Loan Repayment Research Articles

Nexus between small and medium-sized enterprise budgeting skills and loan repayment in South Africa

This study’s purpose is to assess the influence of small and medium-sized enterprises’ (SMEs) budgeting skills on loan repayment in South Africa. The quantitative research approach was selected as the appropriate methodology for this study, while the purposive sampling approach was selected as the appropriate way to select participants for this study. The primary data for this study came from respondents who were business owners of SMEs in the retail, hardware, construction, and manufacturing industries. SPSS was used to analyze the acquired data. A total of 380 research questionnaires were distributed, and there were 375 that were returned for analysis (which gives a response rate of 99%). Both a regression analysis and a correlation analysis using Pearson’s method were carried out. Pearson’s correlation coefficient revealed a positive and significant relationship between SMEs’ budgeting skills and loan repayment at the level of r =.250, p < 0.0005. These results were supported by the finding that there is a positive and significant association between these two factors. According to the findings of the study, it is recommended that financial providers educate their SMEs on how to prepare various types of budgets, how to follow up and compare their financial objectives to their performance, and that financial institutions and government organizations should assist SMEs with budgeting skills to decrease SME loan defaults.

Technical and Economic Performance Assessment of Solar Milling Plants in Zambia

In 2015, the Zambian government embarked on a proactive endeavor to enhance the accessibility of economical maize meal through the inception of the Solar Powered Milling Plants (SMPs) Project. The Chinese Government and the Government of the Republic of Zambia jointly provided co-financing, supporting this audacious initiative with a significant financial commitment of US$200 million. However, there have been no documented results on the technical and economic performance of the solar milling plants. To this effect, this study aimed to establish the technical and economic performance of the milling plants installed by the Zambia Cooperative Federation. To achieve this, the study sought to: (1) establish the technical operational characteristics of the installed SMPS; (2) establish the factors that influenced the sitting of the plants; (3) determine the economic benefits of the SMPs; and (4) benchmark the technical operating conditions of the installed SMPs. The study employed a mixed methods approach, where benchmarking observations and semi-structured questionnaires were used as data collection instruments. The sample size of the study was 168, comprising cooperative leaders, solar milling plant operators, and community members from the 12 sites in Masaiti, Chikankata, Solwezi, and Kapiri Mposhi districts where the milling plants were installed. The field observations and questionnaires that were used for the study showed that all twelve sites in the Solwezi, Masaiti, Kapiri Mposhi, and Chikankata Districts needed the same amount of power to run, which was between 7.5 kW and 9.0 kW. However, only Site 3 in Solwezi and Sites 4 and 5 in Masaiti Districts strictly followed the standard operation time of 8 hours. The study has also shown that the two main factors that influenced the placement of the solar milling plants were proximity to the main roads of the communities and the availability of land near the Food Reserve Agency(FRA) shades. With regards to economic benefits, the generated results showed that the installed milling plants brought about employment creation as two operators were employed for each of the 12 sites. However, the revenues generated by the solar milling plants were not economically viable for loan repayment. The study recommended that predictive and corrective maintenance, in addition to project management training for cooperatives and operators, be carried out to improve the technical and economic performance of the solar milling plants.

Iimpact of federal LRPs on behavioral health workforce examined

In the midst of a national behavioral health workforce shortage, it is necessary to evaluate the nature and effectiveness of current federal policy strategies to address this public health crisis, study authors of a new policy review stated about identifying and characterizing the impact of federal loan repayment programs (LRPs) on the behavioral health workforce.

Interest subvention for crop loans in India: Win-win or win-lose ?

Interest subsidies on crop loans are a common feature of rural credit markets in developing countries. The objective behind giving interest subsidies is two-fold – increasing access to credit and improving loan repayment rates, and is therefore regarded as a win-win for the borrower and the lender. This study focusses on a policy intervention that provides interest subsidy for crop loans availed under the Kisan Credit Card (KCC) scheme - India's flagship program to provide short-term agricultural credit for farmers. Using a unique dataset from a large public sector bank in India, we evaluate the causal impact of this intervention on both credit access and loan repayment behavior. We also capture the heterogeneous impact of the policy on new and existing borrowers. The results of econometric analysis - a combination of matching and difference-in-difference techniques - show a substantial increase (35%) in new loans, in addition to 20% decrease in the overall loan amount, indicating increased breadth and depth of access. However, contrary to standard economic theories, we observe a reduction in odds of repayment. Further, we find that the interest rate subsidy worsens the repayment rates of existing borrowers too. Our findings underscore the importance of various operational and behavioral aspects of the agricultural lending ecosystem to design win-win credit policies.

A Study on Determinants of Non-Performing Assets in Indian Banks

The purpose of this paper is to empirically examine the effect of macroeconomic determinants on non-performing assets (NPAs) in the India’s commercial banks using a panel regression model. This study considers all public, private, and foreign sector scheduled commercial banks during a period of seventeen years from 2004-05 to 2021-22, and uses four macroeconomic variablesGDP growth rate, inflation rate, interest rate and global volatility index- to assess the impact of these variables on NPAs. The findings show that NPAs have a negative relationship with GDP growth rate, confirming a increase in economic growth would rise the incomes of people and businesses and improve the ability of repayment of loans to the banks. Remaining three macroeconomic determinants negatively associated with NPAs but they were statistically insignificant. The result of the empirical study suggests that efficient management policies at the macro level are required to reduce the level of NPAs and to maintain the stability of the performance of banks in India.

A Research Review of Financial Distress Prediction

This study claims that two key points must be addressed in order to increase the success rate and robustness of financial distress prediction: firstly, a simplified financial prediction indicator system must be established based on a correct understanding and clearly distinguish about the concept of financial distress. Secondly, we establish a reasonable and plausible financial distress prediction model. It has been established that machine learning models can enhance financial distress prediction models' predictive power to some degree, bu the outcomes of these models vary. This is mostly due to a lack of knowledge about financial distress and a poor choice of indicators for predicting financial distress. This paper makes the case that there are three distinct, dynamic phases of financial distress. The financial strain stage is the initial phase. The financial distress at this stage is reflected in the financial indicators, as there are now some challenges with loan repayment due to the slowdown in the main business's revenue growth rate, the slowdown in operating cash flow, and the drop in the current ratio. The second stage can be called the financial crisis stage. The enterprise's ability to generate income is still declining, along with the quality of revenue and turnover rate. It’s worth noting that gearing ratio, which will be approaching 50% or above at this stage. The third stage of financial distress is distress situation. In this stage, the firm’s balance sheet structure keeps getting worse, and the gearing ratio keeps rising at an unprecedented rate. In the meantime, with growing revenue-cost-expense ratios and negative profits, profitability is still declining. At this stage, at least two of the three cash flows from financing, investing, and operating operations were negative in terms of cash flow.

Determinants of Loan Repayment Among Microfinance Beneficiaries in Lagos State, Nigeria

This study examines the determinants of loan repayment among microfinance institutions (MFIs) among their 384 microenterprises. The research found that age, gender, marital status, educational level, business experience, family size, type of business, interest rate, profit level, lending method, training/business enhancement program, and loan repayment time are not significant determinants of loan repayment among MEs in the study area. Prompt loan repayment can encourage cordial relationships between MFIs and their customers, and thus, MFIs and stakeholders should consider these significant variables when extending loans to their clients. This highlights the importance of timely loan repayment for MFIs' survival and growth.

Indicators of Sovereign Risk of South Africa’s International Monetary Fund Loan: The Nexus Between Political Risks and Economic Growth

Upon the approval of the 70 billion International Monetary Fund (IMF) loan for South Africa, concerns have emerged over the affordability of this loan and its impact on the economy and sovereignty of the country. South Africa’s ability to pay its IMF loan is assured because its track record of loan repayment is good, considering that the loan is repayable in five years at an interest rate of 1.1%. This study explores political and economic indicators of sovereign risk of South Africa’s IMF loan taken in 2020. The tenets of sovereign risk are being explored in a South African context. The significance of this study lies in understanding sovereign risk from a South African context and forecasting the country’s capacity and sustainability of servicing its IMF debt. This study presents a special and underexplored case of sovereign risk mainly due to 2020 being the first time South Africa has taken an IMF loan since the inception of a democracy in 1994. This qualitative study heavily relies on secondary literature, theories, and predictive forecasting models and is aided by descriptive statistics to reach its conclusion. Findings from the Council of Foreign Relations used the CFR Sovereign risk tracker designed to gauge the susceptibility of emerging economy to default on external debt.

The role of bank and startup fintech P2P lending in supporting financial credit for Indonesian farmers

One of the challenges faced by farmers is securing capital for the development of their agricultural businesses. Banks and peer-to-peer (P2P) lending fintech startups employ various business models to assist farmers in obtaining the necessary capital. This study investigates the credit financing schemes available to farmers through banks and P2P lending fintech startups. The research, which utilized a qualitative approach, involved collecting both primary and secondary data. Primary data were gathered through comprehensive interviews with two academic experts in the agricultural business sector and five leaders of agri-tech startup companies. Secondary data included: (1) annual financial reports from BRI, Mandiri, and BNI; (2) statistical reports on P2P lending providers from the Financial Services Authority (OJK); and (3) models of financing schemes for farmers derived from a range of empirical sources. A descriptive analysis was subsequently conducted to explore the various financing schemes available to farmers through banks and P2P lending fintech startups, as well as to assess the performance of these financing programs via data on the rate of non-performing loans (NPLs). The findings indicate that the financing schemes implemented by banks predominantly focus on economic factors to facilitate loan repayment. In contrast, P2P lending fintech startup schemes emphasize both economic and social aspects, including enhancing farmers' knowledge in implementing Good Agricultural Practices (GAP) and improving financial literacy, aiming to ensure smooth loan repayments. Furthermore, the study observed an increase in the value of Non-Performing Loans (NPL) among both banks and P2P lending fintech startups during the Covid-19 pandemic.

Estimation of Loan Repayment Events in Microfinance Bank Using L1 - Lasso Penalized Cox Proportional Hazards Approach

Estimation of Loan Repayment Events in Microfinance Bank Using L1 - Lasso Penalized Cox Proportional Hazards Approach

Loan Approval Prediction System Using Machina Learning

With the growth of the banking sector, the identification of reliable borrowers that must maintain the natural core income and asset accumulation becomes a key issue. Despite all security measures, reliability of customers remains an unclear question. To tackle this barrier, banking management which is directed towards customer loan repayment consistency is required. Credit approval is a significant aspect of economy since it determines the allocation of credit-linked funds. Today, machine learning is known for its power to automate and scale up the processing of application for loans. This project will begin with data collection which will consist of data on historical (regarding the past) loan applications and the borrower profiles. The dataset has features of the credit score, income, previous work experience, debt-to-income ratio, and loan repayment record. This way, the models learn through the strengths to find good features and the reasons for accepting a loan. They are the experts in these areas and can forecast the potential patterns and connections of the data. Within the scope of this work, the supervised algorithms used are logistic regression, decision trees, random forests, and support vector machines. These algorithms are applied to the dataset available to often produce results like binary classification and regression. The adoption of machine learning among financial institutions is intended for a faster processing of loans which is their benefit. What is credit scoring, it is a tool which automate manual loan application review thereby increases efficiency. The machine-learning algorithms that analyse applications for loans could cut down on the possibilities of human biases and mistakes which are an inherent part of the process. Also, ML uses the model to recognize borrowers who may default and subsequently lower the likelihood of default. Part of the task involve utilizing historical credit market data and implementing ML algorithms to develop a highly accurate and reliable loan approving system based on trained-data, random forests, the stream of loans and reliable clients.

Understanding Students Attitudes and Intentions to Repay Loans: A Comprehensive Study

This research aims to conduct an in-depth study on students' attitudes and their intentions regarding the repayment of loans. Recognizing the importance of understanding the factors that influence students' willingness and ability to repay loans, this study utilizes a mixed-methods approach to explore the intricate relationship between attitudes, financial behaviors, and loan repayment intentions among student borrowers.
 The study employs qualitative research methods, including interviews, focus group discussions, and case studies, to gather nuanced insights into students' attitudes towards loans, their financial decision-making processes, and the factors influencing their intentions to repay loans. Concurrently, quantitative surveys and data analysis will be used to identify trends, correlations, and statistical patterns related to student borrowing and loan repayment behaviors. Various dimensions will be explored, including the impact of financial literacy, economic circumstances, and educational experiences on students' attitudes towards loans. The study also aims to uncover the perceived barriers and facilitators that influence students' intentions to fulfill their financial obligations post-graduation. The findings from this research are expected to provide valuable insights for educational institutions, policymakers, and financial institutions. By understanding students' attitudes towards loans and their intentions to repay, stakeholders can develop targeted strategies to enhance financial education, improve loan repayment rates, and foster responsible financial behaviors among student borrowers. This study serves as a foundation for informed decision-making and future research within the realm of student loan attitudes and repayment intentions.

Replicating the suitability rule and economic theory in pursuit of microfinance inclusion of women micro-agribusinesses in rural financial markets

PurposeWith reference to the global financial crisis and lessons learned, advocacy for distributing suitable financial products by financial intermediaries remain key if consumers, especially the illiterate in underdeveloped financial markets, are to be absorbed into the formal financial system. Financial intermediaries such as microfinance banks should provide suitable financial products, with full disclosure of information and customer protection relating to distribution of all financial products within the financial market to prevent financial vulnerability. The main purpose of this study is to establish the mediating role of financial product suitability in the relationship between access to microfinance products and survival of women micro-agribusinesses in rural Uganda.Design/methodology/approachSmartPLS with bootstrap based on 5,000 samples was used to test for the mediating role of financial product suitability in the relationship between access to microfinance products and survival of women micro-agribusinesses in rural Uganda.FindingsThe results revealed that financial product suitability improves access to microfinance products by 29 percentage points to promote survival of women micro-agribusinesses in rural Uganda. In reality, delivering suitable financial products that suit the economic condition of poor women micro-agribusiness borrowers, can allow them to use these products to generate income to meet timely repayment obligations and business demands.Research limitations/implicationsThe current study selected samples from only women micro-agribusinesses operating in rural Uganda, with a specific focus on the northern region. Thus, studies involving samples selected from other rural developing countries may be necessary in future. Additionally, while the findings are significant, the data were collected from only women microenterprises who are clients of microfinance banks. Future studies focusing on women microenterprises who are clients of other financial institutions may offer insightful comparative data.Practical implicationsThe findings from this study offer strategies for managers of microfinance banks to invent and design financial products that suit the economic status and condition of different microcredit clients, especially the women micro-agribusinesses. This can help them to solve the problem of defaults in loan repayment and delinquency common while lending to the rural poor. In fact, microfinance banks should adopt a customized loan pricing model that can promote the operational sustainability and commercial viability of women micro-agribusinesses in the current situation of mission adrift.Originality/valueThe current study uses the suitability rule and economic theory to elucidate the importance of microfinance product suitability to increase microfinance inclusion of women micro-agribusinesses in rural areas in developing countries. The novelty in this paper is in combining the suitability rule and economic theory with microfinance theory to promote access to microcredit by the women micro-agribusinesses in rural Uganda under the situation of mission adrift. This is limited in the existing microfinance literature and theory, especially in developing countries like Uganda.

Empirical modeling of agricultural climate risk

Effective policies for adaptation to climate change require understanding how impacts are related to exposures and vulnerability, the dimensions of the climate system that will change most and where human impacts will be most draconian, and the institutions best suited to respond. Here, we propose a simple method for more credibly pairing empirical statistical damage estimates derived from recent weather and outcome observations with projected future climate changes and proposed responses. We first analyze agricultural production and loan repayment data from Brazil to understand vulnerability to historical variation in the more predictable components of temperature and rainfall (trend and seasonality) as well as to shocks (both local and over larger spatial scales). This decomposed weather variation over the past two decades explains over 50% of the yield variation in major Brazilian crops and, critically, can be constructed in the same way for future climate projections. Combining our estimates with bias-corrected downscaled climate simulations for Brazil, we find increased variation in yields and revenues (including more bad years and worse outcomes) and higher agricultural loan default at midcentury. Results in this context point to two particularly acute dimensions of vulnerability: Intensified seasonality and local idiosyncratic shocks both contribute to worsening outcomes, along with a reduced capacity for spatially correlated ("covariate") shocks to ameliorate these effects through prices. These findings suggest that resilience strategies should focus on institutions such as water storage, financial services, and reinsurance.

The Effect of Financial Literacy on Loan Repayment Performance of MSMEs: A Literature Review

Credit loans among MSMEs are beneficial for business sustainability. The quality of a credit loan is a concern to avoid default, so the topic of loan repayment performance is interesting to explore. This study summarizes and analyzes several previous studies related to the topic of the influence of financial literacy on business performance among MSMEs, as well as the influence of financial literacy on loan repayment performance. Based on a literature study conducted, financial literacy was found to have a significant influence on business performance and loan repayment performance among MSMEs. This study found gaps in previous research, there are still limited studies that provide a comprehensive framework explaining how financial literacy influences loan repayment performance directly or through business performance variables. Therefore, it is important to research further, how an MSME manager who accesses credit to run his business can achieve optimal business performance, where the results will be used for loan repayment. This research proposes business performance as a mediating variable that could be considered in future research.
 Keywords: financial literacy, business performance, loan repayment performance

A New Formulation of Interest-Bearing Capital and Debt: A Marxian Perspective on the Circuit of Capital

This article refines the analysis of interest-bearing capital and debt in Marx’s circuit of capital, incorporating Kōzō Uno’s critique for a more precise depiction. It reassesses Marx’s model of interest-bearing capital () and Uno’s distinction between creditor and debtor roles, proposing an advanced model that highlights the role of financial instruments () and debt (). The form of money-lending capital for the creditor is articulated as , where represents the issuance of a loan and the collection of debt. On the other hand, the form of merchant capital with debt for the debtor is depicted as , incorporating both the borrowing () and repayment () processes within the form of merchant capital. This approach not only clarifies the transactions between creditors and debtors but also builds upon Uno’s theoretical contributions, offering a comprehensive framework for understanding the dynamics of interest-bearing capital and the movement of capital with debt. The revision aims to elucidate the processes of loan issuance, debt collection, borrowing, and repayment, rectifying previous conceptual oversights and offering a solid foundation for future economic research.

Cost of Training Crisis: Anaesthetics.

The anaesthetic training programme in the United Kingdom (UK) spans over seven years and is overseen by the Royal College of Anaesthetists (RCOA). Junior doctors in England are currently striking amid ongoing pay negotiations with the government, and almost all junior doctors are worried about the cost of living. This article provides an overview of the average financial cost of training for doctors in the anaesthetic training programme. The cost incurred by anaesthetic trainees illustrates the level of financial burden faced by trainees across multiple specialities. The cost includes: student loan repayment (with interest rates), compulsory membership fees (including the Royal College of Anaesthetists and General Medical Council), postgraduate examinations (Fellowship of the Royal College of Anaesthetist exams are compulsory to complete training) and medical indemnity. The average trainee spends between 5.6% and 7.4% of their annual salary on non-reimbursable costs. This article delineates for aforementioned expenses and compares them with the training programs in Australia and New Zealand, given their status as frequent emigration destinations for UK doctors.

A Study on Factors affecting College Graduates’ Entry into the Early Labor Market: Focusing on the Burden of Student Loan Repayment

A Study on Factors affecting College Graduates’ Entry into the Early Labor Market: Focusing on the Burden of Student Loan Repayment

On a Flexible Loan Repayment Method Depending on Borrower’s Asset with an Early Termination Clause

On a Flexible Loan Repayment Method Depending on Borrower’s Asset with an Early Termination Clause

Learning Fair Policies for Multi-Stage Selection Problems from Observational Data

We consider the problem of learning fair policies for multi-stage selection problems from observational data. This problem arises in several high-stakes domains such as company hiring, loan approval, or bail decisions where outcomes (e.g., career success, loan repayment, recidivism) are only observed for those selected. We propose a multi-stage framework that can be augmented with various fairness constraints, such as demographic parity or equal opportunity. This problem is a highly intractable infinite chance-constrained program involving the unknown joint distribution of covariates and outcomes. Motivated by the potential impact of selection decisions on people’s lives and livelihoods, we propose to focus on interpretable linear selection rules. Leveraging tools from causal inference and sample average approximation, we obtain an asymptotically consistent solution to this selection problem by solving a mixed binary conic optimization problem, which can be solved using standard off-the-shelf solvers. We conduct extensive computational experiments on a variety of datasets adapted from the UCI repository on which we show that our proposed approaches can achieve an 11.6% improvement in precision and a 38% reduction in the measure of unfairness compared to the existing selection policy.