Types Of Loans Research Articles

Značaj utvrđivanja efikasnosti poslovanja poljoprivrednih gazdinstava u odnosu na korišćenje vrste kredita u poljoprivredi, primer Republike Srbije

The organization of agricultural production in countries such as the Republic of Serbia should be as close as possible to optimality. This can be achieved in different ways. One of the ways to improve the success and efficiency of business should be seen in the search for the most favorable form of obtaining loans from commercial banks. The paper highlights the importance of analyzing three types of loans, namely: a loan for refinancing intended for agriculture, an investment loan intended for agriculture and a loan for working capital intended for agriculture from the perspective of the efficiency of agricultural operations. A Pearson correlation analysis was performed for the observation period 2021-2022. The main conclusion is that there is a connection between the efficiency of agricultural operations with all three forms of taking loans by agricultural farms on a sample of N =149, that is, the obtained results confirmed this (p<.05). In addition, the study points to the existence of another conclusion, i.e. that the costs related to the taken loans in the observed period have an increase, but they do not have such an impact as the analyzed three forms of loans taken by agricultural holdings, because their impact is in the interval of 0.067 for 2021 to 0.070 in 2022.

The Effects of Government Policies on Agriculture in Indonesia

The content of this research compares the effect of two types of agricultural sector low-interest loans from the government in combination with human development index variables on Indonesia's gross regional domestic product. The government seeks to develop the agricultural sector through various strategies, one of which is the existence of fiscal policies in the form of subsidies. One policy that has been implemented is the interest subsidy for Food and Energy Security Credit (KKPE) and Soft Loans Credit for Agriculture (KUR). KKPE ran from 2008 to 2015. Since 2016, the KKPE policy has been terminated, and all credit is directed through the Soft Loans Credit. This study aims to analyze the effect of these two types of subsidized credit, namely KKPE and KUR, on each province's Gross Regional Domestic Product in Indonesia. The analysis was conducted on data from the top 20 provinces with Indonesia's highest KKPE and KUR realization. The analysis concluded that KKPE partially had a positive effect on GRDP at all quantile levels, and HDI had a positive effect on GRDP only at quantiles 0.15 to 0.35 and 0.80 to 0.95. Another case is with KUR, which does not have a significant effect partially, but with HDI, it has a significant effect on GRDP. Furthermore, KUR and HDI are superior in explaining GRDP compared to KKPE and HDI.

Personal factors as determinants of the risk rating for SME investment

ABSTRACT What variables indicate whether a small or medium enterprise (SME) applying for financing from a development bank is a good loan candidate? Structural equation modeling applied to a set of variables can provide the necessary insights. This paper analyzes 407 SMEs that applied for development loans in Pichincha Province, Ecuador. Rather than specific economic/financial quantitative variables often used in credit scoring models, we employed qualitative variables to study creditworthiness. The structural equation methodology can verify whether a client is creditworthy based on company management, product characteristics, and contextual market aspects. Another key contribution is the finding that an entrepreneur's personal/professional traits are the primary determinant for granting this type of loan. The results have theoretical and practical implications that could enhance the limited empirical research in this field to date.

The effects of the EBA's stress testing framework on banks' lending

This paper investigates the impact of the European Banking Authority (EBA)'s supervisory stress tests on bank lending. Using a sample of 282 European banks over the period 2006–2018, we find that stress-tested banks experience higher credit risk and reduce lending for specific loan types. In particular, due to country heterogeneities, we find that the contraction in lending is more pronounced for stress-tested banks in the GIIPS region. Our results also suggest that the elevated credit risk of highly-exposed stress-tested banks can be a driving factor of a reduction in bank lending. Consequently, prudential measures requiring banks to hold higher capital buffers are justified to contain credit risk shocks.

고등교육 보편화에 따른 중국 학자금 대출 제도와 미국 연방 학자금 대출 제도 비교분석

[Purpose] This study aimed to comprehensively examine the current situation of Chinese student loan system in the context of the universalisation of higher education in China, and to make feasible recommendations for improvement based on a comparative analysis with the United States federal student loan system.
 [Methods] Using a comparative research method, this study provided a detailed analysis that outlines the critical differences between the student loan systems in China and the U.S. Pivotal points include access to information channels, required documentation, loan types, support scope, and repayment strategies. Data were collected from official national websites, policies, and a range of secondary data sources.
 [Results] The study showed that central governments in both China and the U.S. have played an important role in guiding the student loan system to promote educational equity. However, significant gaps and limitations have been identified in Chinese student loans. These include the fragmentation of information channels and the complexity of the application process; the uniformity of loan types; the narrow scope of support; and the unity of repayment options. In contrast, the U.S. has a more mature and detailed system with features such as specialised student loan administration and servicing agencies, the convenience of online services, the diversity of loan types, the breadth of support and the flexibility of repayment plans.
 [Conclusion] This study suggested that China should improve the efficiency of its student loan system by borrowing from the U.S. federal student loan system. Specific strategies include building an efficient student loan platform that integrates online and offline services; expanding the types and amounts of loans and implementing a total loan limit model; and promoting the implementation of Income-Driven Repayment Plans to meet the needs of more students.

PERLINDUNGAN HUKUM TERHADAP DEBITUR PADA LAYANAN PINJAMAN UANG BERBASIS FINANSIAL TEKNOLOGI DALAM PERSPEKTIF HUKUM PERDATA

This research is motivated by the existence of problems in society that are difficult to solve. On the one hand, the community's economic downturn has resulted in them looking at other types of illegal loans. On the other hand, fintech actors take advantage of the situation and conditions of society so that they are trapped by debts and receivables with abnormal interest. Collection methods that are beyond humane limits are disturbing the people who use these loans. Therefore, the author must carry out further studies regarding legal protection for debtors who use illegal online money lending services. The aim of this research is to analyze and examine legal protection for debtors in illegal online money lending services. To analyze and study the legal settlement process undertaken by debtors in Illegal Online money lending services. The method used is normative juridical. The normative juridical approach method is a legal research technique that involves examining library materials (secondary data) using a statutory approach, namely an approach that uses statutory regulations which are useful as a research medium. Apart from that, it uses a conceptual approach, which requires legal concepts as a starting point for research into current legal problems.

Gender Copy in Slavic internationalisms

Abstract In replica languages attesting to grammatical gender, all loan nouns are obligatorily assigned to gender classes. If two languages with grammatical gender come into contact, loan nouns can either retain their original gender (i.e. Gender Copy) or obtain another gender in the replica language (i.e. gender change). In the recent research, it was mostly assumed that the assignment process occurs almost exceptionally according to the internal assignment rules of the replica language. The role of grammatical gender of the words in the donor language was either neglected generally or bound to special sociolinguistic circumstances. The empirical data show, however, that grammatical gender is much more often copied together with loan nouns than assumed until now. In my empirical study, I analyze the processes of gender assignment in a special type of loan words – internationalisms – in the standard varieties of Slavic languages. It is shown that Gender Copy is the most frequent strategy for this type of loans in these genealogically closely related and typologically similar languages.

Beyond origination charges: The pass-through of GSE upfront fee adjustments in 2022

In 2022, a policy increased mortgage guarantee fees for government-sponsored enterprises (GSE) purchases in high-cost areas. Given that the adjustment is specific to selected loan types, we employ a difference-in-differences approach to evaluate the shifts in origination charges for affected mortgages relative to unaffected ones. We find that the increases in origination charges only encapsulate a minor fraction of the escalated costs faced by lenders. Instead, lenders appear to adapt by elevating the interest rates. This research illuminates an unforeseen response from lenders and underscores the necessity for nuanced strategies in housing finance policy formulation.

Perbandingan Kinerja K-Nearest Neighbors dan Naive Bayes Untuk Klasifikasi Perilaku Nasabah Pada Pembayaran Kredit Bank

:Credit customers are people who use banking services or other financial services. to use bank money in its business activities, so it expects that the bank's credit can meet business capital needs. To reach information to increase profits and reduce company losses, we need a method that can provide knowledge to support the company's data. Research data can be obtained from processing classification data from credit customer data that are categorized as potential or not potential in the next credit grant. Data processing can be done using machine learning, namely classification techniques. This technique will produce a predictive churn model to determine which customer categories belong to a group. potential smooth or jammed. The Naive Bayes method was chosen because it can produce maximum accuracy with little training data. Meanwhile, the K-Nearest Neighbor method was chosen because it is robust against noise data. The performance of the two methods will be compared, so that it can be seen which method is better in classifying documents. The results obtained show that the Naive Bayes method has better performance with an accuracy rate of 70%, while the K-Nearest Neighbor method has a fairly low accuracy rate of 40%. Thus, it can be seen the accuracy value displayed by applying the classification algorithm. K-Nears Neighbors and Naïve Bayes. Parameter category. which in this study are account numbers, names of debtors, collectibility in the categories: current, DPK (on special mention), substandard, doubtful, loss. Then clarified with a description of the type of loan, collectability of ADK (computer data archive), type of business.

Politeness matters: The role of polite languages in online peer-to-peer lending

Given the limited information for assessing borrowers in online peer-to-peer (P2P) lending, the textual content of loan requests has been recognized as a crucial factor influencing lenders' lending decisions. However, whether politeness, an important but largely neglected linguistic element in loan requests, is related to lenders' decisions remains underexplored. Drawing from signaling theory, this paper seeks to answer two important questions: (1) Is the use of polite language in loan requests related to lenders' decisions? (2) If so, for which types of borrowers or loans is politeness more beneficial? We test our theoretical framework using a sample of 127,044 loan requests from Renrendai, a leading online P2P lending platform in China. Our findings reveal a significant and positive relation between the use of polite language and the likelihood of successful funding. This positive relation is stronger for borrowers with higher credit ratings, higher education levels, as well as for loan requests with lower information richness and higher certainty in language. Our findings suggest that politeness functions as a costless signal that complements costly signals, reducing information asymmetry in P2P lending. This paper bridges the gap between the literature on the role of politeness in individual decision making and information asymmetry in financial markets, providing new insights into the role of language use in P2P lending.

Risk preference, payday loans and other alternative financial services

PurposeThe purpose of this paper is to examine how individual risk preference influences the borrowing of payday loans – a prevalent type of cash loan in the USA with exorbitantly high-interest rates. Additionally, this paper tests how risk preference determines other alternative financial services (AFS), including pawn shops, rent-to-own purchases, title loans, etc.Design/methodology/approachThe author applies Probit and Tobit regressions to test the relationship between individual risk preference and payday borrowing, based on the state-by-state survey data from National Financial Capability Study (NFCS) sponsored by Financial Industry Regulatory Authority (FINRA) Investor Education Foundation.FindingsIndividuals with higher risk tolerance are more likely to borrow payday loans and other AFS, after controlling for financial situation, financial literacy, overconfidence and demographic features.Originality/valueThis paper is the first to study risk preference as an explanation to the high cost and widely used payday loan services in the United States of America. This study provides evidence that these cash loans are determined by inherent human characteristics. The finding provides new insight for the policymakers and regulators in the consumer debt market.

The dark side of bank taxes

We investigate the impact of a new bank tax in Poland on bank lending behavior. We find that banks respond to the tax by tightening credit supply and increasing the costs of credit to the real sector. However, the responses vary across loan segments. In line with search-for-yield behavior, the tax motivates banks to shift their allocations of household credit from low-margin and relatively safe mortgage loans to higher-margin and riskier consumer loans. We find no evidence that financially weak banks are more incentivized to shift to riskier loan types. Moreover, firms that receive loans from banks more exposed to the tax experience a greater credit contraction.

Differentiated impact of spread determinants by personal loan category: Evidence from the Brazilian banking sector

The empirical literature on the determinants of banking spreads has considered banks as providers of one single product. According to this approach, the study of the effect of bank spreads determinants has assumed that this effect is uniform across the different types of loans offered by banks. The present study assesses the hypothesis that banking spreads attributes have a differentiated impact on spreads, according to the loan category. To this end, we adopt a dynamic model, estimated through System GMM based on a dataset of interest spreads charged on three categories of personal loans in Brazil. Our results support the hypothesis of differentiated impacts according to loan category, and are corroborated by a robustness check, carried out through Difference GMM estimation of the adopted model. Overall, these findings also suggest that regulators should observe the composition of banks’ loans portfolios when designing and implementing policies aiming at banking spread reduction.

Dynamic bank capital regulation in the presence of shadow banks

Regulated banks expand relative to shadow banks in recessions and when credit spreads are high, while regulated banks shrink relative to shadow banks in expansions and when credit spreads are low. Motivated by these facts, I build a quantitative general equilibrium model with endogenous risk taking to study how competitive interactions between regulated banks and shadow banks affect optimal dynamic capital requirements. Limited liability and deposit insurance can lead regulated banks to provide socially inefficient risky loans when the returns on safer loans decline. Competition for scarcer funding can further lower the net returns on safe loans, making it more attractive for regulated banks to exploit the shield of limited liability with risky loans. Higher capital requirements can reduce inefficient risk at the cost of lower liquidity provision and some migration of credit from regulated banks to shadow banks. Accounting for the interactions of regulated and shadow banks can change the magnitude and direction of the optimal response of capital requirements to shocks that drive the business cycle. Moreover, Basel-III style rules that differentiate between the type of bank loans are much better at mimicking the Ramsey optimal capital requirements than standard rules that aggregate loans. The performance of such dynamic rules can be further improved once they are combined with a small static capital buffer.

Digital finance and enterprise investment efficiency in China

This paper uses the panel data of Chinese listed enterprises from 2010 to 2019 to explore the relationship between digital finance (DF) and enterprise investment efficiency. The result of two-way fixed effects regression shows that the DF significantly improves enterprise investment efficiency. And the result is robust to different indicators of digital finance and possible endogenous biases. Further mechanism analyses find that the impact of DF on total debt was insignificant whereas it significantly changes financial composition which in turn affects the investment efficiency of enterprises. Specifically, the mediating effect of financial structure changes in both magnitude and direction with respect to the type of loans, and investment efficiency of under- and over-invested enterprises responses asymmetrically to the DF-induced financial structure adjustments. Overall, financial diversity decreases significantly with the inclusion of DF, which in turn improves enterprise investment efficiency. The results of this paper indicate that, in order to improve investment efficiency, the composition adjustment effect of DF should be further exerted with financing inclined to credit loans and guaranteed loans and guarding against excessive looseness of mortgage loans.

Optimal Loan Portfolio under Regulatory and Internal Constraints

The environment surrounding banks is becoming increasingly severe. Particularly, to prevent the next financial crisis, Basel III requires financial institutions to prepare higher levels of capitals by 1 January 2028, and the financial stability board (FSB) suggests the risk appetite framework (RAF) as their internal risk management. Hence, efficient usage of their own capitals for banks is more important than ever to improve profitability. Under such circumstances, this paper is the first to consider an optimization problem for a typical loan portfolio of international banks under comprehensive risk constraints with realistic profit margins and funding costs to achieve an efficient capital allocation. Concretely, after taking concentration risks on large individual obligors into account, we obtain a loan portfolio that attains the maximum profit under Basel regulatory capital and loan market constraints, as well as internal management constraints, namely, risk limits on business units and industrial sectors. Moreover, we separately calculate credit risk amounts of the internal constraints in terms of regulatory and economic capitals to compare the optimized profits. In addition, considering sharp increases in default probabilities of all obligors as in the global financial crisis, we perform a stress test on the optimization results to investigate the effects of changes in risk amounts and profits. As a result, we propose to unify risk constraints on the business units and industrial sectors by using credit risk amounts in terms of economic capitals.

Credit growth and current account balance

In this paper, we investigate the relationship between different loan types and the current account balance along with its sub-components. Our empirical results suggest that a rise in total loans inevitably leads to a deterioration in the current account balance. This relationship is preserved in the case of the goods trade balance, but it becomes statistically insignificant and disappears if the services trade balance is considered. When we examine different types of loans, our findings indicate that both consumer and corporate loans have sizeable and negative effect on both the current account and goods trade balances with the impact of consumer loans being much higher. We also report that only corporate loans have a significantly negative relationship with the services trade balance although the concurrent effect is rather small.

Loans Secured by Republican Brands from a Regional Banking Syndicate

The subject of the study is loans secured by republican brands from the regional banking syndicate of the Republic of Tatarstan. The object of the study is regional banks and key companies of the Republic of Tatarstan. The relevance of the study is due to the need to introduce promising types of loans, increase interest income and increase the competitiveness of regional banks; providing opportunities for regional companies to raise funds to finance their activities. The goal is to determine the possibility of granting syndicated loans secured by republican brands to the regional banking syndicate of Tatarstan. Information base — official data of the Bank of Russia, Rospatent, companies and banks. Methods of sampling, grouping, analysis, comparison, analogy, synthesis, generalization are used. The results are as follows. The concentration of functioning regional banks in the federal districts was determined as of December 20, 2021. As of October 1, 2021, an analysis of key indicators of banks registered in Tatarstan was carried out. The characteristics of transactions of pledge of exclusive rights to objects of intellectual property (IP on OIP) in Tatarstan for 2014–2021 are presented (pledgers, pledgees, the number and types of OIP pledged, the duration of each of the pledge agreements, the number and date of official state registration, the number of contracts). It can be concluded that the banks of Tatarstan have the opportunity to provide local companies with syndicated loans. Recommendations were given: 1) it was proposed to merge local banks of Tatarstan into a regional banking syndicate to provide syndicated loans against various types of collateral, including intellectual assets owned by leading companies in Tatarstan; 2) consider the possibility of using popular brands of companies operating in Tatarstan as collateral. A list of companies and their brands has been compiled, and characteristics of corporate brands have been given. The list of brands that can be pledged also includes the republican brands “Heritage of Tatarstan” and “Visit Tatarstan”; 3) the expected positive results of interaction for all participants of the regional banking syndicate are determined. Directions of research: assessment of the possibility of attracting banks from other Russian regions for interaction.

Fintech inputs, non-performing loans risk reduction and bank performance improvement

The function of Fintech is preventing and resolving financial risks, and the ability of small and medium-sized commercial banks to apply Fintech to resolve non-performing loan risks deserves attention. This paper uses as a sample the micro-survey data of 432 branches of the city commercial banks in Beijing from 2005 to 2022 and constructs an econometric model of the risk reduction effect of Fintech on non-performing loans.The findings are as follows.Firstly, Fintech inputs can significantly reduce the risk of non-performing loans. For every 1% increase in IT personnel inputs, software inputs, and hardware inputs, the non-performing loan ratio will reduce by 0.091%, 0.055%, and 0.024%, respectively. In other words, IT personnel inputs contribute the most to the reduction of non-performing loan risk, followed by software inputs.Fintech has a certain lag effect in alleviating the risk of non-performing loans in banks and tends to strengthen over time.Secondly, Fintech inputs has an indirect effect on banks' performance by reducing non-performing loan risk, And there is a positive feedback loop between Fintech inputs, non-performing loan risk mitigation, and improving performance. This effect is not significant in the current period but significant when lagged by three periods.Thirdly, Fintech inputs has a significant inhibitory effect on non-performing loans loans of concern and subprime. For every 1% increase in inputs in IT personnel, software, and hardware, concern will decrease by 0.263%, 0.358%, and 0.107%, respectively, while subprime will decrease by 0.115%, 0.216%, and 0.057%, respectively. Software and personnel inputs have a greater inhibitory effect on the above two types of loans than hardware inputs. Fourthly,mechanism analysis shows that data governance application, compliance enforcement, and internal control enforcement have a moderating effect on Fintech input's impact on banks' non-performing loan risk.

Mortgage Loan Costs: Magnitude and Drivers of Variation

This article uses national data disclosed as part of the Home Mortgage Disclosure Act (HMDA) to examine variations in loan costs based on type of loan, borrower, purpose (purchase, improvement, or refinance), and neighborhood characteristics. Loan costs are generally higher for nonconventional conforming loans with higher levels of credit risks (loans with higher combined loan-to-value, higher debt-to-income ratios, and for investment properties). This implies that product and borrower risk impact loan costs. However, borrower characteristics such as income and race/ethnicity are also associated with differences in loan costs even after controlling for loan characteristics, location, and lender fixed effects. Total loan costs are higher both in dollar terms and as a share of the loan amount for Black borrowers and Hispanic borrowers, and total loan costs represent a higher share of the loan amount for lower income borrowers. These disparities are larger in neighborhoods with higher levels of lender concentration and implicit racial bias. These findings suggest that in addition to access to mortgages and interest rates, loan costs can represent a barrier for access to homeownership with a disparate impact for Black and Hispanic borrowers, which contributes to perpetuate the homeownership gap.