Small And Medium-sized Enterprises Financing Research Articles

FinTech developments and their heterogeneous effect on digital finance for SMEs and entrepreneurship: evidence from 47 African countries

Purpose Lack of access to finance is a major constraint to the growth of small and medium-sized enterprises (SMEs) and entrepreneurship in developing countries. The recent proliferation of mobile phone services, access to the internet and emerging technologies has led to a surge in the use of FinTech in Africa and is transforming the financial sector. This paper aims to examine whether FinTech developments heterogeneously contribute to the growth of digital finance for SMEs and entrepreneurship in 47 African countries from 2013 to 2020. Design/methodology/approach The paper uses a novel method of moments quantile regression, which deals with heterogeneity and endogeneity in diverse conditions for asymmetric and nonlinear models. Findings The empirical results reveal that the rise of FinTech companies offering services in Africa heterogeneously increases digital finance for SMEs and entrepreneurship in their different stages of growth. FinTech developments have a strong and positive impact in countries with higher levels of digital finance than those with lower levels. FinTech developments and digital finance positively and significantly influence entrepreneurship in Africa, particularly in the nascent and transitional development stages of entrepreneurship. Institutional quality has a considerable positive moderating effect when used as a control rather than an interaction variable. Practical implications The results suggest the need to promote FinTech developments in Africa: to provide a wide range of alternative digital finance schemes to SMEs and to promote entrepreneurship, especially in countries where entrepreneurship is in the nascent and transitional development stages. The results also underscore the need to promote FinTech development through supportive regulations and institutional quality to reduce risks related to FinTech and digital financing schemes. Originality/value To the best of the authors’ knowledge, this paper is one of the first attempts to account for the often overlooked heterogeneity effects and show that the influence of FinTech developments is not homogenous across the varying development stages of digital finance and entrepreneurship.

Understanding dollar dynamics and SME performance in GCC economies

PurposeThis study investigates the impact of US dollar volatility and oil rents on the performance of small and medium-sized enterprises (SMEs) in the Gulf Cooperation Council (GCC) region, with an emphasis on understanding how these factors influence SME financing constraints in economies with fixed currency regimes.Design/methodology/approachEmploying a random effects panel regression analysis, this research considers US dollar volatility and oil rents as independent variables, with SME performance, measured through the financing gap, as the dependent variable. Controls such as trade balance, inflation deltas and gross domestic product (GDP) growth are included to isolate their effects on SME financing constraints.FindingsThe study reveals a significant positive relationship between dollar volatility and the financing gap, suggesting that increased volatility can exacerbate SME financing constraints. Conversely, oil rents did not show a significant direct influence on SME performance. The trade balance and inflation deltas were found to have significant effects, highlighting the multifaceted nature of economic variables affecting SMEs.Research limitations/implicationsThe study acknowledges potential biases due to omitted variables and the limitations inherent in the use of secondary data.Practical implicationsFindings offer pertinent guidance for SMEs and policymakers in the GCC region seeking to develop strategies that mitigate the impact of currency volatility and support SME financing.Originality/valueThe research provides new insights into the dynamics of SME performance within fixed currency regimes, which significantly contributes to the limited literature in this area. The paper further underscores the complex connections between global economic factors and SME financial health.

Entrepreneurial financing: how global and regional export intentions affect financial and non-financial choices for small and midsized enterprises in low-income countries

PurposeThe study explores how the intention to export affects financing and non-financing variables for small and medium-sized enterprises (SMEs) in a low-income country (LIC). The objectives of this study are (1) to discern between regional and global exporting and (2) to evaluate its policymaking implications.Design/methodology/approachPrimary survey data were collected from 330 Rwandan SMEs and were analysed using ordered logistic models as an application of the expectation-maximisation iterating algorithm, which was tested for robustness using a sampling model variation.FindingsThe results show that alternative sources of finance are the predominant choice to finance the intention to export within and outside Africa. As the scope of export intentions broadened from regional to global, there was a shift in preferences from less formal to more formal lending technologies, moving from methods like factoring to lines of credit. Moreover, reliance on bank officers became more significant, with increasing marginal effects. Finally, the study determined that government financing schemes were not relevant for SMEs pursuing either regional or global exporting.Practical implicationsWhilst alternative sources of finance predominate the export intentions of Rwandan SMEs, establishing a robust banking relationship becomes crucial for global exporting. Despite this implication, the intention to export should prompt more transparent communication regarding government financial support programmes. There is an opportunity for increased usage of relationship lending to customise support for SMEs involved in exporting, benefiting both the private and public sectors.Originality/valueThis study accentuates how export distance alters SME financing priorities. The results also contribute to understanding how the value of relationship lending changes when less familiar markets (i.e. global exporting) are the objective. Moreover, the study offers a new perspective on how institutional voids affect entrepreneurial financing decisions in LICs.

Deciphering the shadows: an empirical exploration of corruption’s impact on SMEs credit costs in OECD countries

Purpose This study aims to investigate the intricate relationship between corruption and the credit costs faced by small and medium-sized enterprises (SMEs) in OECD countries, a critical yet underexplored area in financial crime research. The primary aim is to dissect and understand how corruption impacts SMEs’ access to credit, highlighting a significant yet overlooked aspect of financial crime. This research seeks to fill a gap in the literature by providing empirical insights into the economic consequences of corruption, specifically on SMEs financing. Design/methodology/approach This study used secondary panel data from the World Bank and OECD databases. The data covered the period 2007–2020 for 25 OECD countries. This study used interest rate for SMEs loans as a dependent variable and GDP per capita, inflation and corruption index as independent variables. This study used the panel autoregressive distributed lag (ARDL) model to examine the relationship between variables. Findings The empirical findings derived from Panel ARDL postulate an intriguing dichotomy in the effects of GDP per capita, inflation rate and corruption on interest rates in both the short and long run. It was discerned that an increase in GDP per capita and inflation rate correlates with a decrement in interest rates in the long run, suggesting a potential compromise by central banks between controlling inflation and fostering economic growth. Originality/value This paper makes a novel contribution to the field of financial crime by illuminating the often-overlooked economic dimensions of corruption in the context of SMEs financing. It provides a unique perspective on the ripple effects of corrupt practices in credit markets, enriching the academic discourse and informing practical approaches to combating financial crime.

Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing

The complexities arising from disparate data sources, conflicting contracts, residency requirements, and the demand for multiple AI models in trade finance supply chains have hindered small and medium-sized enterprises (SMEs) with limited resources from harnessing the benefits of artificial intelligence (AI) capabilities, which could otherwise enhance their business efficiency and predictability. This paper introduces a decentralized AI orchestration framework that prioritizes transparency and explainability, offering valuable insights to funders, such as banks, and aiding them in overcoming the challenges associated with assessing SMEs’ financial credibility. By utilizing an orchestration technique involving symbolic reasoners, language models, and data-driven predictive tools, the framework empowers funders to make more informed decisions regarding cash flow prediction, finance rate optimization, and ecosystem risk assessment, ultimately facilitating improved access to pre-shipment trade finance for SMEs and enhancing overall supply chain operations.

Impact of Digital Inclusive Finance on Financing Constraints of Small and Medium-Sized Enterprises Review

This review examines the influence of digital inclusive finance (DIF) on financing constraints of small and medium-sized enterprises (SMEs). As DIF is introduced to more and more enterprises, it has brought many opportunities to enterprises along with global economic growth. The introduction and development of digital financial inclusion has eased the financing constraints of SMEs, reduced information asymmetry and costs, and improved efficiency and capital availability. Research shows that digital financial inclusion has an alleviating effect on financing constraints. This paper provides a review of current research, including an overview of digital financial inclusion, SME financing constraints, and how digital financial inclusion affects SME financing constraints. In addition, this paper states the possible solutions for how digital inclusion can be more widely promoted. Additionally, this paper finds the shortcomings of the existing research to provide a different point of view for future researchers to look at the influence of digital inclusive finance on the financing constraints of SMEs.

Government procurement contracts, external audit certification, and financing of small-and medium-sized enterprises

Government procurement contracts, external audit certification, and financing of small-and medium-sized enterprises

Forecasting Credit Risk of SMEs in Supply Chain Finance Using Bayesian Optimization and XGBoost

Supply chain finance plays a crucial role as a financing channel for small- and medium-sized enterprises (SMEs). However, issues such as financial problems and credit defaults have led to disruptions in this channel. To address credit risk control in SME financing within the field of supply chain finance, this paper focuses on a sample of 506 equipment manufacturing companies listed on the SME board of the Shenzhen Stock Exchange from 2016 to 2020. Taking into consideration, the overall risks faced by these enterprises, the study establishes seven first-level indicators and identifies 84 candidate second-level indicators. Partial correlation and variance analysis are then used for the first round of indicator screening, followed by the use of a BP neural network for the second round of selection. As a result, a system of 26 indicators for supply chain financial risk is constructed. The XGBoost model is employed to evaluate the constructed risk index system, while SVM and random forest models are used as comparison models. Bayesian optimization is utilized for parameter tuning of the three models. Empirical results demonstrate that the BO-XGBoost model reduces prediction errors in comparison to the control models. Furthermore, statistical tests reveal that the predicted values of the BO-XGBoost model significantly differ from those of the other control models. Compared to other individual models, the BO-XGBoost model exhibits increased accuracy in credit risk prediction and a significant discriminative effect. These findings highlight the effectiveness of constructing an efficient risk indicator system and utilizing Bayesian optimization for parameter tuning in XGBoost to better differentiate between risky and normal enterprises, thereby minimizing default losses. The research results underscore the advantages of employing Bayesian optimization in XGBoost, which can be applied in credit default prediction for SMEs and serves as a valuable tool in financial risk management and control.

Proactive legal design—making sustainability visible and monitorable in SME loan agreements

According to the European Commission's Sustainable Finance Strategy, the financial system has a key role to play in promoting sustainable development toward a greener and more sustainable economy. Small and Medium-sized Enterprises (SMEs) represent over 99% of all European businesses and are responsible for around 60% of all business greenhouse gas emissions. Small and Medium-sized Enterprises are therefore crucial to the success of the European Union's sustainability transition. The share of sustainable finance for SMEs will grow both as a result of increasing sustainability legislation and the expectations of customers and stakeholders. However, integrating sustainability can be challenging for SMEs due to limited resources and expertise. The article highlights the importance of clear, transparent, and implementable contract documents as tools to enhance sustainability in financing. Proactive contracting and legal design approaches are discussed as means to transform contracts into management and communication tools, to promote sustainable business practices.

Explore the Impact of China Fintech Loans on the Financing of SMEs

As an important part of the economy, small and medium-sized enterprises (SMEs) play an important role in the recovery of the economy after the epidemic, but the financing difficulties of SMEs have been exposed but not solved. Fintech is the core force to practice inclusive finance and an important breakthrough to improve the financing constraints of SMEs. Fintech loans rely on big data to conduct credit evaluation and risk management for SMEs and play an important role in expanding corporate financing channels, accelerating loan efficiency, and reducing financial discrimination. First, this paper summarizes the financing status of SMEs in China and then subdivides Fintech loans. From the perspectives of bank Fintech loan use and Fintech loan company development, this paper presents the impact of Fintech loans on SME loans and the relationship between different Fintech loans and summarizes the shortcomings of Fintech loans in resolving the financing problems of SMEs. Finally, based on the current research status and objective reality, it provides suggestions for future research directions.

The Role of Artificial Intelligence, Financial and Non-Financial Data in Credit Risk Prediction: Literature Review


 
 
 
 Small and medium-sized enterprises (SMEs) are of major importance in world economies and job creation. Financing is one of the key issues for SME development since SMEs are often considered riskier than large companies. It is argued in the literature that artificial intelligence (AI) and non-financial data could increase the financial inclusion of disadvantaged groups, such as SMEs. This article presents an overview of selected studies on credit risk prediction from the 1960s to 2022, covering topics of research work applying classical statistical methods, studies using AI methods on traditional financial data and studies applying AI methods on non-financial data. Literature overview results showed that the inclusion of non-financial data in credit risk prediction models could increase credit risk prediction performance, while AI methods can enable the inclusion of non-financial data. Since non-financial data potentially could be used as alternative data in credit prediction models, AI and non-financial data could help to increase access to finance for SMEs
 
 
 

FinTech and SMEs financing: A systematic literature review and bibliometric analysis

Small and medium-sized enterprises (SMEs) face obstacles in raising capital and accessing financial services due to information asymmetry, high transaction costs and lack of collateral. FinTech developments have made gathering and sharing information easier, changed how funds are mobilized and allocated, and increased capital-raising activities. This paper conducts a systematic literature review on FinTech and SME financing for the period 2008–2022. So far there are unstructured and separate publications on this topic. Therefore, there is a need to consolidate the empirical research and their findings on the effectiveness of FinTech in meeting SMEs' financing needs. The bibliometric findings show that few studies on FinTech and SME financing are empirical in nature. These empirical studies surged a decade later after FinTech 3.0 started in 2008, with the majority of them using quantitative methods based on data from surveys and FinTech platforms. Furthermore, emerging alternative digital financing to SMEs have attracted more empirical studies than those on FinTech and bank lending to SMEs. In terms of publications, China is dominating, followed by the United States. The content analysis shows that FinTech has increased the ability of financial and non-financial institutions to collect and process accurate information about SMEs, thus reducing information asymmetry and transaction costs. FinTech has also increased the speed and quality of the lending cycle, from establishing an SME pipeline, collecting and processing information, to loan screening, monitoring and repayment. Finally, the paper presents research gaps and areas for future studies, challenges and policy recommendations on this novel subject.

Equity capital financing of Swedish SMEs, innovation, and decentralized management

Purpose The purpose of this paper is to investigate the potential link between Sweden’s high reliance on equity capital financing among small and medium-sized enterprises (SMEs) and its recognition as the most innovative economy in Europe according to the European Innovation Scoreboard (EIS). This paper examines the idea that the high levels of trust within Swedish society can explain why private equity financing is more prevalent among Swedish SMEs. Design/methodology/approach To test these ideas, the authors use data from the Survey on Access to Finance for Enterprises to measure the private equity reliance of firms. The authors also use the EIS to measure the innovation capacity of nations and various aspects of SMEs’ innovation activities. Finally, societal levels of trust are measured through the World Value Survey. Findings First, the authors find that European countries with a higher proportion of SMEs relying on equity financing tend to be ranked as more innovative by the EIS. Second, the authors find that the correlation between a nation’s share of SMEs relying on equity financing and their level of innovation activities is marginally stronger for product innovations than for business process innovations. Third, the authors find that countries with higher levels of trust tend to have higher equity capital reliance among SMEs. Originality/value This study builds upon previous research on equity capital and SMEs’ innovation activity while introducing new insights into the relationship between societal trust and equity financing.

Challenges Faced by Small and Medium-sized Enterprises in China When Seeking Low-cost Financing

SME (small and medium-sized Enterprises) financing has been difficult in recent years. But, SMEs are vital to the economy and must be helped to thrive. China calls SMEs "Five, Six, Seven, Eight, and Nine" since they account for more than 50% of national tax revenue, 60% of GDP, 70% of technological innovation, 80% of jobs, and 90% of enterprises. SMEs drive long-term, sustainable economic growth that benefits everyone. But, reducing SMEs' breathing space will hurt China's economy. Thus, SMEs' problems are the economy's problems, and it is worth investigating and trying to solve them. Most studies examine SMEs' finance dilemma's causes, while others focus on a specific solution. This paper examines these finance issues and weighs the pros and cons of various solutions. This paper uses a literature review to explore China's economy, the problem, risk perception, and its effects. The study also discusses possible solutions and future development.

Dynamic Evolutionary Game Approach for Blockchain-Driven Incentive and Restraint Mechanism in Supply Chain Financing

The sustainability of financing is an important measure in the development of supply chains. However, the difficulty and high cost of financing have always been critical factors hindering the sustainable development of small and medium-sized enterprises (SMEs). Blockchain technology (BT) is an effective tool to relieve the current problem. Based on it, this study aims to establish Blockchain-driven incentives and restraint mechanisms for SME financing using a dynamic game model in which financial institutions (FIs) and new agricultural business entities (NABEs) are regarded as game subjects. By analyzing the impact of key parameters on the equilibrium state of the game for all stakeholders, several findings are drawn as follows. (1) The usage of BT affects FI loan strategies by influencing their cost in supply chain financing. (2) The usage of BT affects NABE’s strategy choice by influencing their loan interest rate. (3) The usage of BT affects NABE’s strategy choice by influencing their default losses. (4) The usage of BT affects NABE’s and FI’s strategy choices by influencing their additional benefits. This study provides decision-making support for optimal strategy decisions under different conditions and serves as a theoretical reference for the government in formulating financing incentive and restraint mechanisms.

How Covid-19 impacts the financing in SMEs: Evidence from private firms

The world economy, and SMEs in particular, have been hit hard by the COVID-19 epidemic. SME finance issues are becoming a significant focus of policymakers and academics. This research uses private companies as a sample to analyze how COVID-19 affected SME finance. We examine critical factors such as business size, leverage, profitability, liquidity, and the influence of COVID-19. Our research shows that the pandemic has had a significant, detrimental impact on funding for small and medium-sized businesses. Small and medium-sized enterprises (SMEs) have expanded their borrowing amid falling profits and cash flow. More specifically, smaller SMEs have been hit harder than their bigger counterparts. Implications for policymakers and the owners of SMEs are substantial. Governments should help small and medium-sized enterprises by providing incentives like tax credits and loan guarantees. Owners of small and medium-sized enterprises (SMEs) should prioritize sound financial management and stability. This research sheds light on SMEs’ funding difficulties in the wake of COVID-19 and highlights the need to aid such businesses as rebuild.

Does Islamic banking reduce the risks of COVID-19 for SMEs? Novel evidence for SME financing in the pandemic period for an emerging market

This paper aims to examine the effect of COVID-19 on SME bank lending in the Islamic banking sector to small and medium-sized enterprises (SMEs) in an emerging market: Turkey. Understanding whether SME bank lending in the Islamic banking sector is procyclical or not is very important to reduce the impact of COVID-19 on SMEs. Interrupted time series analysis (ITSA), the Markov switching regression model, and vector autoregressive (VAR) methodologies are employed using novel weekly data for the pandemic period. The present study finds that the Islamic banking sector for SME financing has behaved countercyclically during COVID-19 in the Turkish economy. The paper thus sheds new light on the relationship between Islamic bank lending for SME financing and the COVID-19 shock in an important emerging market. The findings can provide insights into how Islamic banks mitigate the effect of COVID-19 on SMEs in an emerging market context. The present paper clearly shows differences between Islamic bank lending toward SMEs and deposit bank lending toward SMEs in the pandemic era. The willingness of Islamic banks to supply loans to SMEs during the pandemic plays a vital role in reducing SME firm failure in the Turkish economy.

Comparative Analysis of Internet Financing Modes Based on Smes' Perspective

In China, it is difficult for small and medium-sized enterprises (SMEs) to gain access to external financial support under the traditional financial mode. However, the internet financing can alleviate this problem effectively, which broadens access to finance for SMEs and promotes their development. By comparing three mainstream Internet financing modes (i.e., equity crowdfunding, P2P lending and big data finance), this paper analyses the unique characteristics of each model and proposes more targeted and specific financing suggestions accordingly for SMEs at different development stages. According to the analysis, equity crowdfunding, P2P lending and online micro-credit loan can cater to the funding demands of SMEs in the introduction, growth, and maturity stages respectively. Meanwhile, enterprises in decline should seek financing strategies that suit their current situation. Based on the existing general risks of Internet financing in China, development suggestions from three levels (i.e., the state, the platform, and the SMEs themselves) are proposed. These results shed light on guiding further exploration of financing modes for Chinese SMEs.

Alleviation effect of supply chain finance on financing constraints of high‐tech small‐ and medium‐sized enterprises

AbstractThis paper studies financing constraints of small‐ and medium‐sized enterprises (SMEs) in Guangdong–Hong Kong–Macao Greater Bay Area from the perspective of supply chain finance and examines how the supply chain finance affects the financing of SMEs. First, based on the cash‐cash flow sensitivity model, a multiple regression model is constructed. The results show that the supply chain finance could alleviate the financing constraints of SMEs. Second, a multi‐objective programming model is established, and an optimal solution is found by the genetic algorithm. It is concluded that the enterprise should allocate the appropriate amount of funds to obtain the optimal financing effect; to obtain the maximum financing benefit, the optimal strategy should be 65.2% of the supply chain finance capital. Finally, some suggestions are proposed forward to promote the development of SMEs in the bay area.

Access to Finance: The Determinants and Limitations to the Supply Side of Finance for Liberia’s Rural Market

This critical piece of research paper reviews the literature on the key determinants of finance for Liberia’s rural market. It also takes into account the limitations of the supply of finance for the rural market of Liberia, with the unabated need for the diversification of the Liberian economy in the face of intermittent shocks in the global economy. The study unearthed that investment in agricultural small and medium-sized enterprises (SMEs) will prove adequate in triggering sustainable economic growth and development through poverty alleviation, job creation, and food security which are the drivers of the supply of finance for rural dwellers in Liberia. Notwithstanding, the study found that the supply of finance for Liberian agricultural SMEs is constrained by the lack of creditworthiness information, weak judicial enforcement of contracts and corporate transparency, land ownership, high non-performing loans, and financial literacy. The keywords used in this article include gross domestic product, small and medium-sized enterprises, non-performing loans, inflation, credit rating, bankruptcy, value chain, urbanization, food security, human capital, and risk aversion. Keywords: Bankruptcy, Credit rating, Human capital, Inflation, Small and medium-sized enterprises, Value chain.