Types Of Loans Research Articles

Frontline Worker Discretion in the For‐Profit Banking Industry: Lessons From Early Pandemic Relief Programming

ABSTRACTIn April and May 2020, the United States banking industry approved over $650 billion in federal relief funds as part of the Paycheck Protection Program (PPP). Since then, extensive evidence of discriminatory lending has been revealed by investigative journalism and academic studies. Our study is based on 41 interviews with frontline banking professionals conducted during the days and weeks of the PPP rollout. We find that under the crisis conditions of the pandemic, capped funds in the PPP and built‐in incentives that encouraged certain types of loans, banking employees relied upon the professional norms and logic of the for‐profit sector. We argue that these norms and logics threatened the integrity of the PPP as a public relief programme by applying profit‐oriented priorities to resources marked for universal and fair distribution. Our findings offer new directions for theorising sector‐level differences in street‐level bureaucratic discretion in the context of mixed‐sector collaboration on public service delivery, particularly under conditions of crisis and urgency.

Долгосрочное кредитование в российских банках: современность, влияние инфляции и цифровые новации

The article discusses the theoretical foundations of long-term lending, analyzing its role and necessity for de-velopment within the Russian economy. The dependence of long-term lending on the influence of inflation in the period 2021–2024 is investigated. It also substantiates the dependence of the growth and decline in lending growth rates on the level of inflation and concludes that inflation affects precisely the growth rate of lending volumes, but not the increase or decrease in lending volumes. An analysis of the dynamics of lending is carried out for various categories of borrowers (corporate loans (non-financial organizations, financial organizations, individual entrepreneurs), individuals, government agencies), by types of loans and by loan terms. Innovative trends that can be observed in the long-term lending market in modern conditions are highlighted.

Environmental, Social, and Governance Scores and Loan Composition Inside United States Banks

We analyze the loan portfolios of United States banks from 2013 to 2023, showing that high environmental, social, and governance (ESG) banks have larger shares of consumer loans and commercial loans and smaller shares of construction loans and real estate loans. We also find that the governance pillar (G) is more tightly related to the bank loan composition compared to the environmental (E) and social (S) pillars. Furthermore, we show that construction loans and real estate loans decrease more considerably with bank ESG scores inside countries with high gas emissions, i.e., where ESG issues would arguably be more serious. Our interpretation is that sustainable banks are reluctant in lending money for real estate projects, exposing them to potentially high ESG risk. These findings contribute to developing a deeper insight about the relationship between ESG and bank lending, which, in the previous literature, has been treated more frequently in aggregate terms instead of separating loan types. Our outcomes suggest that sustainability is crucial for the availability of funds in the real estate sector, delivering important insights to bank and real estate managers, besides policy makers.

ANALYSIS OF BUBBLES ASSETS FOR WEIGHTED AVERAGE INTEREST RATES APPLIED TO BANK LOANS

This study examines the existence of the "bubble effect" in the average interest rates of loans applied by banks to various types of loans for consumers. The purpose of this article is the research of the bubble formations in the average interest rates applied by the banks to consumer, housing (home), vehicle, and commercial loan types. This article examines the existence of bubbles in the average loan interest rates of banks in Turkey using the GSADF unit root test developed by Phillips et al. (2015). Bubble assets are analyzed with weekly data for the period June 2019–March 2023. Monte Carlo simulations performed obtained critical values for the GSADF unit root test. The results show that the bubble effect on housing loan interest rates is statistically significant at the 0.05 level. Against this, although the existence of a bubble effect in consumer, vehicle, and commercial loan interest rates has been determined, these bubbles are statistically insignificant.

Interest rate spreads: Different stories for different types of loan

The paper studies the determinants of the interest rate spreads in Estonia, a country that stands out among European countries for its wide spreads and highly concentrated banking sector. Four distinct credit markets are considered for housing loans, consumer loans, long-term corporate loans and short-term corporate loans. The paper uses quarterly panel data from 2000Q1–2021Q1. It uses a two-stage approach to disaggregate the observed spread into a component determined by the bank-specific factors and a component determined by the market-specific factors, which is called pure spread. For each of the two components, we find substantial differences in the determinants of the spreads across different types of loan. While credit risk is important for long-term corporate and housing loans, inverse efficiency is significant in the segment of short-term loans. The contribution of market concentration to the pure spread is larger for household loans than for corporate loans.

The Determinants of the Efficiency of Microfinance Institutions in Africa

Over the past few decades, microfinance institutions have attracted the interest of governments and academics alike, given their unique nature of being financial institutions with a dual mission of promoting social development and reducing poverty. However, concerns have been raised about their effectiveness in achieving these goals while remaining financially sustainable. In this study, we attempt to examine the factors that have the greatest impact on the social, financial, and overall efficiency of microfinance institutions in African regions. We adopt a two-step approach: First, we assess the efficiency scores of 95 microfinance institutions in Africa between 2005 and 2018 using a data envelopment analysis (DEA) approach. We then regress their efficiency scores on a set of determinant variables, capturing the microfinance institutions’ characteristics. Our findings suggest that a majority of institutions prioritize profitability over social outreach. Furthermore, the panel data regression indicates that factors such as profitability, equity capitalization, types of loans, and low gross domestic product (GDP) have a positive influence on microfinance institutions’ efficiency. Conversely, variables including their risk portfolio, grants, microfinance institution status (Non-Governmental Organization (NGO), cooperative, etc.), operational area, political environment, and size exert a negative impact on efficiency. Through this study, we seek to enhance our understanding of microfinance institutions and to identify the factors that impact their operational efficiency, thereby reinforcing their crucial role in advancing financial inclusion, empowering marginalized communities, and fostering inclusive economic growth.

Providing Security for Flash Loan System Using Cryptocurrency Wallets Supported by XSalsa20 in a Blockchain Environment

The days of long lines at banks and piles of paperwork are long gone. The lending landscape has been completely transformed by digital loans, which provide a quick, easy, and frequently paperless transactions. A payee can apply for a digital loan anytime, anywhere. The entire lending procedure is accessible and efficient, but the availability of data on the Internet provides many risks and threats, where there are certain difficulties in the world of digital lending and data security, and privacy are major concerns. It is important to address the possibility of predatory lending practices that target weaker payees, especially with flash loans, which are considered a critical type of digital loan, as they add additional pressure to banks in terms of security because they return to the same block of the blockchain, and the possibility of tampering with them is considered great. Therefore, we have developed a security protocol based on the principle of digital cryptocurrency wallets: these digital wallets are protected by our use of the Xsalsa20 algorithm. It has high specifications and is enhanced with the usage of the Crow search algorithm, which guarantees fast and efficient search results. After the analysis of the proposed system in the Tamarin Prover tool, we obtained proof of a lot of security properties like data authenticity, perfect forward secrecy, and many others, which constitute the matter that gives our system the power of security. Also, we obtained 0.6667 ms. as the rate of processing speed, 2990 ms. as the time required by the proposed system to repay loans after the conditions are met, and, finally, our proposed system has the power to present a flexible property by creating 29,700 loans every 3 s; by this, we obtained a system that is secure, authentic, fast, and flexible.

Spatial-temporal distribution of debt and delinquency of the elderly in Thailand: Perspectives from the National Credit Bureau data.

Household debt in Thailand has become a serious problem, particularly for the elderly, because they have less ability to pay debts compared to the working population. Therefore, better understanding of the elderly's debt and delinquency is crucial in policy formulation for the aged society. Previous works have focused on the elderly's debt, either at the macro or individual levels. Little is known about geographic differences at the regional level. Knowing where the elderly debt and delinquency tend to cluster could guide area-specific policies to tackle the elderly financial stability. This research aims to examine the spatio-temporal distribution of the debt and delinquency of the near-elderly population (age 50-59) and the elderly (age 60 and above) using data from the National Credit Bureau of Thailand from 2008 to 2019. The analysis focuses on various types of loans. Spatial clusters are identified by Moran's I and Local Geary statistics. The results show that the pattern of elderly debt and delinquency generally follows the life cycle hypothesis, except for credit card and business-related loans. There exist spatial clusters and spatial differences in different types of loans, suggesting regional heterogeneities that require area-specific policy responses.

Enhancing Loan Prediction Accuracy: A Comparative Analysis of Machine Learning Algorithms with XAI Integration

The contemporary financial landscape necessitates loan recommendation systems that offer both accuracy and transparency. Conventional assessment methodologies often suffer from limitations in efficiency and transparency, leading to potential risks for both lenders and borrowers. This research proposes the development of a novel loan recommendation system that leverages the power of machine learning (ML) and Explainable Artificial Intelligence (XAI). The paper delves into the processes of data collection, preprocessing, model training, evaluation, and subsequent integration into a web application using the Flask framework. The employed datasets encompass a variety of loan types, with the study aiming to identify the most effective ML algorithms from a selection that includes XGBoost, CatBoost, Random Forest, Gradient Boosting, and Logistic Regression. To enhance the system's transparency, Explainable AI methods, such as LIME, are incorporated. The culmination of this research is a web application that facilitates personalized predictions regarding loan eligibility, accompanied by clear explanations. Index terms - Loan Recommendation System, Machine Learning, Explainable AI, XGBoost, CatBoost, Random Forest, Gradient Boost, Logistic Regression,LIME.

PEER-TO-PEER LENDING (P2P) AS DISRUPTIVE, BUT COMPLEMENTARY IN COVID-19 EXOGENOUS SHOCK

The purpose of this study is to examine the effect of P2P lending on bank credit in each type/segment of banking credit consisting of working capital credit, investment credit, and consumer credit in the period before and during the occurrence of the Covid-19 exogenous shock. Examining the effect of P2P lending on various types of bank loans is important because there is no conclusive evidence of whether P2P lending substitutes or complements various conventional bank loans. The Covid-19 pandemic impairs the income of many people and accelerates the use of digital technology in most daily activities including banking. Due to economic contraction during the outbreak, the government requires banks to relax the loan covenants. Therefore, P2P lending that provides flexibility might complement bank loans during the Covid-19 pandemic. The test in this study uses panel regression and is carried out by separating the period before (July 2019–March 2020), and during (July 2020–March 2021) the Covid-19 pandemic. The results show that P2P lending was disruptive for bank loans before the pandemic and turned to be complementary during the pandemic, it might be due to P2P lending flexibility complementing the bank credit relaxation during the pandemic.

Automated Social Media Text Clustering Based on Financial Ontologies

Social media networks provide an aggregation of news and content, allowing users to share and discuss topics of greatest interest to them. Users can enrich the news by providing context and opinions that are useful to other users. Understanding topics of interest sheds light on the collective thinking of a group of individuals and offers important insights for exploring a given field. Among the fields of interest on social media networks, finance stands out. Automatically identifying and organizing the main issues that users discuss can be useful for multiple purposes, e.g., identifying the preferred types of loans could be useful for refining targeted advertising. Our work aims to identify and organize the topics discussed on a social media network that are related to the financial sector. For this, we propose an approach that consists of analyzing posts from Reddit communities oriented to finance. First, posts were gathered and cleaned to remove punctuation, links, and images. Then, textual similarity was computed to match posts with classes from dedicated ontologies designed for the financial sector. Finally, the populated ontology was analyzed to identify clusters of concepts. The results showed that the proposed approach and corresponding tool can summarize topics from a large number of Reddit posts using the identified classes. Over 70% of posts were linked to ontologies when considering both posts and comments, which shows that the automatic support given to posts related to financial concepts had a high degree of success.

A Study on Agricultural Loans offered by NABARD to Farmers

This study delves into the comprehensive landscape of agricultural loans disbursed by the National Bank for Agriculture and Rural Development (NABARD) to farmers in India. The research scrutinizes the varied purposes for which these loans are extended, encompassing crop cultivation, animal husbandry, dairy farming, poultry, fisheries, and agro-processing. Emphasizing the different loan types – short-term, medium-term, and long-term – the investigation explores the interest rates associated with each category and evaluates the role of government subsidies in enhancing affordability. Additionally, the study investigates the credit delivery mechanism facilitated by NABARD through cooperative banks, regional rural banks, and commercial banks, ensuring an inclusive approach to reach farmers across diverse strata. The research underscores the technological impetus provided by NABARD, encouraging farmers to adopt modern agricultural practices and technologies. Special attention is given to risk mitigation measures, including crop insurance, designed to shield farmers from losses arising due to unforeseen circumstances. Keywords: NABARD, Agricultural Loans, Farmer Financing, Credit Delivery, Government Subsidies, Rural Development, Risk Mitigation, Financial Inclusion, Technological Adoption, Indian Agriculture.

Examining payday loan utilization among households with mainstream credit access

PurposeThis study aims to gain insight into the motivations behind the decision to use high-cost payday loans by households who possess mainstream credit and to determine whether this behavior has changed over time.Design/methodology/approachUsing data from Statistics Canada’s Surveys of Financial Security, probit models are used to examine the sociodemographic and financial indicators associated with payday loan use.FindingsThe analysis uncovers the sociodemographic and financial characteristics of payday loan-user households with access to lower-cost short-term loans. The findings indicate that the likelihood of payday loan use has risen over time. Additional analysis reveals that indicators of financial instability are positively associated with payday loan use among this group.Research limitations/implicationsThis research highlights the dichotomy of payday loan users and recommends policymakers tailor solutions to the specific needs of different types of payday loan users.Practical implicationsThis research highlights the distinguishing sociodemographic and financial characteristics of payday loan user households and recommends policymakers tailor solutions to the specific needs of different types of payday loan users.Originality/valueThis is the first study, to our knowledge, to focus analysis on payday loan use of those with access to lower-cost short-term credit alternatives in Canada and to include measures of financial instability in the analysis. This research is timely given the current economic environment of high interest rates and high levels of household debt.

Is This Time Different: How Are Banks Performing during the Recent Interest Rate Increases Compared to 2004–2006?

In 2022, the Federal Reserve began its latest monetary tightening cycle. Increases in interest rates are generally favorable for commercial bank net interest income (interest income minus interest expense). This relationship holds because many loan types have adjustable rates, and banks do not pass through all interest rate increases to depositors.

THE INFLUENCE OF FACTORS ON THE COSTS OF DIFFERENT TYPES OF LOANS IN BUSINESS OF AGRICULTURAL FARMS AND MEDIUM-SIZED AGRICULTURAL ENTERPRISES

The application of the use of different types of loans in the real organization of agricultural production in Republic of Serbia was the focus of the authors of the study. The goal of the research was to determine the existence of legality based on the analysis of 7 factors affecting the loans of agricultural farms and medium-sized agricultural enterprises, namely: limit, repayment delay, efficiency, average exchange rate, possibility of repayment, increase in production, currency, as well as the overall score of all analyzed factors as well as the total score. Using the t test (Table 1), the authors found that there are significant differences in the evaluation of all 7 analyzed factors (p<0.0005*). In addition, the authors determined that there are significant differences in the evaluation of the use of three types of loans (p<0.0005*) by agricultural farms and medium-sized agricultural enterprises in the Republic of Serbia.

Does bank-tax-interaction benefit small and medium manufacturer? An intertemporal signaling game

High cost of financing is a major obstacle to the growth of small and medium enterprises (SMEs), with opaque operational information being an important factor. Recently, a novel type of bank loan, bank-tax-interaction (BTI), which requires SMEs to share their previous tax information with the bank (e.g., via the tax administration), aims to lower SMEs’ financing costs by improving the information transparency. We develop a two-period intertemporal signaling game in which market demands are uncertain and correlated over the two periods. The manufacturer (SME) that is better informed about the market relies on bank loan for production, and the bank offers two types of bank loans: BTI and the traditional bank credit loan (BCL). Interestingly, we find that BTI does benefit the manufacturer when the market in the last period is low and the demand uncertainty is small. Notably, BTI does not lower the manufacturer’s financing cost, but reduces the operational inefficiency caused by the manufacturer distorting the amount of the bank loan to convey market information to the bank under BCL. Moreover, the impact of the correlation between the markets in the two periods may be non-monotonic on the manufacturer’s total profit, but monotonic on the bank’s total profit. Our findings shed light on the underlying mechanism by which BTI benefits small and medium manufacturers and provide insights into the operations of small and medium manufacturers and banks.

Loan Recovery in Maimana Islamic Investment and Finance Cooperative Microfinance Institution

MIIFC is one of the financial institutions operating in financial sector in Faryab province of Afghanistan. One of the most important problems of financial institutions is the recovery of the loans from the borrowers. The purpose of this study is to find the determinants of loan recovery in MIIFC micro finance institution. The statistical population of this research is the borrowers of MIIFC micro finance institution, the sample size is 300 and the stratified random sampling technique was employed. The study used both descriptive and inferential statistic, the quantitative method has been analysed by descriptive statistic with statistical package SPSS (24) and empirical analysis is conducted by using binary logistic regression model to stablish of all explanatory variables. The results show that from these variables, only economic and political situation, number of loans taken, penalty of delay, gender and debt guarantee have a significant relationship with loan repayment. The marital status, education level, age, monthly expenditure, loan utilization, literacy, income-increasing debt, relative location, type of loan, group loan, amount of repayment, repayment period, interest rate on the loan, number of families, loan utilization training and pre-loan purpose have no relationship with loan recovery.

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

Performance and Assets and Liabilities Management in the U.S. Credit Union

Abstract Our main research objective is to study the influence of different decisions inherent to allocating assets, and to the weights given to some types of loans on the profitability of credit unions. Only few studies having been carried out on these financial institutions and on their asset portfolio structural change. Another objective is to analyse the influence of increasing deposits, as part of liabilities, on their financial performance. In order to reach our research objectives, we carried out statistical analyses and panel regressions by using biannual data from a large sample of credit unions in the United States. In fact, we analyzed the influence of the choices of allocating some assets and liabilities, represented by ratios, on the profit of credit unions in the United States for 20 years, represented by the return on assets. The results of our analysis enable us to conclude that attracting more deposits would ensure better profitability for these credit unions. As regards to loan types, the increase of the first mortgage loans weight is a profitable strategy. Our research add value to the field of financial institutions management, since most studies concern banks profitability and cannot be generalized to credit unions. Keywords: Credit unions, Credit unions performance, Credit unions asset portfolio structure, Credit union deposits, Assets and liabilities management in banking industry, First mortgage loan.

The impact of the forestland‐tenure disputes on the new type of forestry operating entity's long‐term investment: The intermediary effects on credit constraints

AbstractIn the context of the state's proposal to accelerate the development of new type of forestry operating entities in rural area, we provide an analysis of how forestland‐tenure disputes affect the long‐term investment behavior through credit constraints based on the perspective of forestland‐tenure disputes. Based on the survey data of 485 new type of forestry operating entities in nine provinces across China, the empirical analysis is conducted using the Tobit model and mediating effect model, while paying attention to the heterogeneity of management scale and different entity types on the impact of new type of forestry operating entity's long‐term investment behavior. The conclusions are as follows: both forestland‐tenure disputes and dispute areas have a significant negative impact on the new type of forestry operating entity's long‐term investment. In addition, forestland‐tenure disputes not only have a direct negative impact on the long‐term investment but also have an indirect negative impact on the long‐term investment by constraining the new type of forestry operating entity's bank loan and expanding the loan gap. It is suggested to improve the forestland trading market, regulate the order of trading, and implement the policy of forest tenure mortgage to provide stable policy guarantee and external conditions for fully activating the vitality of forestland management.