Search results

The authors estimate the determinants of the value of purchases of semi-durable goods using permanent and transitory income, and the demographic characteristics of customers. The purpose is to identify whether individuals face remaining liquidity constraints, and how this friction affects their purchases.

This study uses anonymized data of 516,525 credit card holders, with more than 7,501,065 records of purchases between 2010 and 2015. The authors decompose the income of individuals into permanent and transitory components to test the prevalence of the life cycle–permanent income hypothesis (LC–PIH). Determinants of the value of purchases for constrained and unconstrained consumers are estimated, considering the period in which individual characteristics are valid, the decisions not to make purchases in some months, and the potential endogeneity of the interest rate and the transitory component of income.

The authors present evidence of liquidity constraints for individuals who have used a high percentage of the credit limit on their cards. For these restricted customers, the value of purchases is inelastic to the interest rate, whereas the response is sizable for customers who are less restricted. The restricted customers increase the value of purchases when faced with increases in their credit limit. The elasticity of the value of purchases of semi-durable goods to permanent income is less than that for transitory income; regardless of the constraints, this still supports the LC–PIH.

This credit card is targeted at low- and middle-income individuals in Bogotá. Although the results might be considered as indicative of the behavior of those with similar characteristics in Colombia, the authors regard this work as the study of a particular case. A limitation of this work is that the authors do not have alternative sources of credit at an individual level.

The broad credit channel of monetary policy does not apply to the restricted customers. This should be considered not only by the monetary authority, to understand the true extent of this policy, but also by the financial institutions that use this business model. The monetary authority should be cautious not to overreact when intervening in the money market to try to prompt an adequate consumer response.

Financial institutions have the policy of modifying the credit limits of their customers' credit cards which affects the well-being of restricted customers. Given that the card is aimed at low and middle income individuals, the credit limits of customers who use a high percentage of their credit limit might be increased.

This is the first paper to study liquidity restrictions with a retail credit card in Colombia and Latin America using information on customers' characteristics. The results are highly relevant for the implementation of monetary policy.

Under the background of low consumer financial knowledge and accumulated credit card liabilities, this study investigates the relationship between financial knowledge and responsible credit card behavior using data from the 2019 China Household Finance Survey (CHFS). From the perspective of consumer economic well-being, this study defines accruing credit card debt to buy houses and cars when loans with lower interest rates are available as irresponsible credit card behavior.

This study uses probit regressions to examine the association between financial knowledge and responsible credit card behavior because the dependent variable is a dummy variable. To alleviate endogeneity problems, this study uses instrument variables and Heckman’s two-step estimation. Furthermore, to explore the potential mediators in this process, this study follows the stepwise regression method. Finally, this study introduces interaction terms to examine whether this association differs in different groups.

The results indicate that financial knowledge is conducive to increasing the probability of responsible credit card behavior. Mediating analyses reveal that the roles of financial knowledge occur by increasing the degree of concern for financial and economic information and the propensity to plan. Moderating analyses show that the effects of financial knowledge on responsible credit card behavior are stronger among risk-averse consumers and in regions with favorable digital access.

This study measures responsible credit card behavior from the perspective of the consumer’s well-being, which enriches practical implications for consumer finance. Furthermore, this study explores the potential mediators influencing the process of financial knowledge that affects responsible credit card behavior and identifies moderators to conduct heterogeneous analyses, which helps comprehensively understand the nexus between financial knowledge and credit card behavior. By achieving these contributions, this study helps to curb the adverse effects of irresponsible credit card behavior on consumers’ well-being and the economic system and helps policymakers promote financial knowledge to fully prevent irresponsible credit card behavior.

This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

This study aims to establish that the relationship between the risky indebtedness behavior (RIB) of consumers and their attitude toward adopting buy-now-pay-later (BNPL) is not immediate but is mediated through impulse buying. Moreover, it explores how perceived risk moderates the association between the attitude to adopt BNPL and its adoption intention.

This study used the existing theoretical and empirical evidence to propose a model and validated it using the data collected from 339 young shoppers in India. Analysis of data is conducted using partial least squares structural equation modeling.

The study results show that consumers’ RIB is not directly related to their attitude toward BNPL. However, impulse buying fully mediates this relationship, influencing the attitude toward BNPL. Impulse buying and attitude serially mediate the relationship between RIB and BNPL adoption intention. Further, in the context of BNPL, perceived risk strengthens the attitude-intention gap.

This study advises policymakers and BNPL providers to carefully assess users’ creditworthiness to prevent those already in debt from entering into a detrimental loop.

This study provides novel perspectives on consumer’s RIB and BNPL within the Indian context. The study additionally identifies the mediating influence of impulse buying and the moderating effect of perceived risk on BNPL adoption intention.

This paper aims to understand if buy-now-pay-later (BNPL) services, a digital type of credit that targets young consumers, acts as a protective or a risk factor for food insecurity among young consumers in Australia.

The study uses survey data from a representative sample of young consumers aged 18–24 from all internal states and territories in Australia. Propensity score matching is used to test two hypotheses: BNPL drives young consumers to food insecurity, and food insecurity leads young consumers to use BNPL.

There is evidence that BNPL use is driving young Australian consumers to experience food insecurity, but there is no evidence of food insecurity driving the use of BNPL services.

The evidence of BNPL driving young consumers to experience food insecurity calls for the adoption of practices and stronger regulation to ensure that young users from being overindebted.

Although the link with more traditional forms of credit (such as personal loans) and consumer wellbeing has been explored more broadly, this project is the first attempt to have causal evidence of the link between BNPL and food insecurity in a high-income country, to the best of the authors’ knowledge. This evidence helps to fill the gap about the protective or risky nature of this type of digital financial product, as experienced by young Australians.

Consumer culture is promoting immediate gratification, and the rise of digital financial services is increasing the risk of indebtedness while debt reduces well-being and affects mental health. The authors assess the effects of consumer information provision, debt literacy, chronic debt and attitudes toward debt on the intent to purchase on credit.

An online survey including an experiment with a credit offer vignette was conducted in a representative sample of Estonia (n = 1204). Treatment conditions depicted either the total cost and duration of the credit agreement or the annual percentage rate.

Receiving modified information resulted in a 26 to 30 percentage points decrease in propensity to purchase on credit. Purchasing on credit was associated with attitudes towards credit and chronic debt, but not with debt literacy.

The findings reveal large effects of information provision and highlight the limited effects of debt literacy on credit decisions. Limitations may emerge from differences in financial regulation across countries.

The authors' results highlight the importance of applying behavioural insights in consumer credit information provision, both in the financial sector and policy. Testing the messages allows having evidence-based solutions that promote responsible purchasing on credit.

The findings call for changes in credit information provision requirements. Their effect is significantly larger compared to the literature, emphasizing the role of credit information provision in less regulated online markets.

The literature review stated that financial inclusion (FI) influences economic growth through different channels. Hence, this paper aims to investigate the underlying process of FI in Egypt theoretically, and to derive some policy implications for promoting the process and achieving more improvement in different financial and economic aspects, that is basically through discussing the opinions of FI's main stockholders in Egypt.

The analysis used secondary data from the Global Findex and FAS Database, namely, automated teller machines, outstanding deposits and loans with commercial banks, debit and credit cards ownership. The research particularly used scientific methods as method of deduction, methods of graphical and tabular representation of data, comparative analysis and synthesis of partial knowledge. The paper is also based on a descriptive approach in addition to in-depth interviews with the main stakeholders of the financial inclusion process in Egypt.

The analyzed results of interviews revealed that new FI vision should have a deep understanding of the financial lives of the poor and low-income groups, including how they acquire, manage and use their money. However, the impact is becoming more prominent for the efficiency of the banking system and hence economic growth rather a regulatory and sound institutional framework enhances it. This finding supported the fact that Egypt can design an appropriate FI strategy, but the main challenge is how to implement it with the required speed and outreach capacity, especially in underprivileged communities.

The result of this study has interesting implications for Egypt's ability to attain effective FI initiatives that promote sound financial choices and behavior which in turn help to stimulate financial and economic growth.

The study contributes to the literature by assessing the FI level in Egypt, its implications and how it should be enhanced for better performance and results in the future. It addresses the deep fact of this process through inclusive surveys and interviews that help in determining the road ahead.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

Perceived risk and benefits have been proposed as crucial elements in consumers’ technology adoption intention. Therefore, this study aims to use the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, with perceived risks and benefits, to explore how they affect consumers’ Buy-Now-Pay-Later (BNPL) behavioural intention.

An online survey was conducted among 537 users of BNPL. Partial least square structural equation modelling analysis was performed to examine the hypothesized relationships.

The study found that perceived benefits, performance expectancy, effort expectancy, habit and social influence increase consumers’ behavioural intention towards BNPL. In contrast, perceived risk reduces the consumer’s intention to use. Additionally, the study revealed that consumers’ intention towards BNPL services positively affects their usage.

The lack of information makes consumers hesitant to use BNPL. Therefore, marketers should optimize facilitating conditions, such as user-friendly interfaces, accessible resources and efficient customer support, which should be the business strategy of BNPL service providers to ensure a seamless user experience.

The research empirically investigates the effect of perceived benefits on consumer behavioural intention. This contribution is crucial because while there was speculation about benefits as a driving force to consumers’ adoption intention, there was a lack of sufficient empirical evidence to support it.