Model Of Lending Research Articles

The Resource-Backed Lending Model: An Economic Limitation to Sovereignty of Developing States

The 21st century developing and under-developed economies are being relegated to the status of neo-colonial states. Developed economies like China, Russia and the United States of America are really in the scramble for more neo-colonial states, mostly in Africa. This has presented itself through the economic relationship among states. The economic relationship under consideration here is taking new turns with emerging global trends and the desire of developing states to alleviate or eradicate poverty. The economic relationship between developed and developing states has grown from exchange of goods and investment to the execution of infrastructure loans on the understanding that the receiving states (borrower in this instance) shall mortgage its local resources to secure the loan. This is clearly the greatest limitation to the sovereignty of developed states under the guise of business agreements. The objective of this article is to examine a number of resource-backed lending systems between developed and developing states, delving more into the business relationship between China and Nigeria; this examination is further related to the relationship between China and states like Angola and Congo. The question sought to be answered is whether this system has proved to be beneficial or detrimental to the sovereignty of developing states is considered in this study. This is done by examining the Nigeria-China Bilateral Investment Treaty and the $400 million Loan Agreement (“Loan Agreement”) executed by the Ministry of Finance on behalf of Nigeria and the Export –Import Bank of China for the Nigeria National Information and Communication Technology (ICT) Infrastructure Backbone Phase II Project in 2018.

Resilience of the group lending model to a COVID-19 induced shock: evidence from an Indian microfinance fund

PurposeThe authors study the effect of an exogenous shock in the form of Coronavirus lockdowns on individual default and on default contagion within the microfinance (MF) sector in India. The authors rely on proprietary data obtained from an MF institution for the period from Nov 2019 to Dec 2020. The authors show that default increased to 95.29% in the month of April 2020, when Covid lockdowns were fully in place. However, borrowers bounced back thereafter, either making full or partial payments, so that defaults had fallen to 5.92% by December 2020. Static features of the group lending model like peer monitoring and joint liability help explain 90% of the monthly deficit during Covid lockdowns among uneducated borrowers. Dynamic features such as contingent renewal help explain why defaults were cured quickly through timely repayments. Finally, there is an absence of default contagion at the district level. Indeed, lagged own default explains 96.6% of variation in individual default, rather than contagion through group, village or district-level defaults. The authors conclude that the MF sector is resilient to exogenous shocks like the pandemic.Design/methodology/approachThe authors use time series panel regressions, as well as cross-sectional regressions.FindingsThe authors find that borrower defaults increased significantly to 95.29% during the month of April 2020, when Covid lockdowns were fully in place. However, borrowers bounced back almost immediately, either making full or partial payments, such that defaults had fallen to 5.92% by December 2020. The group lending model does remarkably well in explaining defaults even during Covid lockdowns. Among the majority (92%) of borrowers who are residents of rural districts, the group lending model appears to blunt the impact of the exogenous shock on rates of default. Indeed, panel regressions demonstrate that the group lending model helps explain 90% of the monthly deficit among uneducated borrowers. Logistic regressions indicate that the group lending model is less persuasive among relatively affluent borrowers residing in semi-urban or urban areas who have some formal schooling. Contingent renewal is shown to be an effective disciplining mechanism when a group does default due to the Covid lockdowns. The authors find that groups who defaulted in April 2020 but repaid the outstanding balance within the next two months were more likely to receive subsequent loans from the lender. On the other hand, groups who defaulted in April 2020 and did not repay the outstanding balance until December 2020 did not receive follow-on financing. Finally, the authors find that lagged individual default is the primary source of individual default, rather than contagion through group, village or district-level defaults.Research limitations/implicationsThe limitation of the study is that it is confined to a single MF institution in India.Social implicationsThe authors conclude that the social capital that is the foundation of the group lending model succeeds in limiting both the risk and contagion of default from an exogenous shock, such as the Covid pandemic.Originality/valueTo the best of the authors’ knowledge, the authors are the first to examine defaults in the Indian MF sector during the Covid lockdowns in April 2020.

On-Demand Circulation of Software Licenses

The Miami University Libraries (MUL) developed an open-source Software Checkout system to allow patrons to make use of software licenses owned by the library. The system takes advantage of user-based licensing under the Software as a Service (SaaS) license model and vendor-created APIs to easily and legally assign access to users. The service currently supports Adobe Creative Cloud, Final Cut Pro, and Logic Pro software. MUL has successfully used this software for three years. This article describes the expansion of offerings and the increasing use of the service over that time. Built on a model developed by Pixar for managing employee software licenses, the Software Checkout system is believed to be the first of its kind for circulating licenses to library patrons. Both this lending model and the open-source software developed by MUL are available to other libraries. This paper is intended to prompt libraries to take advantage of the legal and technical environment to expand software license sharing to other libraries.

The effects of policy interventions to limit illegal money lending

We estimate a structural model of borrowing and lending in the illegal money lending market using a unique panel survey of 1,090 borrowers taking out 11,032 loans from loan sharks. We use the model to evaluate the effects of interventions aimed at limiting this market. We find that an enforcement crackdown that occurred during our sample period increased lenders’ unit cost of harassment and interest rates, while lowering volume of loans, lender profits and borrower welfare. Policies removing borrowers in the middle of the repayment ability distribution, reducing gambling or reducing time discounting are also effective at lowering lender profitability.

Banking competition, credit financing and the efficiency of corporate technology innovation

Based on the data spanning 2010 to 2022, this study delves into how banking competition impacts the efficiency of enterprise science and technology innovation by lowering credit costs, enhancing credit availability, optimizing credit allocation, and offering empirical evidence for the significant role of banking competition in influencing corporate technology innovation efficiency. This paper concludes that increased competition in the banking sector notably impacts corporate technology innovation efficiency. Banking competition alters the traditional relationship-based lending model, enhancing banks' ability to assess risks and support innovative projects by enterprises, encouraging enterprises to enhance innovation quality and boost research and development investments, leading to a learning curve effect on innovation and enhancing the efficiency of technology innovation. Mechanism analysis reveals that credit financing plays an intermediary role. Competition in the banking sector leads to lower costs and increased availability of bank credit for research and development in enterprises. It helps address the issue of limited finance for innovation in enterprises, encourages larger-scale innovation, and enhances innovation efficiency. Banking rivalry has a role in enhancing corporate technology innovation efficiency, which is influenced by the environment to a certain extent.

Risk Analysis and Supervision of P2P Online Lending

In the new era of rapid development of science and technology, the combination of finance and technology has brought new financial cognition to people, but the emergence of financial technology has also brought great challenges to risk management in the financial field. With the development and maturity of Internet technology, the rapid innovation of Internet finance has promoted the prosperity of online lending, well met the financing needs of various entities in the market, and effectively solved the problem of expensive financing for small and medium-sized enterprises and private enterprises. However, the rapid development of Internet finance has also spawned a wider range of financial risks and updated forms. Taking P2P online lending as an example, this paper analyzes the causes and effects of the rise of P2P online lending, finds that there is asymmetric leverage effect in the fluctuations of P2P online lending, analyzes the risks, existing problems and causes of final failure of P2P online lending, and explores the development model of online lending in the post-P2P era and the construction of big data risk control system. Finally, some practical suggestions and countermeasures are given.

Climate risk in mortgage markets: Evidence from Hurricanes Harvey and Irma

AbstractUsing the Credit Risk Transfers (CRTs) issued by Fannie Mae and Freddie Mac, we study how, absent government intervention, mortgage markets would price hurricane risk. Currently, such risk is priced equally across locations even if it is location‐specific. We hand collect a novel and detailed database to exploit CRTs' heterogeneous exposure to Hurricanes Harvey and Irma. Using a diff‐in‐diff specification, we estimate the reaction of private investors to hurricane risk. We use the previous results to calibrate a model of mortgage lending. We simulate hurricane frequencies and mortgage default probabilities in each US county to derive the market price of mortgage credit risk, that is, the implied guarantee fees (g‐fees). Market‐implied g‐fees in counties most exposed to hurricanes would be 70% higher than inland counties.

Choosing a mortgage lending model in the Kyrgyz Republic

In the modern world, mortgage plays an important role in the life of the citizens of the country due to its important role in providing their housing needs. Thus, it is important to find the most effective model of mortgage lending for the country to maximize the living standards of its citizens. The aim of the work is to choose the most effective model of mortgage lending that can be used in the country and bring the greatest benefit to it. The main methods used in the research were analysis, deduction, induction, and abstraction. The paper examined various aspects of mortgage lending, focusing on the different payment models and their implications for borrowers. Two types of mortgage loans were considered: with annuity and differentiated payments, their main differences in terms of payment rates were described, and mathematical formulae for their calculation were specified. To illustrate the impact on the borrower of each of them, a theoretical example was provided, on the basis of which the differences between the two systems were described. The paper also describes three models for organizing mortgage lending systems: a closed (stand-alone) mortgage system, a truncated open model and an extended open model. The suitability of these models for the development of the Kyrgyz mortgage market was assessed based on their characteristics and features, positive and negative components. The work brings new knowledge in the context of studying the peculiarities of mortgage lending as a whole, as well as allows finding opportunities for improving its functioning in the Kyrgyz Republic

Understanding Lifelong Learning in Successful Women Managed Small and Medium Enterprises in Kakamega County: The Case of Kenya Women Microfinance Bank

This qualitative study was a follow up to a 2022 study on the impact of lifelong learning (LLL) on women managed, small and medium enterprises in the context of KWFT biashara loan. The study sought to: create a deeper understanding of the LLL experiences of successful women managers of KWFTbiashara loan SMEs; find out the influence of LLL on successful women managed KWFT SMEs, from the perspective of the women managers, with an aim of making recommendations for policy and practice for LLL in the KWFT financial literacy training. This study utilized a multi-site case study approachthat purposively selected three successful SMEs from a pool of six SMEs that were observed in the 2022 study in Kakamega County of Kenya, under this Women Economic Empowerment Project funded by the Bill and Melinda Gates Foundation and housed at Kenyatta University WEE-Hub. Data was collectedby use of semi-structured interviews and observation. Among other findings, this study reveals varied experiences and opinions concerning LLL in the context of KWFT biashara loan, including the group model of training and lending that was praised in one case and described as having some weaknessesthat required attention in two cases. Notably, all women managers of the successful KWFT biashara loan SMEs understood the basics of business and financial management, which they partly attributed to LLL in the context of KWFT financial literacy training. They also had strong support from their spouses,diversified their businesses and had visible assets that were acquired from the proceeds of the SMEs, among other findings. This study demonstrates how KWFT could strengthen the group model of training and improve on the training curriculum, among other recommendations.

Credit Lending Models and Loan Performance of Deposit-Taking Savings and Credit Cooperative Societies in Kenya

The study sought to determine the effect of credit lending models on loan performance of deposit-taking savings and credit cooperative societies in Kenya. Specifically, the study focused on group lending model, individual lending model, digital credit model and cooperative lending model on loan performance of deposit-taking savings and credit cooperative societies in Kenya. The study adopted a descriptive cross-sectional design. The targeted population was all DT-SACCOs as per their registration with SACCO Societies Regulatory Authority. The study population was 176. The study found out that group lending models, individual lending models, digital credit lending and cooperative lending were adopted by the DT-SACCOs to a moderate extent. The study established that the size of the DT-SACCOs and the lending models used accounted for 97.9% of changes in loan performance. The consequence is that other factors not considered in the model were responsible for only 2.1% of variances in loan performance. Further, credit lending models had a significant effect on the loan performance of DT-SACCOs in Kenya. This implied that effective implementation of the credit lending models led to improved loan performance of DT-SACCOs. The study concluded that credit lending models significantly affect the loan performance of DT-SACCOs in Kenya. Further, the DT-SACCOs adopted, on an average basis, the credit lending models. Lastly, individual lending models and total assets significantly affected loan performance. Group lending models, digital lending models, and cooperative lending models, however, do not have a significant effect on loan performance. The study recommended that the managers of the DT-SACCOs should establish mechanisms for improving individual loan processing and the development of competitive individual loan products.

Research on Decentralized Finance Lending Protocols: A Case Study of Compound

Decentralised finance (DeFi) is a decentralised peer-to-peer system based on blockchain technology that facilitates lending and borrowing through smart contract code and lending protocols replacing traditional financial activities that typically require trusted intermediaries such as brokers or banks. In this essay, the four factors of collateral presentation, borrowing rate, lending relationship, and subject of legal connection are compared between decentralized and centralized financial lending models. This paper illustrates the entire DeFi lending model using Compound as a real-world example. The borrowing interest rate is decided in real time by Compound's smart contract according to the supply and demand of funds in the market, so the borrower does not need to bargain with the lender. The smart contract will automatically match the money market. Additionally introduced are the DeFi innovation's concept and features. The paper concludes by discussing the advantages of DeFi lending and borrowing, the hazards associated with doing so, and providing an outlook on the future path of DeFi research.

A decentralised KYC based approach for microfinance using blockchain technology

• The proposed lending model eliminates the middle parties like banks in the loan process. It decreases the time taken to a great extent. • The proposed decentralised KYC model eliminates a lot of human interaction in the process of KYC verification. It restricts the submission of one's documents in multiple organizations, which has a high risk of data bleaching if those organizations compromise the security systems. • As every transaction will be stored in a blockchain and are resistant to modification, neither of the parties can default on any transaction. Financial inclusion is seen as a dynamic tool for achieving multifaceted microeconomic stability, (and) sustainable economic growth, job creation, poverty reduction, and income equality for both developed and developing nations. The needy segments of the population must be provided with financial services to accomplish this inclusion. Still, the traditional financial market is unavailable due to its lack of collateral and shallow income. Thus, they go to local moneylenders, also known as "loan sharks," who charge exorbitant interest rates. Introduction to microfinance came as a new and refreshing light to these needy segments of the population as it provides small valued loans (micro-credit) to support their micro-scale businesses and engage in productive activities. As emerging technology started to be incorporated into every aspect of society, thus microfinance also needed to be incorporated into the technology. An application is required to protect data integrity and smoothly influence the microfinance sector. As the databases are vulnerable to data manipulation, this can affect the transaction history of the loan. Blockchain technology can be used to solve this problem, as data in the Blockchain is stored immutably. So, we designed a microfinance application that uses blockchain technology with decentralised KYC architecture to reduce multiple KYC verification and easy access to micro-credit.

Community influence on microfinance loan defaults under crisis conditions: Evidence from Indian demonetization

AbstractResearch SummaryThe microfinance “group lending” approach has achieved widespread success in promoting high rates of repayment, and thus the viability of financial access, in very low‐income environments. Yet group lending, which relies on social connections between borrowers to reinforce repayment, may be vulnerable under crisis conditions in which defaults are commonplace. We explore this possibility in the context of the liquidity crisis that followed India's 2016 demonetization policy. Using proprietary data on the repayment behavior of about two million microfinance borrowers, we find evidence of disproportionate localization of defaults within lending communities. Further analysis reveals evidence consistent with borrower‐to‐borrower spread of defaults not only through formal joint‐liability connections but also through informal community‐level connections, the latter effect being especially pronounced for borrowers from the same religion.Managerial SummaryMicrofinance lenders have successfully employed a “group lending” approach that holds borrowers within a small group responsible for each other's loans, thus creating strong social pressures for repayment. The findings of this study underscore potential vulnerabilities in the group lending model during economic crises. We analyze the loan repayment behavior of two million microfinance borrowers during a liquidity crisis precipitated by India's 2016 demonetization policy, finding that the resulting defaults were clustered within particular lending communities. Further analysis suggests that social processes within communities played a role in spreading defaults, not only through formal ties between borrowers who were responsible for each other's repayments, but also through informal social ties. The estimated effect of informal social ties was particularly strong for borrowers who shared the same religion.

ANALISIS PEMBUATAN SISTEM ANTIFRAUD PADA STARTUP FINTECH, KHUSUSNYA PEER-TO-PEER LENDING

Fintech startups, especially those in the peer-to-peer lending model, have major challenges regarding security risks and fraud. Therefore, this research aims to analyze the creation of an effective antifraud system to increase transaction security on peer-to-peer lending platforms. By understanding the characteristics of possible fraud and applying advanced technology, it is hoped that this system can provide better protection against security risks.

The Impact of Online Credit Lending Model on the Public's Overspending Decision

In recent years, with the rapid development of the Internet, the financial market pattern is also changing. And the way of consumption through the Internet is gradually becoming mainstream. In order to meet the needs of the majority of consumers, online credit products have emerged. The emergence of this new financial service is not only a change in the quality of life of the masses of society, but also a new challenge for the financial market. Therefore, this paper investigates its impact on consumers' over-consumption decisions. Through regression analysis, we conclude that there is a positive relationship between the online credit lending model and the public's overspending decision. And the higher the loan amount, the longer the repayment period, the lower the loan interest rate, and the more accessible the loan qualification, the higher the public's willingness to overspend. On the other hand, the degree of loan facilitation has no statistically significant effect on the degree of overspending. By establishing a model to analyze the degree of overspending, this study is conducive to the establishment of reasonable consumption habits by consumers. It can help the financial service industry understand customers' consumption tendencies, rationalize their programs and provide a reference for government agencies to formulate economic policies. And it can promote the successful development of the financial market.

Peer-to-Peer Lending as a Determinant of Federal Housing Administration-Insured Mortgages to Meet Sustainable Development Goals

In this paper, we investigate the influential factors of Federal Housing Administration (FHA) mortgage loans, focusing our research interest on peer-to-peer (P2P) lending, the most successful FinTech lending model. We consider P2P lending an alternative source of financing that marginal borrowers use to pay the increased mortgage down payment, making them eligible to receive a mortgage from conventional banks. In other words, we examine whether and to what extent P2P lending has a positive impact on the FHA loans volume by providing the ability to circumvent the loan-to-value (LTV) cap policy. As a result, P2P lending can be seen as a means for ”rationed” borrowers to have access to the market by reducing inequalities and promoting financial inclusion, thus achieving Sustainable Development Goals (SDGs). We employ hand-collected data from FHA mortgages, P2P loans, and other economic factors from all 50 U.S. states during 2007–2017 and use panel data techniques for this purpose. Research shows that P2P lending, GDP per capita, population growth, broad money growth rate, interest rate, unemployment rate, new housing units, and consumer confidence Index produce effects on FHA loans. We show that P2P lending, a nonconventional determinant, is causally associated with a significant increase in the count and volume of FHA loans, implying that P2P lending has a positive impact on them. The ability of P2P to bypass mortgage supply constraints (tightened LTV caps) by providing small loans to borrowers to meet the increased down payment requirements is very important to policy-makers, as it shows that constraining the volume of mortgage loans may be not achieved. Macroprudential tools designed to control credit growth may prove ineffective, as the use of alternative forms of lending helps circumvent them and ultimately leads to excessive household leverage with all the risks that it poses to the financial system.

FinTech credit: uncovering knowledge base, intellectual structure and research front

PurposeOwing to the dramatic rise of FinTech credit in the financial sector, this study describes its knowledge and intellectual structure and paves the way for future research.Design/methodology/approachThe study employs citation analysis, keyword analysis, co-author analysis, co-citation analysis and bibliographic coupling on 268 peer-reviewed articles published during 2010–2021 and extracted from the Web of Science database.FindingsResearch on FinTech credit has picked up momentum from 2016, with majority contributions from China, followed by UK and USA. International Journal of Bank Marketing is found to be the most productive journal. Co-citation analysis reveals that past studies have focused on three dominant themes, viz. (a) factors that influence user intention to adopt technological products and services (b) borrowers' and lenders' characteristics that impact fund-raising in FinTech credit platforms and (c) evolution of FinTech market over the years. Bibliographic coupling reveals that recent trends in FinTech credit include (a) impact of emerging technologies like blockchain, artificial intelligence, big data on financial system, (b) factors that encourage consumers to adopt the FinTech products and services, (c) mechanisms by which FinTechs have transformed formal credit markets, (d) factors that lead to successful fundraising in FinTech platforms and (e) critical perspectives on digital lending platforms.Originality/valueTo the best of the authors' knowledge, this is a pioneering study undertaking an exhaustive analysis of FinTech credit as a research area. The study offers valuable insights on potential topics of research in FinTech credit domain like investigating Balance Sheet Lending Model, investigating the impact of FinTechs on financial system, and new markets by collaborating with scholars of other regions.

INCREASING SOLVENCY BY MODERATING SOCIAL CAPITAL: A STUDY ON GROUP LENDING MODEL FROM COMMUNITY EMPOWERMENT TRUST FUND – INDONESIA

The Community Empowerment Trust Fund is a revolving fund belonging to the community originating from the former Sub-District Development Program and the National Program for Independent Rural Community Empowerment in Indonesia which ended in 2014. Community institutions then manage the Community Empowerment Trust Fund to fund community economic activities in the form of group loans. The group lending model is a financial inclusion that reaches the poor who do not have collateral. These funds have been managed well with the group loan model. However, the success of managing these funds cannot be separated from the social capital built between group members and between the group and the fund management unit. This study aims to examine the management of the borrower group – group internal setting; group loan appraisal and group loan control – and social capital on repayment performance. The study results prove that group lending appraisal, group lending control, and social capital positively impact repayment capacity. The research finding is social capital strengthens group lending control dynamics to increase repayment capacity. Another finding explains that women’s loan groups have a higher collectability rate in repayment of loans compared to productive economic business groups whose members are both male and female.

Group lending, sorting, and risk sharing

This paper studies group lending with joint-liability contracts offered by Microfinance Institutions (MFIs). We develop a model of group lending where heterogeneous agents form groups, obtain capital from the MFI, and share risks among themselves. We show that the composition of the groups is not always homogeneous once risk-sharing is introduced, rationalizing the empirical evidence of risk heterogeneity within groups. Moreover, we find that joint liability introduces inefficiency for risk-averse borrowers, which explains why MFIs are moving away from joint-liability contracts. Surprisingly, the first-best outcome can be achieved even in the presence of information asymmetry.

Digital Transformation in the FinTech Sector

This paper mainly analyzed the specific application of fintech technology in different aspects, and the changes this emerging technology can bring to people's lives. In terms of the payment system, the formation of oligopoly may lead to serious uneven market competition. Although clients with personal advisers are less likely to trust the services of robots, robo-advice can provide better investment advice to ordinary people and expand the benefit group. For P2P lending, this is a new lending model, eliminating the tedious steps and high fees of the middleman. Virtual currency as an original application of blockchain is the financial derivative that threatened the financial money investment market. The author explained how to benefit more consumers through fintech technology, and the progress of technology enables customers of different classes to have better service experience. The digitalization process of financial services promotes economic development and can provide customers with more inclusive and professional financial services. Fintech has gradually changed the pattern of the financial industry, gradually weakened the role of financial intermediaries, and created a new operating system.