Bank switching of US small businesses: new methods and evidence

Despite being informationally opaque, small firms often switch from their primary financial institution to transactional lenders, with the relationship banking theory invoking the holdup problem as a culprit explanation. Using US evidence and an estimation strategy that overcomes traditional shortcomings in small business research, our study captures the determinants and, for the first time, the ex post effects of the switching decision. We find that switching is less likely when the primary financial institution is a nearby bank associated with quality services and connected to the firm via other business or social relationships. Small firms become more loyal as they grow in size and pursue nonmortgage credit. Outside the primary relationship, both loan approval and borrowing cost are adversely impacted, however loan maturities are longer. Moreover, the likelihood of pledging collateral remains unaffected, provided that the type of collateral is least sensitive to the borrower’s information environment. Jointly, our findings describe a trade-off inconsistent with the holdup problem, and an opportunity for banks to enhance customer loyalty by improving aspects of the relationship unrelated to the terms of credit.

A profile of nontraditional agricultural real estate lender activity in the secondary market

PurposeThis paper uses novel data from a secondary market to assess how loans from nontraditional agricultural real estate lenders (NARELs) differ from traditional sources. Over $2 billion in loans from these entities were purchased by the secondary market between 2011 and 2020, but a lack of data has prevented a robust understanding of how these institutions operate.Design/methodology/approachThe authors review loans from nontraditional lenders through their lifecycle in the secondary market from application to purchase and performance.FindingsThis paper finds no observable differences between nontraditional and traditional volumes with regards to borrower credit characteristics, loan approval rates, interest margins and loan performance. It finds significant differences between loan volumes and variable rate product use.Originality/valueThis is the first paper to use internal lender data to review nontraditional agricultural real estate loans and is the first analysis of nontraditional agricultural volumes in the secondary market.

DETERMINANT FACTORS INFLUENCING HOUSING AFFORDABILITY AMONG BUMIPUTERA YOUTHS IN KLANG

Housing affordability issues arise when the household income is insufficient to cover the expenses of owning a house due to high housing market prices. This significantly impacts potential buyers, especially members of the youth generation who have just embarked on their careers. This study contributes to the empirical studies related to the monetary and non-monetary factors that influence the affordability of housing for Bumiputera youths in Klang. Primary data was gathered from 382 respondents using purposive stratified sampling. The findings indicate that seven main factors strongly influence housing affordability for Bumiputera youths: household income, housing price, loan approval, household expenditure, type of property, number of working households and location. Thus, the findings of this study will contribute to policy decisions, assessments and practices related to housing affordability among Bumiputera youths and support the implementation of the government policy to ensure that at least 75% of Bumiputera households are able to own residential property.

Qualitative Study in Identifying Factors Affecting the Behavior of Muslim Generation Y Towards Islamic Home Financing Products in Malaysia

House is the most important basic need for the human survival, however many individuals especially those who are categorised in the category of generation Y still do not acquire a house due to various factors. It is quite a normal practice for most of home-buyers in Malaysia to purchase a house through banking institutions. However, as a Muslim, it is an obligation to purchase and acquire a house through Islamic financial institutions (IFIs) as it is accordance to the Shariah principle. The objective of the study is to qualitatively identify factors affecting the behavior of Muslims generation Y in Malaysia towards Islamic home financing products. Apparently, it is found that religious belief, profit rate, offer and promotion, and fast service (loan approval) are factors in affecting Muslims generation Y in choosing Islamic home financing products. Afterwards, the study proposed to integrate the findings (identified factors) with the theory of Attitude-Behavior-Context (ABC). The study findings are expected to contribute significantly to the theory, methodology, and empirical practices.

Lending standards, productivity, and credit crunches

We propose a macroeconomic model in which adverse selection in investment amplifies macroeconomic fluctuations, in line with the prominent role played by the credit crunch during the financial crisis. Endogenous lending standards emerge due to an informational asymmetry between borrowers and lenders about the riskiness of borrowers. By using loan approval probability as a screening device, banks ration credit following increases in lending risk, generating large endogenous movements in TFP, explaining why productivity often falls during crises. Furthermore, the mechanism implies that financial instability is heightened when interest rates are low.

The Impact of Relationship Lending on Bank Loan Process for Korean SMEs

We investigate the effects of the bank-firm relationships on the decision making process regarding loan application, loan approval, and loan interest rate. To do this, we use data from 2016, and 2017 Surveys of Korea Small Business Finance conducted by Industrial Bank of Korea. We found that a more intense bank-firm relationship increases the likelihood of loan approval. Also, SMEs borrowing from lower number of banks and with more concentrated loans in main bank seem to obtain credit from main bank at lower interest rate than others. But applying for a loan is not related to the bank-firm relationship. This findings suggest that a close bank-firm relationship can reduce information asymmetry problem and alleviate SMEs’ credit constraint. Also bank-firm relationships seem to be important in determining the loan interest rate. As a relsult, our findings support that relationship lending has a beneficial effect on the supply side of the Korean SME credit market.

Customer Loan Approval Prediction Using Logistic Regression

Banking Sector contains loan where it is a process of lending or borrowing a sum of money by one or more individuals, organizations, etc. from Banks. The Person who lends that money from respective financier incurs a debt, and he is responsible to pay back the money with the Interest decided by Bank within a certain period. Generally what Bank’s look into before applying for a loan is Credit History, Credit loss and Income of Applicant. So basically,loans play a major role regarding Income for Bank. Due to rapid urban development people who are applying for loans got increased rapidly. Therefore, finding the applicant to whom loan can be approved become a complexed process. In this paper, we want to predict the loan eligibility based on details of the customer. Fields that required are Matrimonial Status, Income, Education, Loan Amount, Credit History and other income sources of Applicant dependants. To predict the status, we will use Logistic Regression to spot the eligible applicants so bank will engage with them for granting loans to those people who can payback in a given time.

Fair value accounting from the users’ perspective: an experiment on how financial analysts rely on fair value estimates in their decisions

Purpose The current paper aims to understand whether fair value accounting (FVA) affects analysts’ loan approval decisions and default risk judgments. Design/methodology/approach This study focusses on three issues: unrealized gain or loss resulting from FV measurement recognized in other comprehensive income (OCI), recognition of assets at FV or historical cost and the disclosure or non-disclosure of the FV of collateral assets. It uses an experiment carried out with a sample of 29 CFA analysts. Findings The results show that all three issues have a significant effect on analysts’ judgment and decision-making in processing FV estimates. Originality/value The paper extends knowledge on how financial analysts perceive FV estimates and disclosure and may help the accounting standard boards assess the challenges facing analysts when they apply professional judgments in interpreting FV measurements and disclosures. Moreover, it offers fresh views to the debate on the decision usefulness of FVA, particularly relevant in the post-implementation review of IFRS 13.

Survey on Prediction of Loan Approval Using Machine Learning Techniques

The enhancement in the banking sector lots of people are applying for bank loans but the bank has its limited assets which it has to grant to limited people only, so finding out to whom the loan can be granted which will be a safer option for the bank is a typical process. So in this paper we try to reduce this risk factor behind selecting the safe person so as to save lots of bank efforts and assets. This is done by mining the Big Data of the previous records of the people to whom the loan was granted before and on the basis of these records/experiences the machine was trained using the machine learning model which give the most accurate result. The main objective of this paper is to predict whether assigning the loan to particular person will be safe or not. This paper is divided into four sections (i)Data Collection (ii) Comparison of machine learning models on collected data (iii) Training of system on most promising model (iv) Testing.