Business Loans Research Articles

Sectoral similarity of banks’ business loans and its negative externality in China

Sectoral similarity of banks’ business loans and its negative externality in China

Access to Capital: Analysis of CDFI Lending and Black Women Entrepreneurs

ABSTRACT This study investigates Black Women Entrepreneurs in Georgia utilizing Community Development Financial Institutions (CDFIs) to access capital, analyzing 2,173 loan applications from 2021–2023. Employing Afrocentric Perspective and Ecological Systems Theory, it identifies factors impacting funded loans, including business age, location, referral source, and loan amount requested. Binary logistic regression reveals significant correlations, emphasizing ecosystem support for this demographic. Findings underscore CDFIs’ role in addressing systemic inequities and advancing economic opportunities for underserved populations.

Integration of Grab Methods with Artificial Neural Networks for Enhanced Decision-Making Systems

This study explores the architecture, development, and practical applications of artificial neural networks (ANNs), with advances in Gray Relational Analysis (GRA) techniques. ANNs are computational models designed to model biological neural systems, consisting of layers of interconnected neurons—i.e., input, hidden, and output layers—connected by synaptic weights. Operating through a connectionist approach, these networks effectively mimic the four basic functions of biological neurons: receiving input, integrating information, processing data, and generating output. Traditional ANNs, although powerful, face limitations in embedded systems due to their reliance on high-precision digital information transfer and the resulting resource demands. This has prompted the development of more efficient alternatives, such as spiking neural networks (SNNs), which use event-driven spiking signals to reduce power consumption and memory usage. The field has advanced further by incorporating theoretical models for quantum neural computing and the use of genetic algorithms employing various crossovers and mutation techniques. The versatility of ANNs is evident in a variety of applications. In healthcare, they aid in pattern recognition associated with conditions such as breast cancer and diabetes. For water resource management, ANN models predict relationships between rainfall and water levels. In financial sectors, they analyze complex economic conditions and assess credit risk for small business loans. Industrial applications include modelling complex systems in manufacturing plants, although widespread adoption in this field is limited. Complementing neural network advances, GRA methods have emerged to address multi-criteria decision-making challenges. Notable advances include the GRAS techniques have been developed to correct matrices with negative values, while fuzzy GRA methods now include interval-valued triangular fuzzy numbers and probabilistically uncertain linguistic word sets. Recent advances include innovations such as score values and normalized Hamming distances within single-valued neutrosophic fuzzy stein summary, these computational approaches offer powerful ways to solve complex, multidimensional problems, with recent studies highlighting improved performance and promising prospects for future application.

Integration of Grab Methods with Artificial Neural Networks for Enhanced Decision-Making Systems

This study explores the architecture, development, and practical applications of artificial neural networks (ANNs), with advances in Gray Relational Analysis (GRA) techniques. ANNs are computational models designed to model biological neural systems, consisting of layers of interconnected neurons—i.e., input, hidden, and output layers—connected by synaptic weights. Operating through a connectionist approach, these networks effectively mimic the four basic functions of biological neurons: receiving input, integrating information, processing data, and generating output. Traditional ANNs, although powerful, face limitations in embedded systems due to their reliance on high-precision digital information transfer and the resulting resource demands. This has prompted the development of more efficient alternatives, such as spiking neural networks (SNNs), which use event-driven spiking signals to reduce power consumption and memory usage. The field has advanced further by incorporating theoretical models for quantum neural computing and the use of genetic algorithms employing various crossovers and mutation techniques. The versatility of ANNs is evident in a variety of applications. In healthcare, they aid in pattern recognition associated with conditions such as breast cancer and diabetes. For water resource management, ANN models predict relationships between rainfall and water levels. In financial sectors, they analyze complex economic conditions and assess credit risk for small business loans. Industrial applications include modelling complex systems in manufacturing plants, although widespread adoption in this field is limited. Complementing neural network advances, GRA methods have emerged to address multi-criteria decision-making challenges. Notable advances include the GRAS techniques have been developed to correct matrices with negative values, while fuzzy GRA methods now include interval-valued triangular fuzzy numbers and probabilistically uncertain linguistic word sets. Recent advances include innovations such as score values and normalized Hamming distances within single-valued neutrosophic fuzzy stein summary, these computational approaches offer powerful ways to solve complex, multidimensional problems, with recent studies highlighting improved performance and promising prospects for future application.

How does bank loans affect carbon emissions? A comparison of household and business loans

Abstract Household and business loans are essential financial instruments that bolster economic growth by improving access to capital and fostering various economic activities. However, their environmental implications remain underexplored, particularly in economies with high carbon footprints like the United States. Household loans primarily facilitate consumer spending and personal investments, helping households meet financial needs and supporting overall demand in the economy. In contrast, business loans drive economic expansion by providing firms with the necessary resources to grow, innovate, and enhance productivity. However, in the United States, where environmental pollution is a significant concern, these loans can also amplify environmental challenges. Business loans, in particular, are often channeled into industries with substantial carbon footprints, potentially accelerating emissions through increased production, transportation, and energy consumption. This study employs the machine learning-based Kernel-based Regularized Least Squares technique, which allows for flexible, non-parametric estimation, capturing complex relationships between variables without imposing restrictive functional forms. The analysis covers the period from 1945 to 2020. The findings show that home loans have no discernible impact on emissions, while corporate loans and GDP growth do. While home lending may not be as closely associated with carbon-intensive spending, this study implies that company loans serve as a conduit for emission-intensive activities. Considering these findings, it is recommended that policies promote sustainable business loan practices, such as incentivizing investments in low-carbon technologies, to reduce the environmental footprint associated with business-driven growth. Additionally, financial regulations could encourage green credit mechanisms, ensuring that business lending aligns with long-term sustainability goals.

US Bank Lending to Small Businesses: An Analysis of COVID-19 and the Paycheck Protection Program

This paper examines the characteristics of banks and their lending behavior in relation to Paycheck Protection Program (PPP) loans and commercial and industrial (C&I) loans to small businesses during the COVID-19 pandemic. Our findings show that lenders facing greater risk tended to lend more PPP loans, consistent with the risk-aversion theory. Specifically, banks with a higher loan–deposit ratio, lower overall profitability, poorer loan quality, and higher exposure to risks in business (C&I) loans are characterized by higher PPP loans. C&I loans to all businesses are negatively related to the loan–deposit ratio and loan loss allowance ratio, but are positively linked with the capital ratio. However, we find important differences in C&I lending to small businesses versus large businesses. Furthermore, there is evidence regarding the success of targeting PPP loans towards more productive sectors of the US economy. Using FDIC-defined banks’ lending specializations, we show that banks focused on international lending had a limited role in PPP lending.

Bank Socialness: It Matters When It Counts

In the last decade, social unrest has significantly increased on a global scale as well as in the USA. The literature has documented the negative economic impact of social unrest on lower GDP and stock valuations. In this paper, I extend the literature by examining the effect of social unrest on credit supply in the US. I document a negative relationship between social unrest and the growth of business loans, especially commercial and industrial loans (even for small businesses). More importantly, the socialness of banks seems to moderate this negative impact, as banks with high social scores increase their commercial loan supply more than their peers with low social scores. Specific borrower characteristics and lending conditions also play similar mitigating roles.

Republic of Azerbaijan

This paper focuses on the Republic of Azerbaijan’s Financial Sector Assessment Program as part of Financial System Stability Assessment. Azerbaijan’s economy has recovered from two downturns prompted by the collapse of global oil prices in 2015 and coronavirus disease 2019 pandemic in 2020. An intensification of regional conflicts poses risks to the economy. Similarly, the high reliance on oil and gas revenues renders Azerbaijan vulnerable to oil and gas price declines. This in turn would impact banks’ asset quality and liquidity. Key structural risks to banks stem from substantial reliance on volatile wholesale corporate deposits; continued high financial dollarization, particularly in business loans and deposits; and high credit concentration. Further measures to strengthen regulation and supervision would reinforce financial sector resilience. As noted in previous FSAPs, addressing long-standing issues would entail fully implementing a consolidated supervision framework; safeguarding the Central Bank of the Republic of Azerbaijan’s (CBA) independence; establishing an interagency body for crisis preparedness and management; and giving the CBA full powers for bank resolution.

FACTORS AFFECTING LOANS TO SMES BY THE BANKING SECTOR: AN EMPIRICAL APPLICATION ON TURKİYE

Despite their contribution to innovation, employment and economic growth, small and medium-sized enterprises (SMEs) face many problems in accessing finance. The most important of these problems is their access to bank loans. In many countries, including our country, SMEs can overcome this problem to some extent thanks to government support and incentive programs. In this study, gross domestic product (GDP), consumer confidence index (CCI) and real sector confidence index (RSCI) were selected as factors that are thought to affect the loans extended to SMEs by the banking sector on a scale basis, and the relationship between them and the relevant factors was examined using the ARDL bounds test in 2013Q2-2023Q2 period. According to the empirical findings obtained because of the relevant study, a long-term relationship was determined between variables related to SME bank loans. In the long term, while GDP and RSCI variables affect micro-scale business loans negatively, CCI variable affects them positively. While SME bank loans of other scales are negatively affected by the RSCI variable in the long run, they are positively affected by the GDP and CCI variables.

Performance Appraisal of Pradhan Mantri Mudra Yojana (PMMY)

This study focuses on the Pradhan Mantri Mudra scheme's performance review. The program was introduced on April 8, 2015, and its primary objectives are to increase the number of Micro and Small Businesses and the general public's level of life. The bank offers three different loan categories under the PMMY: Shishu, Kishor, and Tarun. The government created MUDRA (Micro Units Development & Refinance Agency Limited) to implement the Scheme. This organization is in charge of micro unit development and refinance and functions as a microfinance sector overall. All banks wishing to refinance small business loans obtained under the PMMY program can do so under the MUDRA scheme. The overview of Mudra Yojana, including its programs and PMMY's overall performance, is the primary subject of this study. The secondary source of data used in this study has been gathered from a variety of publications, papers, and MUDRA websites.

An Analysis of the Role of the Mitra Dhuafa Cooperative (KOMIDA) in Awakening the Economic Potential of Women in the Pase Raya Sub-District, Aceh Jaya District

Mitra Dhuafa Cooperative (KOMIDA) society, especially for economically weak women, as a financial institution that focuses on providing business capital assistance for the small and medium economic business sector has been supportive in sustaining the lives of micro-enterprises, home-based businesses, and low-income women in general. This thesis research aims to find out the role of Koperasi Mitra Dhuafa (KOMIDA) in raising the economic potential of women in Pasie Raya District, Aceh Jaya Regency. This research is a qualitative descriptive research. The data used is primary data obtained from direct interviews with the management of the Mitra Dhuafa Cooperative Branch and members in Pulo Tinggi, Lhok Guci, and Tuwi Perya Villages in Pasie Raya District, Aceh Jaya Regency. Data collection techniques using interview techniques, observation, and documentation. Data analysis techniques in this study are 1) data reduction, 2) data presentation, 3) data analysis, and conclusion drawing. The results showed that: (1) the implementation of savings and loan business unit activities, creating business entrepreneurs for women who allow community potential to develop (2) the existence of Mitra Dhuafa Cooperative, can make it easier for women to generate existing potential through capital loans so that they can improve the economy better.

Predicting microfinance inclusion and survival of microenterprises in rural Uganda: testing the mediating role of ethical financial behavior of poor young women owners

Purpose The main purpose of this study is to test whether ethical financial behavior as a mediator promotes microfinance inclusion and survival of the poor young women microenterprises in rural Uganda. Design/methodology/approach The methods recommended by Kenny et al. (1998); Shrout and Bolger (2002); MacKinnon et al. (2004); and Preacher and Hayes (2004) were used to establish the existence of non-zero monotonic association between microfinance inclusion and survival through testing the mediating effect of ethical financial behavior in SmartPLS. Findings The results from the structural equation modeling revealed a significant full mediating effect of ethical financial behavior in the relationship between microfinance inclusion and survival of the poor young women microenterprises. Microfinance inclusion and ethical financial behavior explain 62 % of the variation in survival of the poor young women microenterprises in rural Uganda. Research limitations/implications Whereas significant results were obtained from this study, the data were collected only from rural-based poor young women microenterprises located in northern Uganda. Extending the sample to cover the whole country may provide a more representative picture. Besides, it would be useful to compare results across developing countries as this may provide information about the generality of our findings. Practical implications The findings from this study can be useful to managers of microfinance institutions in developing countries to adopt practice that can promote financial discipline among rural poor young women microentrepreneurs. Routine financial education and business mentorship can be organized through workshops, trainings and seminars to teach rural poor young women microentrepreneurs how to manage money, especially business loans borrowed from the microfinance institutions to put it into right use. This can help them to meet timely loan repayment to increase access to future microfinance loans. Originality/value This study provides the first evidence on the use of the theory of planned behavior (TPB) and theory of reasoned action (TRA) to explain microfinance inclusion of the poor young women microentrepreneurs in rural Uganda. The study uses a blend of TPB and TRA derived from psychology and sociology to explain repayment intention and ethical behaviors of the poor young women borrowers, which determines the microfinance lending cycle to make microcredit available for them to engage in entrepreneurship to come out of poverty to attain wellbeing.

Analysis of the Loan Program of the Savings and Loan Business Unit at BUMDesa Mutiara Welirang, Ketapanrame Village According to the Perspective of Sharia Economics

Village development through Village-Owned Enterprises (BUMDes) is an important strategy to improve community welfare by empowering local economic potential. BUMDes, is a legal entity owned and managed by the village community. One example is BUMDesa Mutiara Welirang in Ketapanrame Village, Mojokerto, which manages various business units including savings and loans. This savings and loans unit applies the sharia concept with the qardh contract, providing interest-free loans to help people establish businesses or obtain capital, demonstrating BUMDes' commitment to supporting the village economy sustainably and following Islamic economic principles. So, the formulation of the problem in this study, first: How is the implementation of the Savings and Loans Business Unit loan program at BUMDesa Mutiara Welirang, Ketapanrame Village? Second: What are the results of the analysis of the BUMDesa Mutiara Welirang Savings and Loans Business Unit loan program from a Sharia Economic perspective? Third: How is Risk Management in the Savings and Loans Business Unit at BUMDesa Mutiara Welirang, Ketapanrame Village? The research method used is qualitative descriptive with a case study approach. Data collection was conducted through field observations, in-depth interviews with tourism managers, community leaders, and tourists, and analysis of related documents. The results of this study indicate that: first, the BUMDes savings and loan business unit loan program has become an effective financing alternative at the village level, increasing financial inclusion through easy access and simple procedures using the infaq system. Second, the Mutiara Welirang BUMDesa Savings and Loan Business Unit applies Sharia economic principles through the infaq and qardh mechanisms in its loan program. Third, the Mutiara Welirang BUMDesa Savings and Loan Business Unit has implemented comprehensive risk management, covering aspects of operational, liquidity, and credit risk.

Impact of Digital Yuan (e-CNY) Promotion on Traditional Banking: Challenges and Response Strategies

The introduction of China’s digital yuan (e-CNY) marks a significant transformation in the country’s financial sector, impacting traditional banking, financial institutions, and consumer behavior. As a central bank digital currency (CBDC), e-CNY is designed to enhance financial inclusivity, increase monetary control, and reduce reliance on third-party payment providers. However, its widespread adoption presents challenges and opportunities for traditional banks, requiring them to rethink their business models, adapt to digital currency dominance, and develop new financial strategies to maintain competitiveness. This paper explores the regulatory framework, technological challenges, and financial sector implications of e-CNY, focusing on its effects on traditional banking business models, deposit structures, and loan issuance mechanisms. The study also examines consumer behavior, market adoption patterns, and the competitive landscape, highlighting the role of fintech firms and digital payment platforms. The discussion extends to financial inclusion, particularly in rural and underbanked regions, assessing the potential of e-CNY in bridging economic disparities. The research further investigates response strategies for commercial banks, including hybrid financial models, fintech collaborations, and AI-driven banking solutions. It also provides policy recommendations to ensure stability in the banking sector amidst digital transformation, including monetary policy adjustments, cross-border e-CNY integration, and cybersecurity measures. Findings suggest that while e-CNY presents short-term disruptions to commercial banks, it also offers long-term opportunities for financial innovation and international trade expansion. The paper concludes that traditional banks must embrace technological advancements, regulatory collaboration, and service innovation to maintain relevance in China’s evolving digital economy.

An Investigation on Constituency Development Funds (CDF) and Citizens Economic Empowerment Commission (CEEC) Loan Compliance by Medium Small and Micro Enterprises (MSMEs): A Case Study of Chinsali District (Zambia)

This study investigated Constituency Development Funds (CDF) and Citizens Economic Empowerment Commission (CEEC) Loan Compliance by Medium Small and Micro Enterprises (MSMEs) In Chinsali. The study was done to further comprehend the factors that limit CDF/CEEC loan compliance by MSMEs. The study intended to attain the following objectives: examine the level of compliance of CDF/CEEC loan requirement, evaluate different factors that influence compliance with loan Conditions by MSMEs, Assess the economic impact of CDF and CEEC loans on the growth and sustainability of MSMEs. The study applied Quantitative research methods to drive the findings where a total of 201 MSMEs in Chinsali participated indicative of 99% participation rate. Questionnaires were administered randomly to participants, where data analysis was done through SPSS V26 presented by means of descriptive and inferential statistic. Th study revealed that most MSEMs have business income that is > ZMK 5000, and obtain both long- and short-term loans ranging from ZMK 5000 to < 40000. The study reveals a positive correlation between loan Range and Compliance (p=0.00, sig at 0.01), Business Income and Compliance (p= 0.00, sig at 0.01). The study recommends that MSMEs, should increase income through projective planning and effective management, they should also be improvement of financial education through capacity building meeting, to enhance business expansion and loan compliance. In addition to the above MSMEs should apply for loans that are attainable and fit their business models.

Business Loan Characteristics and Inflation Shocks Transmission in the Euro Area

Business Loan Characteristics and Inflation Shocks Transmission in the Euro Area

Determinants of Bank Lending to Microenterprises: Evidence from Vietnam’s Commercial Banks

Microenterprises largely rely on bank loans for external funding. In an emerging market such as Vietnam, the role of commercial banks in providing loans to micro-firms is even more crucial. The present paper examines the question of what the determinants of bank lending to microenterprises are. This study conducts a two-step system generalised method of moments (GMM) estimation to investigate the relationship between bank-specific variables, macroeconomic factors, and bank industry characteristics on bank loans to microenterprises using the panel data from 26 Vietnamese commercial banks from 2011 to 2020. The results show that the microenterprise loan growth rate depends on bank-specific variables and macroeconomic factors. However, bank-specific variables and banking industry characteristics determine microenterprise lending propensity. This paper also contributes to the debate concerning microenterprise lending as the best approach, and which type of commercial banks would most often choose this alternative. Interestingly, it was demonstrated that larger banks had higher microenterprise loan growth rates, and smaller banks experienced a greater proportion of microenterprise loans in their total business loans.

How do institutional biases in lending practices restrict financial opportunities for underprivileged groups, and how do they perpetuate economic inequalities?

This paper explores how systemic barriers, specifically institutional biases, disproportionally restrict business opportunities for underprivileged groups through data analysis and literature review. This paper also highlights how biases in loan approval criteria and interest rates create systemic barriers. Minority-owned businesses and low-income entrepreneurs face significant challenges in securing necessary business loans and venture capital. This paper examines these biases and proposes possible strategies to reduce them and promote financial inclusion.

Factors Influencing Loan Repayment Among the Customers of Microfinance Institutions in Pokhara, Nepal

Background: Understanding the factors influencing loan repayment is essential for ensuring borrowers make timely loan payments. The microfinance model allows borrowers to access small business loans safely, aligned with ethical lending standards. Moreover, repayment behaviour highlights how individuals manage their debt, whether through on-time payments, paying more than the minimum, or defaulting. Objectives: This paper examines the factors influencing loan repayment among microfinance customers in Pokhara. Client, business, lender, and group characteristics are potential influencers of loan repayment. Methods: The study is based on a survey method with a purposive sampling technique, focusing on 120 respondents from registered microfinance institutions in Pokhara. Data was gathered using structured questionnaires, and the analysis was conducted using descriptive and inferential statistics. Results: The findings reveal that client characteristics such as age, marital status, and education significantly affect loan repayment, with middle-aged, married individuals showing better repayment behaviours. Business characteristics positively influence repayment, including enterprise type, years in operation, and business size. Lender characteristics such as MFI policies, monitoring, and performance are crucial in enhancing repayment, while group characteristics like peer support and pressure do not significantly impact repayment behaviour. Conclusion: The age, education, business type, and size of a client play a significant role, while lender policies and monitoring are also crucial. In contrast, group dynamics have less impact. Thus, microfinance institutions may focus on developing tailored financial products, flexible repayment schedules, and supportive programs to help clients repay their loans effectively. Keywords: Business characteristics, client characteristics, lender characteristics, loan repayment, microfinance institutions Paper Type: Research Paper JEL Classification: E4, E5, G21, G28

Developing A Predictive Model for Small Business Loan Default

Purpose: Governments assume responsibility for supporting SBs, including financial assistance. In South Africa, legislative measures and strategic initiatives have been established to bolster SBs, including the creation of funding agencies. These agencies intervene to enhance SB growth, job creation, poverty reduction, increased tax revenue and overall economic participation. This inherent risk results in ongoing losses and suboptimal returns on government investments, potentially wasting taxpayer funds. This paper proposes a model aimed at proactively increasing loan repayment probabilities. The study investigates SB characteristics that can pre-emptively mitigate loan repayment failures to government agencies. Design/Methodology/Approach: Employing a quantitative approach, a purposive sample of 114 SBs was analyzed using Stata, a versatile statistical software package. Findings: The findings highlight factors that may predict SBs' failure to repay loans from government agencies. These factors include risk taking, innovativeness, pro-activeness, customer relations, interpersonal relations, business planning, record keeping, financial management, market orientation, education and training, business experience and age and gender. Implications/Originality/Value: The study recommends that loan agreements should incorporate covenants that stipulate a required level of owner involvement in the business, as this serves as a demonstration of the owner's commitment.