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This paper aims to examine prospective graduate students' attitudes toward educational loan borrowing in an experimental setting.

Participants were randomly assigned to two treatment groups and one control group. Subjects in experimental group 1 received financial education: a short online course on the economic viability of getting a master's degree and how to finance it with a graduate student loan, while subjects in experimental group 2 received financial education along with information on the availability bias.

Relying on a control group in the assessment of financial literacy education intervention impacts, this research finds positive causal treatment effects on individuals’ attitudes toward debt-financed graduate education. In comparison to the control group, experimental subjects perceived the possibility of going into debt with a graduate loan to complete a master’s degree as less stressful and worrying.

This study has important educational policy implications to prevent students from stopping investing in human capital by perceiving educational loan debt as something stressful or worrying. The results can help potential (and current) grad students develop a feasible financial plan for graduate school by encouraging higher education institutions to implement educational loan information and financial education into university seminar courses for better graduate student loan decision-making.

Student attitudes toward debt have been analyzed in the context of higher education, but only a few researchers internationally have used an experimental design to study personal financial decision-making.

The framework of this paper is financial mathematics and, more specifically, the control of data fraud and manipulation with their subsequent economic effects, namely, in financial markets. The purpose of this paper is to calculate the global loss or gain, which supposes, for the borrower, a change of the interest rate while the contracted loan is in force or, in another case, the loan has finished.

The methodology used in this work has been, in the first place, a review of the existing literature on the topic of manipulability and abusiveness of the loan interest rates applied by banks; in the second place, the introduction of a mathematical-financial analysis to calculate the interests paid in excess; and, finally, the compilation of several sentences issued on the application of the so-called mortgage loan reference index (MLRI) to mortgage loans in Spain.

There are three main contributions in this paper. First, the calculation of the interests paid in excess in the amortization of mortgage loans referenced to an overvalued interest rate. Second, an empirical application shows the amount to be refunded to a Spanish consumer when amortizing his/her mortgage loan referenced to the MLRI instead of the Euro InterBank Offered Rate (EURIBOR). Third, consideration has been made to the effects and the possible solutions to the legal problems arising from this type of contract.

This research is a useful tool capable of implementing the financial calculation needed to find out overpaid interests in mortgage loans and to execute the sentences dealing with this topic. However, a limitation of this study is the lack of enough sentences on mortgage loans referenced to the MLRI to get some additional information about the number of borrowers affected by these legal sentences and the amount refunded by the financial institutions.

To the best of the authors’ knowledge, this is the first time that deviations in the payment of interests have been calculated when amortizing a mortgage.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

This paper examines how the macroeconomic environment affects the determinants of prepayment of mortgage loans from October 2004 to February 2020. For more accurate analysis, the authors define the timing of prepayment not only before the loan maturity but also at the time when 50% or more of the loan principal is repaid. The results show that, during the global financial crisis as well as the recent period of low interest rates, macroeconomic variables such as interest rate spreads and housing prices have a different effect compared to the normal situation. Also, significant explanatory variables, such as debt to income (DTI) ratio, loan amount ratio and poor credit score, have different effects depending on the macroenvironment. On the other hand, in all periods, the possibility of prepayment increases as comprehensive loan to value (CLTV) increases, and the younger the age, the shorter the loan maturity. The results suggest that, in the case of ultralong (40 years) mortgage loans recently introduced to support young people purchasing houses, the prepayment risk can be, at least partially, migrated by offsetting the increase in prepayment by young people and the decrease in prepayment due to long loan maturity. In addition, this study confirms that the accelerated time failure model compared to the logit model and COX proportional risk model has the potential to be more appropriate as a prepayment model for individual borrower analysis in terms of the explanatory power.

This paper aims to investigate whether loan officers' risk taking in credit decisions are associated with their personal financial risk preference and personality traits or solely with bank-contextual and loan-relevant factors.

An online survey administered in six large Swedish banks to 163 loan officers responsible for assessing credit risk and approval of loan applications. The loan officers rated their likelihood of approving fictitious loan applications from business companies.

The loan officers' credit risk taking is associated with bank-contextual factors, directly with perceived organizational credit risk norms and indirectly with self-confidence in assessing credit risks through attitude to credit risk taking. A direct association is also found with personal financial risk preference but not with personality traits.

Increased awareness of that loan officers' personal financial risk preference is associated with their credit risk taking in loan decisions but that the banks' risk policy has a stronger association. Banks' managements and boards should therefore assure that their credit risk policy is implemented, followed and being aligned with their performance incentives.

Increased awareness of that loan officers' credit risk taking is associated with personal financial risk preference but more strongly with the banks' risk policy that motivate banks' managements and boards to assure that their credit risk policy is implemented, followed and being aligned with their performance incentives.

The first study which directly compare the associations of loan officers' risk taking in credit approvals with personal risk preference and personality traits versus bank-contextual factors and loan-relevant information.

Using bank-level data over the 1994–2015 period, the authors aim to investigate the role of bank-specific factors on credit risk in Italy by considering two different groups of banks, namely, cooperative and non-cooperative (commercial and popular), in different local markets.

Relying on highly territorially disaggregated data at labour market areas’ level, the authors estimate the impact of the role of bank-specific factors on credit risk in Italy from the estimation of a fixed-effect estimator. Non-performing loans to total loans has been used as a proxy of credit risk; the bank-specific factors are as follows: growth of loans, reflecting credit policy; log of total assets, controlling for banks’ size; loans to total assets, reflecting the volume of credit market; equity to total assets, capturing the solvency of banks and reflecting their capital strength; return on assets, reflecting the profitability of banks; deposits to loans, reflecting the intermediation cost; cost of total assets, reflecting the banks’ efficiency or volume of intermediation cost.

The empirical findings suggest that regulatory credit policy, capitalisation, volume of credit and volume of intermediation costs are the main bank-specific factors affecting non-performing loans. Nevertheless, the present analysis suggests that the behaviour of cooperative banks’ behaviour seems to be in line with that of commercial rather than popular banks, casting doubts about the feasibility of their credit policies. It turns out that recent reforms involving popular and cooperative banks represent the first step toward the enhancement of the stability and efficiency of the Italian banking system. While the present study’s benchmark results are not particularly affected by the degree of competition in the banking sector and by banks’ size, it shows that both cooperative and non-cooperative banks have undertaken more prudent credit policies after the advent of the financial crisis and the introduction of the Basel regulation.

The relationship between bank-specific factors and credit risk has been analysed using a rich sample of cooperative, commercial and popular banks in Italy over the 1994–2015 period. The authors rely on labour market areas being sub-regional geographical areas where the bulk of the labour force lives and works. The contribution is motivated by the financial distress experienced after the 2008 financial crisis, which has significantly hit the Italian banking system and cooperative banks in particular.

This study aims to examine and compare the credit risk management (CRM) scenario of Islamic banks (IBs) and conventional banks (CBs) in Pakistan, keeping in view the phenomenal growth of Islamic banking and its future implications.

A sample of five CBs and four IBs was chosen out of the whole banking industry for the study. Secondary data obtained from the banks’ annual financial reports for 13 years, starting from 2004 to 2016, were analyzed. Multiple regression, correlation and descriptive analysis were used in the examination of the data.

The results show that loan quality (LQ) has a positive and significant impact on CRM for both IBs and CBs. Asset quality (AQ), on the other hand, has a negative impact on CRM in the case of IBs, but has a significantly positive relation with CRM in the case of CBs. The impact of 16 ratios measuring LQ and AQ have also been individually checked on CRM, by making use of a regression model using a dummy variable of financial crises for robust comparison among CBs and IBs. The model proved significant, and CRM performance of IBs was observed to be better than that of CBs. Moreover, the mean average value of financial ratios used as a measuring tool for these variables shows that the CRM performance of IBs operating in Pakistan was better than that of CBs over the period of the study.

The research findings are expected to facilitate bankers, investors, academics and policy makers to build a better understanding of CRM practices as adopted by CBs and IBs. The findings would be useful in formulating policy measures for the progress of the banking industry in Pakistan.

This research is unique in terms of its approach toward analyzing and comparing CRM performance of CBs and IBs. Such work has not been carried out before in the Pakistani banking industry.

The authors examined the impact of the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP) payments to United States agricultural producers on non-real estate agricultural loans.

The authors used quarterly, state-level commercial bank data from 2016–2020 to estimate dynamic panel models.

The authors found MFP and CFAP payments not associated with the percentage of non-real estate agricultural loans with payments over 90 days late. However, these payments associated with the percentage of non-real estate agricultural loans with payments between 30 and 89 days late. The available data utilized cannot consider when producers received the actual payment and what they specifically did with those funds.

The contribution of this study is for US policymakers and agricultural lenders. The findings could be helpful in designing and implementing future ad hoc payment programs and provide an understanding of potential shortcomings of the current safety net for agricultural producers in the Farm Bill. Additionally, findings can assist agricultural lenders in predicting the impact of ad hoc payments on their distressed loan portfolios.

The paper aims to disentangle the physiological credit risk from the credit risk coming from the inefficient screening and monitoring management process. The analysis is conducted on a sample of 338 Italian banks–56 joint-stock banks (SpA), 23 cooperative banks (Popolari) and 259 mutual banks (BCCs)–over the time period 2006–2017.

The authors use the maximum likelihood method to estimate the efficient frontier, as a set of best management credit practices, which minimises the credit risk defined on the basis of the level of loans granted, the technical structure of the loan portfolio (such as credit lines, mortgages, consumer loans and other technical loan categories) and the interest rate charges.

The empirical results show that the increase in non-performing loans (NPLs) is related both to the severe and protracted recession in Italy, which significantly reduced borrowers' capacity to service their debt, and to other factors, such as banks' lending monitoring policies with limited capacity to work-out defaulted loans.

The authors propose a new approach to the study of the performance of the credit process. With the stochastic frontier, the physiological credit risk, assumed by the bank according to its lending activity and management choices, is separated from the credit risk resulting from an inefficient management of the screening and monitoring process. In addition, the authors analyse the determinants of the excess of NPLs. This aspect is considered particularly original because the scientific contributions which consider the causes of NPLs have largely focused on the level of NPLs not considering the physiological part, linked to the structure of the bank's loan portfolio and its operational strategy and therefore not compressible and in any case not attributable to mismanagement or moral hazard.

To enhance the loan repayment performance of microfinance institutions (MFIs) in Pakistan, this study aims to analyze the direct impact of social capital and loan credit terms on loan repayment performance and microenterprises’ business performance while considering the mediating role of microenterprises’ business performance on the relationship between social capital, loan credit terms and loan repayment performance.

The analysis was conducted based on the data gathered via a questionnaire distributed to 316 microenterprises owners. The respondents were selected using the stratified sampling technique by dividing the target population into three influential groups of manufacturing, trading and services microenterprises. The reliability and validity of the constructs were established using (1) factor loading, (2) Cronbach’s alpha, (3) composite reliability, (4) average variance extracted, (5) the variance inflation factor, (6) the Fornell–Larcker criterion and (7) the heterotrait–monotrait ratio. The structural equation modeling technique was then applied, and the hypotheses were tested based on the structure model generated through bootstrapping by using partial least squares structural equation modeling.

The results confirm the direct impact of social capital and loan credit terms on microenterprises’ business performance and loan repayment performance. It also supports the mediating role of microenterprises’ business performance toward the relationship between social capital, loan credit terms and loan repayment performance while considering the direct impact of microenterprises’ business performance on loan repayment performance.

To date, the direct impact of social capital and loan credit terms on microenterprises’ business performance and loan repayment performance has been hardly investigated in the context of Pakistan. This study also examines the mediating role of microenterprises’ business performance toward social capital, loan credit terms and loan repayment performance. The findings will enable both MFIs and microenterprises to improve their business performance and loan repayment performance through enhanced social ties and the development of more flexible credit products that protect the borrowers’ interests and the interest of lenders.