profitability

Figure 2.1: conceptual Framework

RESEARCH METHODOLOGY

A descriptive research design was adopted to investigate the relationship between Financial Technology (FinTech) adoption and the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Kakamega County. This design was deemed appropriate as it enables the researcher to systematically describe and interpret the characteristics of the population and the phenomena under study without manipulating the variables (Creswell, 2014). The target population comprised 2,370 registered MSMEs in Kakamega County, drawn from diverse sectors including retail, services, manufacturing, and agribusiness. Given the size of the population and the need for cost-effective and reliable generalization, Yamane’s (1967) formula was employed to calculate the appropriate sample size. The formula is stated as:

n=N1+N(e)2n =

Where:

n = sample size

N = population size (2,370)

e = margin of error (0.05)

n=2370/1+2370(0.05)²=342

Based on this calculation, a sample size of 342 MSMEs was selected. This ensured an adequate representation of the population, allowing for meaningful analysis and generalization of the findings. Primary data was collected using structured questionnaires, which were administered to the owners or managers of the selected MSMEs. The questionnaire was designed to capture key aspects of FinTech usage as well as indicators of financial performance such as profitability, revenue growth, and operational efficiency (Mugenda, 2003). Prior to data collection, the research instrument was pre-tested on a small subset of the population to ensure reliability and validity. Feedback from the pilot study was used to refine the questionnaire, ensuring clarity and relevance of the questions. Collected data was cleaned, coded, and analysed using both descriptive and inferential statistics. Descriptive statistics such as frequencies, percentages, means, and standard deviations were used to summarize the demographic and FinTech adoption profiles of the respondents (Babbie, 2007). Inferential statistical techniques, including correlation and regression analysis, were employed to determine the nature and strength of the relationship between FinTech usage and financial performance of MSMEs.

The results of the analysis were presented in well-organized tables and charts for easy interpretation and comparison. The findings offer insights into the extent of FinTech adoption among MSMEs in Kakamega County and its implications for their financial outcomes.

RESULTS AND DISCUSSION

Out of the 342 questionnaires distributed to the targeted respondents, a total of 327 were duly completed and returned, yielding a high response rate of approximately 95.6%. This response rate is considered highly acceptable for survey-based research and exceeds the generally recommended threshold of 60% for academic studies, as suggested by Babbie (2007), who notes that response rates of 70% and above are regarded as very good. The high rate of return in this study enhances the reliability and generalizability of the findings.4.2 Descriptive statistics: Financial Technology and Financial Performance of Micro, Small, and Medium Enterprises in Kakamega County, Kenya

Table 1

Statement	Mean	Std dev
Mobile banking has significantly streamlined my business’s financial transactions.	3.73	1.084
My business has experienced better financial record-keeping due to financial technology tools.	3.91	1.076
There is inadequate knowledge and training on the use of financial technology in my business.	4.14	1.231
Government and other stakeholders should reduce transaction costs associated with financial technology.	4.09	1.109
Financial technology has positively impacted the overall performance of my business.	3.94	1.112
There is inadequate knowledge and training on the use of financial technology in my business.	3.67	1.157
Overall mean	3.91	1.1282

Source: Field Data (2025)

The descriptive statistics in Table 1 highlight respondents’ perceptions of financial technology and its impact on the financial performance of Micro, Small, and Medium Enterprises (MSMEs) in Kakamega County, Kenya.

The statement “Mobile banking has significantly streamlined my business’s financial transactions” recorded a mean score of 3.73 with a standard deviation of 1.084, indicating moderate agreement among respondents, albeit with some variability in responses. Similarly, the statement “My business has experienced better financial record-keeping due to financial technology tools” received a slightly higher mean score of 3.91 and a standard deviation of 1.076, reflecting a general consensus on the positive role of financial technology in enhancing record-keeping.

Respondents strongly agreed with the statement “There is inadequate knowledge and training on the use of financial technology in my business,” which had the highest mean score of 4.14 and a standard deviation of 1.231, indicating widespread acknowledgment of the knowledge gap. Furthermore, the need for stakeholders to reduce transaction costs associated with financial technology also received strong agreement, with a mean of 4.09 and a standard deviation of 1.109.

The overall perception of financial technology’s impact on business performance was positive, as evidenced by the statement “Financial technology has positively impacted the overall performance of my business,” which recorded a mean of 3.94 and a standard deviation of 1.112. However, the repeated statement on the inadequacy of knowledge and training garnered a slightly lower mean of 3.67 and a standard deviation of 1.157.

The overall mean score of 3.91 and standard deviation of 1.1282 suggest that respondents generally view financial technology as beneficial to their businesses. However, the variability in responses highlights differences in individual experiences, particularly concerning knowledge and training on financial technology use. Addressing these gaps could further enhance the adoption and impact of financial technology among MSMEs in the region.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.698a	.487	.486	.922
a. Predictors: (Constant) Financial Technology

ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	262.189	1	262.189	308.696	.000b
	Residual	276.037	325	.849
	Total	538.226	326
a. Dependent Variable:  Financial Performance.
b. Predictors: (Constant), Financial Technology

Source: Field Data (2025)

The model summary presents the overall strength and predictive power of the relationship:

Correlation Coefficient (R = 0.698): This value indicates a strong positive correlation between financial technology and financial performance. It suggests that improvements in financial technology adoption are strongly associated with better financial performance of MSMEs. R Square (R² = 0.487): R² explains the proportion of variation in the dependent variable (financial performance) that is accounted for by the independent variable (financial technology). Here, 48.7% of the variation in financial performance is explained by financial technology, demonstrating that FinTech is a significant predictor. Adjusted R Square (0.486): The adjusted R² value accounts for the model’s complexity and ensures that the estimate remains unbiased when additional predictors are added. With an adjusted value nearly equal to R², the model is robust and well-fitted.

The Analysis of Variance (ANOVA) tests the overall significance of the model:

Regression Sum of Squares (262.189): This value represents the variation in financial performance that is explained by the independent variable, financial technology. Residual Sum of Squares (276.037): This value indicates the variation in financial performance not explained by financial technology, highlighting factors outside the scope of this model. The correlation coefficient (R = 0.698) and R² = 0.487 are consistent with studies such as Jack and Suri (2011), which found that mobile money platforms like M-Pesa have significantly enhanced the revenue and profitability of businesses in Kenya by providing efficient payment systems. Similarly, Ouma et al. (2017) demonstrated that digital financial services reduce transaction costs and improve access to credit, leading to better financial outcomes for small businesses. These studies corroborate the finding that nearly half (48.7%) of the variance in financial performance can be attributed to financial

CONCLUSION

The model demonstrates that financial technology significantly influences the financial performance of MSMEs in Kakamega County, explaining nearly 49% of the variation in financial performance. The strong positive correlation underscores the importance of adopting financial technology to enhance MSMEs’ financial outcomes. However, the unexplained variation (51.3%) suggests the need to investigate other factors influencing financial performance, such as market conditions, managerial skills, and government policies.

RECOMMENDATIONS BASED ON FINDINGS

The study made the following recommendations:

Promote Financial Technology Awareness and Training – Given the significant relationship between financial technology and financial performance, MSME owners in Kakamega County should receive targeted training programs to enhance their understanding and usage of FinTech solutions. This could include workshops, online tutorials, and partnerships with FinTech providers to demonstrate the practical benefits of digital tools.

Enhance Accessibility to Financial Technology Platforms – Policymakers and FinTech developers should prioritize improving the accessibility of financial technology by expanding internet infrastructure in rural and underserved areas, ensuring that FinTech solutions are compatible with basic mobile devices widely used in Kakamega County and Offering subsidies or incentives to MSMEs adopting FinTech to offset initial costs.

Encourage Collaboration Between FinTech Providers and MSMEs – Financial institutions and FinTech companies should develop affordable, user-friendly solutions tailored to the needs of MSMEs. For example, simplified digital accounting software and mobile-based credit assessment tools can help businesses streamline operations and access funding.

Address Digital Literacy Gaps – With findings suggesting that knowledge and training on FinTech use are inadequate, the government, non-governmental organizations (NGOs), and financial institutions should collaborate to implement community-based digital literacy programs. These initiatives should focus on equipping MSME owners with the skills to adopt and optimize FinTech solutions effectively.

Diversify Financial Technology Offerings – FinTech companies should expand their service offerings to include more advanced tools like digital credit scoring, inventory management, and data analytics to support the diverse needs of MSMEs.

Encourage Research and Development – Further studies should explore the unexplained variation in financial performance to identify other contributing factors, such as managerial skills, competitive dynamics, and macroeconomic conditions. This will provide a holistic understanding and more targeted recommendations for enhancing MSME performance.

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