FinTech as a digital innovation in microfinance companies – systematic literature review Open Access

In an era where digital transformation is remodelling industries globally, FinTech stands out as a disruptive force in improving the operational efficiency and customer reach of microfinance companies. FinTech integration promises to transform customer service and adequate resource management in addition to streamlining administrative procedures in microfinance operations (Liu et al., 2020). However, it is widely acknowledged that one of the most important tools for modern businesses' organisational growth, development and operational effectiveness is financial technology (FinTech) (Gabor and Brooks, 2017). This is in relation to research conducted by Lwesya et al. (2023) which highlights three sorts of significant resources in any organisation. These resources include technology infrastructure, processes and employee expertise, an example of the kind of resource synergy that every microfinance company needs to survive and flourish.

FinTech refers to the use of technology to improve financial services and it includes a wide range of services that cater to different areas of finance, such as payments, investments and loans (Demir et al., 2022). FinTech companies offer innovative solutions that leverage technology to solve financial problems. Some examples of FinTech companies are PayPal, Square, Robinhood and TransferWise (Shaikh et al., 2017).

Thus, Dorfleitner et al. (2022) argued that FinTech has become a digital innovation because it represents a fundamental shift in the way financial services are delivered. The financial industry has historically been dominated by large financial institutions, which have relied on legacy systems and manual processes. Hence, this digital transformation has been driven by a variety of technological advances, including mobile computing, cloud computing, blockchain technology and artificial intelligence (AI) (Velazquez et al., 2022).

The microfinance companies, in particular, has been greatly impacted by the digital revolution, as technology enables microfinance companies to reach previously underserved clients with greater ease and efficiency (Dorfleitner et al., 2022). FinTech has given microfinance companies the ability to digitise and automate their services, providing a more convenient management operations and impacting organisational performance and competitiveness (Shaikh, 2021).

Moreover, the use of FinTech tools in microfinance companies' organisational structures has increased in recent years. Through mobile banking, digital wallets and other tech-driven solutions, these technologies offer a wide range of services to the impoverished in rural and urban areas, including digital payments, online savings, automated insurance and remittance platform (Piotrowski and Orzeszko, 2023). It is important to recognise the main objectives of incorporating FinTech into microfinance have been to satisfy the organisation’s operational requirements, improve service provision and guarantee the long-term viability of microfinance activities (Banna et al., 2022).

As the popularity of FinTech in microfinance increases, most microfinance companies have therefore implemented internal initiatives targeted at encouraging the adoption of FinTech. This entails building organisation resource capacities, establishing supporting internal policies and internal digital ecosystems that is favourable to the growth of digital products and services (Katsamakas and Sánchez-Cartas, 2022), as a part of the general innovation ecosystems (Klimas and Czakon, 2022) and organisational identity in the digital age (Czakon et al., 2024).

In this research, we take into consideration the dynamic shift in microfinance companies adopting FinTech as a digital tool over the last ten years. The existing and growing body of work tends to centre more on the impact of technological change, service innovation and digital transformation. However, there are few works in the literature on the subject under review devoted to the understanding of key drivers influencing digital innovation in FinTech-driven microfinance companies. And most of these works focus on a relatively narrow understanding of the key drivers of FinTech in relation to digital innovation, most important areas of research to date and emerging areas for future research in microfinance literature.

The current research consolidates all works on FinTech in microfinance companies, identifies key drivers of FinTech as a digital innovation in microfinance companies, and suggests the likely future research direction. To achieve our goal, we will seek to answer the following research questions:

This study contributes significantly to the literature on FinTech and microfinance in several ways. The research findings provide knowledge on the key themes and current directions in the literature. Compared to other studies, our paper expands beyond the impact of technological change and digital transformation but also pays attention to the key drivers of FinTech as a digital innovation in microfinance companies. Methodologically, the study employs selected multidimensional statistical methods, such as correspondence analysis and log-linear model, to visualise complex relationships within the literature. This analysis reveals patterns of knowledge sharing amongst scholars and identifies gaps in the existing literature, proposing areas for further exploration. The study’s originality is underscored by its use of advanced research methods. To our knowledge, this is the first study on FinTech as a digital innovation in microfinance to use a selected multidimensional statistical method, such as correspondence analysis and log-linear model in a systematic literature review.

A systematic review (based on the publications indexed in the Web of Science and Scopus databases), using selected multidimensional statistical methods, such as correspondence analysis and log-linear model, were applied. Following this introduction, the paper is structured as follows: Section 2 presents the literature review. Section 3 describes the research methodology employed in this study. Section 4 presents the findings and discusses them considering the research objectives. Finally, Section 5 concludes the paper, summarising the key findings, discussing the implications and suggesting avenues for future research.

FinTech or financial technology, is a rapidly growing industry that has been disrupting the traditional financial industry through the integration of technology into financial services. While there is general agreement that FinTech is a digital innovation, there is debate amongst different authors about the precise definition and theoretical underpinnings of FinTech.

FinTech is often viewed as a digital innovation that has emerged due to advancements in technology. According to a definition by Gabor and Brooks (2017), FinTech is “the use of technology to provide financial services and products that were previously offered only by traditional financial institutions.” The use of technology allows FinTech companies to offer services that are faster, more convenient and cost-effective.

Similarly, FinTech has been described as a “disruptive innovation” by Kong and Loubere (2021). They define disruptive innovation as “a process by which a product or service takes root initially in simple applications at the bottom of a market and then relentlessly moves upmarket, eventually displacing established competitors”. FinTech has disrupted the traditional financial industry by offering new and innovative services that are more attractive to consumers.

In the exploration of FinTech management, Lăzăroiu et al. (2023) pay particular attention to the fusion of blockchain, cloud computing and AI. They draw attention to how it affects the delivery of financial services, management performance and business efficiency. AI algorithm, and big data analytics increase mobile payments, risk assessment, fraud detection and transaction speed.

The concept of FinTech has also been linked to the broader concept of digital transformation. According to Dorfleitner et al. (2022) digital transformation depicts integration of digital technology into every sector of a business, developing fundamental changes to how businesses carry out operations and deliver value to clients. FinTech is seen as a key driver of digital transformation in the financial industry, offering new and innovative ways of delivering financial services. Therefore, FinTech has been widely regarded as a digital innovation that is disrupting the traditional financial industry by offering new and innovative services that are faster, more convenient and cost-effective. It is often viewed as a disruptive innovation that is driving digital transformation in the financial industry. Various definitions of FinTech highlight the use of technology, the various technologies driving FinTech innovation, the interconnectedness of the various players in the FinTech ecosystem and the broader concept of digital transformation.

Microfinance is a concept that emerged in the 1970 and 1980s, as a response to the failure of traditional banking systems to serve the needs of the poor. According to Banna et al. (2022), microfinance refers to “the provision of financial services to people with low-income status, including savings, money transfers, credit and insurance. The definition of microfinance by other authors has offered slightly different perspective to what microfinance depicts. For example Khan et al. (2021) explain microfinance as “the delivery of financial services to the vulnerable (poor) at the lower tier of the economic pyramid, including microinsurance microcredit, microenterprise development and microsavings. Similarly, Ndungu and Moturi (2020) think that microfinance as “the supply of savings, loans and other basic financial services to the low income earners. Despite these variations, there is a general consensus that microfinance is about providing financial services to people who have been excluded from the formal banking sector, either because they lack collateral, credit history or access to traditional banking channels (Orozco Ramos, 2022). The impact of FinTech on microfinance firms has revolutionised the business operations and delivery in the industry. Microfinance companies have integrated FinTech to streamline their operations, enhance efficiency and improve their services to clients.

A study by Musaigwa and Kalitanyi (2023) conducted on leadership strategies in the FinTech and microfinance amid digital transformation-driven organisational change yielded some important findings. The study disclosed that managers persist in utilising conventional leadership approaches, such transformational leadership, which are still applicable and efficacious in the digital age. Furthermore, the research underscored the significance of involving people of the organisation in the development and execution of change, stressing that employee support is a prerequisite for effective change management. To fulfil the needs of the digital era, the study advised FinTech executives to embrace digital leadership, even while traditional leadership positions are still important (Sharma et al., 2024). According to Musaigwa and Kalitanyi (2023), digital leadership entails acquiring new skills like networking intelligence and creative business models, which are essential for managing digital change and preserving competitiveness.

According to Bhagat and Roderick (2020), the characteristic of FinTech in microfinance companies is the provision of innovative digital financial services to unbanked or underserved populations. FinTech has enabled microfinance companies to offer personalised services such as mobile banking, mobile wallets and online lending platforms, which are convenient, accessible and affordable. The characteristic of FinTech in microfinance companies points to the use of big data and AI to enhance credit risk assessment and customer profiling. Ashta and Herrmann (2021) explained that FinTech-enabled microfinance companies utilise data analytics to evaluate the creditworthiness of borrowers, which reduces the risk of loan defaults and enhances financial inclusion. Microfinance and the adoption of blockchain technology to increase the transparency and security of financial transactions as presented by Milana and Ashta (2021) signify one key characteristics of FinTech in microfinance. Blockchain technology enables microfinance companies to create tamper-proof records of financial transactions, which enhances transparency and reduces the risk of fraud.

The work of Kallmuenzer et al. (2024) looks at the benefits and drawbacks of enterprises going digital. Using information and communication technologies to increase productivity and speed is how managers define digitalisation. Many organisations continue to use outdated systems despite new tools because they are risk averse and expensive. The study emphasises that success requires both hard and soft digital abilities, pointing out that digitalisation improves stakeholder communication, internal procedures and consumer interactions. However, growth is hampered by conservative views, a lack of funds and inadequate skill sets. Effective digitalisation and increased commercial performance require a strategic strategy that combines technology, expertise and a positive company culture. One of the most significant benefits of FinTech for microfinance is the ability to reduce transaction costs and sustainable operations as argued by Ozili (2020). By using digital platforms, microfinance companies can automate their loan processing, reduce paperwork/administrative burden and reach more customers at a lower cost. This can translate into lower interest rates and fees for borrowers, which is a critical factor for the management and sustainability of microfinance operations. It can be considered as an innovation related to the environment (Szopik-Depczyńska et al., 2021). Thus, the advantage of FinTech for microfinance is the ability to expand the range of services offered to clients. For example, Ascarya and Sakti (2022) say that “microfinance companies can use digital channels to provide savings accounts, insurance, and other products that were previously out of reach for their clients”. This can help to deepen the inclusion of low-income populations and enhance their resilience to economic shocks. FinTech provides advanced tools for risk assessment and management, including algorithms and data analytic. By using digital tools to collect and analyse data on clients' creditworthiness, behaviour and preferences, microfinance companies can make better lending decisions and reduce the risk of default (Bollinger and Yao, 2018). This can lead to a more sustainable and responsible microfinance business environment, which is essential for the long-term impact of microfinance on poverty reduction.

It is worth noting that, there are also challenges and risks associated with the intersection of FinTech and microfinance. According to Wang and Drabek (2021), one of the main concerns is the potential for over-indebtedness and exploitation of vulnerable clients, particularly in cases where digital lending platforms use aggressive marketing tactics, opaque pricing and high interest rates. This highlights the importance of consumer protection and responsible business practices in the FinTech–microfinance ecosystem. The social mission of microfinance faces risk due to the impact of FinTech according to some critics. Bu et al. (2021) argues that FinTech may prioritise financial returns over social impact, leading to a dilution of microfinance’s original goals of poverty reduction and empowerment.

In summary, research into FinTech in microfinance companies predominantly focusses on the technological change and operational efficiencies it brings. There is a significant gap in addressing the broader organisational and strategic drivers, particularly regarding the integration of these technologies into existing management structures and processes. Moreover, while studies frequently discuss the technological benefits, there is limited exploration of the important research path and emerging areas for future research. Furthermore, the current literature mainly employs basic statistical methods, with a notable absence of advanced analytical techniques like multidimensional correspondence analysis combined with cluster analysis. Addressing these limitations, the present work aims to extend and complement the existing literature presented above.

In the work to identify the most important directions of research to date and to indicate new, emerging areas of research concerned with application of FinTech solutions in microfinance companies, two-stages procedure was applied (Figure 1).

In the framework, the lead author carried out all searches determining and selecting studies relevant to the topic under review within a specific period 2010–2023. Web of science (WoS) was used for the search to identify peer-reviewed articles under the scope of the study. Google scholar was used to search for additional publications. Only scientific articles in English were included. Thereafter, primary retrieval, assessment and evaluation of potentially relevant study samples according to the inclusion and exclusion criteria illustrated in Table 1.

The basis for a systematic literature review using selected methods of multivariate analysis is publications available in the Web of Science database. At the first stage, based on selected keywords and their various combinations, works were sought that would describe the research results that fit into the scope of the analysed area. VOS viewer software version 1.6.14 was used to study the relationships between the works identified in this way and to identify clusters connecting the most frequently repeated research terms selected during the study. The final effect of the first stage of the research is a map of dependencies between the most frequently used terms in the analysed works.

At the second stage, keywords identified in this way were used to build models of relationships between selected keywords describing the results of quantitative or qualitative research presented in the analysed studies. For building models of relationships correspondence analysis was used. It is a method that can be used for both qualitative and quantitative data analysis.

Its detailed description and examples of application can be found, amongst others, in the works of: “Greenacre, 2010, 2017; Frankowska and Cheba, 2022).

The multidimensional correspondence analysis that was used for the study is an extension of the simple correspondence analysis to issues with the number of variables greater than two. It is carried out on a matrix of codes (system), where individual rows correspond to successive observations and columns – variants of variables. In fact, it is customary to analyse the inner product of such a matrix, which is called the Burt Table.

An important step in the correspondence analysis is to determine the dimension of the real space (K) of the co-occurrence of all categories of variables adopted for the study. The following formula is used for this purpose:

where: $Jq$ – number of feature categories q.

The most common effect of using correspondence analysis is a scatterplot, also referred to as a perception map, in which individual points represent categories for individual variables. In correspondence analysis, coordinates are determined for each variable category, which will allow to present this category in the form of a point on a scatterplot. In more advanced cases, it may be necessary to use, for example, cluster analysis to visualise the results. This method is used when the projection space of the analysed features is more than two-dimensional.

According to Greenacre’s criterion, the best choice is the dimension of projecting categories of variables in which the own values follow the condition $λB,k>1Q$⁠.

Greenacre added to the complex criterion of choosing the relevant own values (⁠$λB,k>1Q$⁠) the way to “improve” the results of the analysis of variables given in the form of Burt’s matrix (Greenacre, 2017):

where: Q – number of variables, $λB,k$ – k-th own value.

When using the correction of Greenacre, new coordinates for the categories of characteristics are set according to the formula:

Where: $F∼$ – matrix of new coordinates for variable categories, F^* – matrix of the primary values of coordinates for variable categories, $Γ−1$ – diagonal reverse matrix of the peculiar values, $Λ∼$ – diagonal matrix of the modified own values.

The basis for the analyses at both stages of the study is publications indexed in the Web of Science database. In total, 6,115 publications from the years 2000–2023 were identified in the WoS database, which in the title, keywords or abstract referred to such terms as: FinTech or digital innovation ^[1]. In the set of publications created in this way, additional, narrower research areas were sought by adding further terms to the indicated keywords, narrowing the area of analysis. The results of this stage of the study are presented in Table 1.

The conducted analyses show that the increase in the number of publications referring to such terms as: financial technology, FinTech, innovation and microfinance has been observed basically since 2014, in which 27 papers were published. T0 2018, there were already 214 studies indexed in the WoS database and another 247 by the end of 2023. Along with the increase in the number of publications, the number of their citations also increased, from 342 in 2018 to 1,686 in 2023. These are mainly papers published by authors from: the USA (168 publications), England (120), China (77) and India (54). In nearly 300 of them, microfinance and entrepreneurship have received considerable attention (117). In many of them we can also find references to the various sustainable development goals (SDGs), mainly: Goal 1. No poverty (461 publications), Goal 10. Reduce inequality (314) and Goal 9. Industry, innovation and infrastructure (158) (Figure 2).

Despite the growing number of publications and their citations, the created database of works referring to a more narrowed area of digital innovation is not impressive. In total, in the analysed period, only 461 publications were identified in the WoS database using this search method. This confirms the limited exploration of issues in this field. For this reason, the results of the last two searches were used in further analyses.

The integration of FinTech into microfinance companies has been significantly influenced by various strategic and managerial considerations. This section delves into the key drivers, highlighting how these factors align with broader organisational goals and strategies. The findings draw upon existing literature to provide a nuanced understanding of why microfinance is increasingly adopting FinTech solutions.

One of the main drivers for microfinance companies implementing FinTech as a digital tool, is to increase their operational efficiency. Consider managing a small firm where you are responsible for handling a large volume of transactions, many clients and making sure everything goes as planned. AI and blockchain are two examples of FinTech components that help automate these procedures, speeding up operations and lowering human error. Blockchain, for instance, manages transactions safely and transparently, making them impervious to tampering. This is especially helpful in places where there may not be as much trust in credit companies. Microfinance companies can lower the risk of customer defaults on their product by using AI to help with customer profile and credit risk assessment. This allows the companies to make better informed lending decisions.

In literature, studies have shown that operational efficiency is a significant driver for implementation of FinTech. For example, Ashta and Herrmann (2021) emphasises how AI is revolutionising the banking, investing and microfinance sectors of the financial system. Enhancements in productivity, efficiency and customisation made possible by the integration of AI have resulted in notable business development and strategic potential for microfinance companies. The report does, however, also provide a warning regarding the possible dangers of implementing AI, including data bias, financial model overfitting and the difficulties in maintaining system security and data privacy. Because AI is dynamic, it necessitates constant attention to detail and a well-rounded strategy to maximise advantages while minimising risks. Musaigwa and Kalitanyi (2023) further discuss how strategic deployment of these technologies requires careful planning and investment, emphasising the need for proper change management.

This is further supported by the study of Taherdoost (2018) who investigate the technology adoption process model in businesses. It is worth mentioning as it sheds light on the strategic decisions that microfinance companies make when incorporating FinTech solutions. Their results highlight how adoption decisions are influenced by managerial support, organisational preparedness and the perceived advantages of technology. This is especially important for microfinance companies, since the management there needs to justify the integration of FinTech solutions into current systems by pointing out the operational efficiencies they provide. This underscores the essential need for managers to persistently pursue and adopt technological innovations that boost operational efficiency.

For microfinance companies, increasing customer satisfaction is a top priority, particularly since consumers demand more individualised, efficient and easily accessible services another key driver in FinTech as a digital tool. FinTech offers technologies like big data analytics that can be used to learn more about the preferences and behaviours of its customers. With the use of these information, microfinance organisations can more successfully customise their services to match the needs of specific clients.

According to Fianto et al. (2020), using data analytics for customer insight can greatly improve service personalisation, which, as a result, leads to increased levels of customer satisfaction and loyalty. This is consistent with research by Ashta and Herrmann (2021), who found that microfinance companies are able to provide customised financial products thanks to AI and machine learning technologies, increasing consumer engagement and retention.

Our finding identified that programmes for education are necessary to guarantee that customers can take full advantage of FinTech advancements. By putting in place digital literacy initiatives, financial institutions may better serve their clientele by assisting them in comprehending and utilising emerging technologies. This corroborates the study by Hasan et al. (2024) which shows that the relationship between the uptake of FinTech and the efficiency of microfinance services is significantly mediated by financial literacy. It has been discovered that customers who possess greater levels of financial literacy are more likely to engage and make better use of the FinTech solutions offered by microfinance organisations. This helps achieve more general financial inclusion goals in addition to improving their financial stability. Additionally, the study indicates that raising financial literacy can greatly increase the beneficial effects of FinTech on microfinance services by empowering consumers to handle their money more skilfully and make better financial decisions. This is further supported the results of the study of Okičić and Kokorović Jukan (2023) that the relationship between the uptake of FinTech and the efficiency of microfinance services is significantly mediated by financial literacy. It suggests that raising target audiences' financial literacy can greatly maximise the advantages of FinTech and improve consumers' financial results. Additionally, the results indicate that financial literacy-focussed interventions may improve the FinTech solutions' overall uptake and efficacy in the microfinance industry, supporting the goal of financial inclusion more broadly.

The corroborating citations from other writers demonstrate the scope of the literature that validates the significance of emphasising customer experience as one of the key drivers for FinTech adoption in microfinance organisations. These findings highlight how important it is for microfinance managers to give technology and projects that improve the customer journey top priority and funding. In addition to meeting consumer demands, this strategic focus on the customer experience seeks to set microfinance companies apart in a competitive market.

The strategic goal of financial inclusion is not just a testament to the social mission of microfinance companies but also serves as a major driver for FinTech implementation. This synergy originates from the capacity of digital technologies to connect conventional banking amenities with marginalised populations. The management’s purposeful strategy in leveraging FinTech for financial inclusion is multifaceted, involving expanding access to product and services, improving their affordability and empowerment amongst target groups.

In the literature, studies have shown that, financial inclusion extends beyond basic access to financial services. It involves offering a variety of financial products customised for marginalised groups, including microloans, insurance and remittance services. These offerings are crafted to suit the specific needs of underserved groups. Moreover, they are made easily accessible through mobile technology, a key factor highlighted by Mia (2020) as it effectively diminishes barriers to entry for individuals with low incomes, thereby playing a crucial role in enhancing global financial inclusion efforts.

Additionally, the strategic incorporation of FinTech solutions tackles crucial obstacles like the expensive nature of providing financial services in remote regions, the absence of official credit records amongst marginalised communities and the overall scepticism or lack of familiarity with conventional firms. For example, inventive methods of assessing creditworthiness, which leverage alternative data like mobile phone usage habits and transaction records, empower microfinance companies to evaluate potential borrowers even without conventional credit data, thereby expanding their clientele (Dorfleitner et al., 2019).

The results emphasise how FinTech has the power to revolutionise access to financial services for marginalised groups. Nonetheless, they also stress the importance of integrating technology thoughtfully, with a focus on inclusivity, accessibility and sustainability principles. Therefore, achieving financial inclusion through FinTech adoption is not just about operations or technology; it is a deep-seated organisational dedication to fostering social change.

The effect of the analyses carried out at the first stage of the study is the division of key words identified in 461 collected publications into clusters containing terms commonly used by the authors to describe the analysed phenomenon. Thanks to the use of VOS viewer software in version 1.6.14, five clusters containing the following terms were distinguished:

• Cluster 1: credit programmes, empowerment, gender, households, impact(s), intervention, intimate-partner violence, microcredit, microfinance evidence, poor, poverty, risk, savings.

• Cluster 2: crowdfunding, education, entrepreneurship, governance, hybrid organisations, innovation, investment, knowledge, market, microfinance, model, policy, social enterprise, social entrepreneurship, sustainable development, technology.

• Cluster 3: banks, crisis, determinants, efficiency, financial inclusion, FinTech, institutions, Islamic microfinance, microfinance, microfinance companies, outreach, performance, sustainability.

• Cluster 4: banking, business, economic development, emerging economies, finance, growth, markets, models, panel-data, strategy.

• Cluster 5: credit, joint liability, networks, programmes, social capitals.

The results of this stage of the study were also visualised in a map showing the combinations of the terms digital innovation with other keywords identified in the surveyed publications (Figure 3).

This analysis shows each cluster’s temporal distribution of keywords. In the plot created by VOSwiewer, keywords are coloured according to a score, which is assigned based on the average yearly occurrence of keywords. The change in colours represents the evolution of the topic examined (see: Elia et al., 2023; Jalal et al., 2021).

Figure 4 shows the clusters identified on the basis of papers published between 2010 and 2016 in the field analysed. Compared to the next figure, which is based on papers published between 2017 and 2023, it is clear that the number of clusters is smaller (4 cluster based on the publications from 2010-2016 and 6 based on publications from 2017-2023). There are also significantly fewer keywords forming individual clusters. At the same time, it is worth noting that the first of these linkage maps was based on 146 papers published between 2010 and 2016, whereas the number of papers published between 2017 and 2023 is much higher, at 315 (See Figure 5).

Considering the connections between the keywords, several recurring features characteristic of the studies described in the analysed publications can be indicated (Table 3).

In the work, special attention was focussed on publications in which the analysed issues are described in a model approach. For this purpose, from the collection of 461 publications, papers describing the studied phenomenon in a model approach were extracted. In total, 200 works of this type have been identified. On this basis, a dichotomous dependent variable (M) was created, defining the model approach to the researched issue (where M1 – means considering various types of models, both quantitative and qualitative, when describing the studied phenomenon and M2 – a different type of approach). On the other hand, as independent variables (categorisation variables), the features characterising works in this field, identified during the study, were adopted, as described in Table 2, where:

• (1)

  A – area (A1 – research conducted at the national level, A2 – at the regional lev).

• (2)

  L – level of analysis (L1 – research conducted at the level of at least one sector (industry), L2 – research conducted at the level of enterprises).

• (3)

  IN – works presenting the results in the field of innovation (IN1 – no references to innovations, IN2 – innovations in total, IN3 – digital innovations).

• (4)

  SD – works referring to sustainable development (SD1 – not considering any SD area; SD2 – considering at least two SD areas, SD3 – considering all three areas SD; economic, social and environmental).

For the variables created in this way, a Burt matrix with dimensions of 12 × 12 was determined (the number of categories adopted for the study of variables). The dimension of the real space of co-occurrence of variables, determined based on Formula (1), was 7. In the next step, it was checked to what extent the eigenvalues of the space with a lower dimension explain the total inertia (λ = 2,000). Using Greenacre’s criterion, it turned out that these are inertias for K taking at most 3, because principal inertias greater than $1Q=15=0.200$⁠. For these dimensions, the share of inertia of the selected dimension was determined (λ_k) in total inertia (λ), which is marked as τ_k. Therefore, it was decided that the presentation space of the coexistence of variable categories should be three-dimensional. The degree of explaining the inertia in this space is 43.10%, and after modifying the eigenvalues according to Greenacre’s proposal, it is 69.82% (Table 4).

To determine the number of clusters that best describe the relations between the categories of variables in three-dimensional space, the Ward’s method with the Euclidean distance was used. The optimal number of clusters was determined based on the first clear increase in the agglomeration distance for subsequent binding steps. As a result, 4 homogeneous groups were obtained, which can be characterised as follows:

• (1)

  Group I: (M2, L1, IN3) refers to publications in which the analysed issues are not presented in a model approach, they concern research conducted at the sectoral level and contain references to digital innovation.

• (2)

  Group II: (M1, L2, IN2) refers to publications in which the analysed issues are presented in a model approach, they usually concern research conducted at the enterprise level and describe issues related to innovations, but without specifying their type (in terms of general).

• (3)

  Group III: (A1, SD2, SD3) are publications in which the analysed area is described in relation to individual countries or groups of countries.

• (4)

  Group IV: (A2, IN1, SD1) refers to publications describing the researched area in regional terms, which do not address issues related to innovation and sustainable development.

The division into four groups illustrates the interdisciplinary approach that is increasingly being adopted in microfinance research. For instance, Group 1 focusses on the impact of microfinance on poverty alleviation and gender empowerment, echoing findings from other studies like Datta and Sahu (2022), who argue that microfinance can play a pivotal role in empowering women and reducing household poverty. This is in line with the notion that access to microcredit and savings programmes can significantly impact poor households' ability to manage risks and invest in income-generating activities (Aziz et al., 2022).

Group 2’s emphasis on social entrepreneurship, innovation and sustainable development correlates with the growing recognition of the role microfinance companies play in promoting sustainable economic growth and development. This group reflects a trend towards leveraging microfinance as a tool for achieving broader development goals, including those outlined in the United Nations SDGs (Pandey et al., 2022).

The analysis of publications through a model approach, as indicated by the dichotomous variable (M), and the subsequent identification of four homogeneous clusters based on the Burt matrix and Ward’s method, further adds depth to the understanding of the field. This methodology allows for a nuanced view of how different research perspectives – ranging from those emphasising digital innovations to those focussed on sustainable development – are grouped and how they interact within the microfinance research ecosystem.

Moreover, the study’s attention to the role of digital innovations (IN3) in Cluster I underscores the increasing importance of FinTech solutions in enhancing financial inclusion and efficiency within the microfinance sector. This finding resonates with the work of other researchers who have highlighted the potential of digital finance to revolutionise microfinance by lowering transaction costs and expanding access to financial services for the unbanked (Tay et al., 2022).

The exploration of the drivers behind FinTech as a digital innovation in microfinance companies, along with an examination of the current and emerging research directions, yields insightful conclusions that not only address the study’s initial research questions but also pave the way for future enquiries in this dynamic field. The investigation reveals that the primary motivations for adopting FinTech in microfinance organisations are centred around enhancing operational efficiency, improving customer experience and fulfilling the strategic objective of financial inclusion. Operational efficiency is achieved through the strategic deployment of technologies such as blockchain and AI, which streamline processes, improve management performance and scale operations. The emphasis on customer experience, driven by rising consumer expectations for personalised and accessible financial services, necessitates the use of data analytics and AI to tailor services to individual needs. Lastly, financial inclusion stands out as a significant driver, with digital technologies enabling microfinance companies to extend their services to marginalised populations, thereby supporting their social mission of making financial services accessible to underserved communities.

The analysis of research trends and emerging areas highlights a diverse and interdisciplinary approach to studying the application of FinTech in microfinance. The study categorises existing literature into clusters focussing on different aspects, such as the impact of microfinance on poverty alleviation, the role of social entrepreneurship and the importance of digital innovations for financial inclusion. This clustering indicates a broadening scope of research, moving beyond traditional financial performance metrics to include social and technological dimensions. The model-based approach to analysing publications reveals a growing interest in digital innovations, sustainable development and the strategic implications of FinTech for microfinance companies.

The research’s novelty lies in its focussed exploration of digital innovation within microfinance, an area that remains relatively underexplored. No similar paper was found during the literature review. The findings identify key themes, gaps and future research directions, shedding light on the strategic implications of digital technology in microfinance. This comprehensive analysis significantly advances the understanding of how FinTech enhances microfinance management operations and objectives, contributing to both academic discourse and practical applications.

While the study provides comprehensive insights, it acknowledges certain limitations, primarily related to the scope of literature reviewed and the potential for broader generalisability of findings. The reliance on published literature might have constrained the exploration of unpublished or emerging research areas not yet widely discussed. Additionally, the study’s findings are predominantly based on secondary data, which could benefit from complementation with primary data sources to deepen the understanding of FinTech’s impact on microfinance.

Future research directions should aim to bridge these gaps by incorporating more extensive empirical studies, exploring under-researched areas such as the impact of FinTech on microfinance companies' resilience to new business models and management approaches, and assessing the long-term effects of digital transformation on the microfinance sector’s dual objectives of financial sustainability and social impact. Further investigation into the regulatory, ethical and technological challenges facing FinTech adoption in microfinance can also enrich the discourse, ensuring that advancements in this field are leveraged for maximum academic and societal benefits.

Funding: Co-financed by the Minister of Science under the “Regional Excellence Initiative” programme.