Consumer Credit Research Articles

Improved Support Vector Machine Personal Credit Rating Model

Credit consumption has become the choice of more and more people. While the expansion of credit consumption brings convenience, the consequent problem of discredit brings incalculable loss to trust institutions, such as intentional arrears, malicious overdraft consumption, etc. to the trust in the operation of the huge losses caused. On the one hand, our country is unable to establish perfect personal credit record, customer credit information is difficult to share, access to relevant data is limited, personal credit system is not perfect, therefore, it is necessary to establish a perfect and automatic personal credit evaluation system, identify the personal credit risk scientifically, and realize the maximization of bank credit income. In the bank risk management, the main problem is how to measure and avoid the bank's financial risk, and personal credit assessment is the most difficult and important part. In this paper, we use the XGBOOST algorithm to sort the importance of features, and select the number of features and the specific features according to the relationship between the model accuracy and the number of features, then 80% of the data was taken into the traditional Support vector machine model as a training set and tested with the remaining data with low accuracy, so that, in terms of individual credit risk assessment, this paper introduces the quadric surface into the traditional Support vector machine and builds the kernel-free quadric surface Support vector machine model, which improves the accuracy by 9.8 percentage points and has a guiding significance for the bank reference risk control.

Relational foundations of an unequal consumer credit market: Symbiotic ties between banks and payday lenders

AbstractBanks have financially supported payday lenders for decades. In this article I qualitatively demonstrate how these financial relationships have reinforced and expanded a bifurcated consumer credit market, and why these relationships matter for consumer access to financial services. I use archival financial documents from publicly traded payday lending companies between 1996 and 2014, available through the Securities and Exchange Commission, to construct the bank‐payday lender network and reveal motivations for these financial relationships. I find that bank‐payday lender relationships are sustained over many years, and that these relationships are mutually beneficial, enabling payday lender expansion and providing a way for banks to quietly profit from high‐interest lending in the face of other regulatory constraints. Further, I show that these relationships have significantly reshaped the consumer credit market over the past two decades. I conclude by considering broader implications of symbiotic institutional relationships in contemporary markets.

National Varieties Still Matter: A Comparative Analysis of Consumer Credit Data Regimes in the United States, Sweden, Israel, and France

Before asking why countries vary, we should ask how they differ. Stressing variations in capitalism models, this article explores how regulatory regimes are related to underlying national institutions and politics. Using a stepwise comparative analysis of consumer credit data regimes in four countries, it underscores variation in two regulatory dimensions: the business restrictions between two clusters, the United States and Sweden vs. France and Israel; and the consumer empowerment within these clusters. The article concludes that grasping the regulatory state’s multidimensional character improves understanding of the regulatory process and underlines the continuity of national capitalist models in the era of regulatory capitalism.

Mathematical Modeling of the Consumer Loan Market in Russia under Sanctions

The article develops and investigates a new model for the formation of interest rates on consumer loans based on an analysis of commercial interests and the logic of behavior of commercial banks. The model assumes that the borrowers’ incomes are described by a geometric Brownian motion. Commercial banks assess the default risk of borrowers. According to the Feynman–Kac formula, the assessment is reduced to solving a boundary value problem for partial differential equations. An analytical solution to this problem is constructed. The model is used to analyze the problem of maintaining consumer credit under the current conditions as a mechanism for social adaptation of households.

Инструменты цифровизации учетно-аналитических процессов региональных компаний (на примере кредитных потребительских кооперативов)

The availability of complete and timely accounting information about the facts of the economic life of companies is a prerequisite for their effective work. The relevance of improvement of accounting and analytical work in credit and consumer cooperatives is due to both changes in the legislation, such as the introduction of a unified chart of accounts and updating of industry accounting standards for non-credit financial organizations, and the need to comply with regulatory requirements and optimize risks. An important tool for the modernization of accounting work is its digitalization. Digitalization of accounting makes it possible to increase the objectivity, rationality and speed of making financial and investment corporate decisions by managers, thereby increasing the competitiveness, sustainability and security of business activities. Digitalization of accounting and analytical processes is of particular importance for regional companies, which, on the one hand, operate in conditions of fierce competition with companies at federal and international levels of administration, and on the other hand, are obliged to comply with the requirements of the regulator for accounting and analytical systems. At the same time, regional companies often have limited budgets for the introduction of digital services, which necessitates the effectiveness of justifying the choice of software for accounting and analytical processes of regional companies based on certain criteria. The purpose of the study was to specify the sources of accounting and analytical information and to develop a methodology for financial standards’ calculation, taking into account the specifics of the activities of credit consumer cooperatives and the requirements of the unified chart of accounts. In the paper, the authors showed the possibilities of software use by credit consumer cooperatives for making managerial decisions and presented accounting information necessary for financial standards calculation. The methodological tools presented in the study can be used by companies to increase the sustainability of their activities and optimize risks.

Real Effects of Search Frictions in Consumer Credit Markets

Abstract We show that search frictions in credit markets affect accepted interest rates and loan sizes and distort consumption. Using data on car loan applications and originations not intermediated by car dealers, we isolate quasi-exogenous variation in both the costs and benefits to searching for credit. After identifying lender-specific policies that price risk discontinuously, we study the differential response to offered interest rates by borrowers who face high and low search costs. High-search-cost borrowers are 10$\%$ more likely to accept loan offers with higher markups, consequently originating smaller loans and purchasing older and less expensive cars than lower-search-cost borrowers. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Algorithmic decision-making in financial services: economic and normative outcomes in consumer credit

Consider how much data is created and used based on our online behaviours and choices. Converging foundational technologies now enable analytics of the vast data required for machine learning. As a result, businesses now use algorithmic technologies to inform their processes, pricing and decisions. This article examines the implications of algorithmic decision-making in consumer credit markets from economic and normative perspectives. This article fills a gap in the literature to explore a multi-disciplinary approach to framing economic and normative issues for algorithmic decision-making in the private sector. This article identifies optimal and suboptimal outcomes in the relationships between companies and consumers. The economic approach of this article demonstrates that more data allows for more information which may result in better contracting outcomes. However, it also identifies potential risks of inaccuracy, bias and discrimination, and ‘gaming’ of algorithmic systems for personal benefit. Then, this article argues that these economic costs have normative implications. Connecting economic outcomes to a normative analysis contextualises the challenges in designing and regulating ML fairly. In particular, it identifies the normative implications of the process, as much as the outcome, concerning trust, privacy and autonomy and potential bias and discrimination in ML systems. Credit scoring, as a case study, elucidates the issues relating to private companies. Legal norms tend to mirror economic theory. Therefore, this article frames the critical economic and normative issues required for further regulatory work.

Providing an Islamic approach of monetary systems

PurposeThe purpose of this paper is organized as follows. Section 2 reviews the literature on the subject matter, focusing on western economic literature and the Islamic economic paradigm, including the Quran, Sunnah, jurisprudence and Islamic philosophy thinking, to illustrate the origins of the Islamic approach to monetary systems. The money interest rate and its studies are explained, and the role of money and credit in the production function is considered. Then, it is shown that money maintains the demand for money in the overlapping generation model, as well as the consumption behavior of households. It is followed by an explanation of general Pareto optimality and the role of the money interest rate in inefficiency and nonoptimality for households and firms. Finally, Section 4 concludes the paper.Design/methodology/approachThis paper studies the effects of money issuance and bank creation on Pareto optimality. In explaining the origins of the Islamic approach to monetary systems, the literature review, it focuses on western economics’ literature and Islamic economics paradigms such as the Quran, sunnah, jurisprudence and Islamic philosophy thinking. In modeling section, the authors show how banks’ fractional reserve credit is profitable. The authors also examine how the introduction of the money interest rate can change the Pareto optimality. In this regard, the comparison between two situations, namely, financing by the stock of money and borrowing in the credit market, indicates that welfare is reduced by the creation system and is inefficient (or nonoptimal). The result is that no money and no credits are created. The provision of this system compensates money by increasing the real money supply or deflation. To ensure Pareto optimality, it has been proven in the field of microfoundation that there should be no fixed money contracts and no money interest rates. It is necessary that the interest rate on consumption credit is zero or Qarz-al-Hasna is broken. Moreover, profit sharing is offered in the production sector.FindingsAs a result, the authors proved mathematically that the money interest rate must be zero to ensure productivity and Pareto optimality. On the other hand, the introduction of money or credit through loanable money leads to inefficiency, both in production and households and in the general equilibrium. The inflation generated by the credit system stimulates the change in the price level and perpetuates this inefficiency. Thus, if the authors want to return to the optimality condition, the interest rate on consumption credit must be zero or Qarz-al-Hasna is breached. However, the behavior of the fractional banking system and the credit mechanism teaches us that the money interest rate is an integral part of credit and loanable funds. Thus, the elimination of the money interest rate from the banking system without bank creation is implausible. Finally, to ensure Pareto optimality, it has been mathematically proven in the field of microfoundation that there should be no fixed money contracts and no money interest rate. It is necessary that the interest rate on consumption credit is zero, or Qarz-al-Hasna is broken. Moreover, profit sharing is offered in the production sector. The result is that no money and credit are created. The provision of this system compensates money by increasing the real money supply or deflation.Originality/valueThe capitalist theory of the definition of interest plays a decisive role in economic science. In this context, the authors are dealing with different vocabularies and terms for the interest rate. These different vocabularies have their origin in the different economic situations and especially determine the thinking of the schools. Because of the relationship between future and spot, the authors have to transform the variable “level” into the variable “interest rate” in the dynamic space. Finally, the exact explanations for the movement and evaluation of the economy are revealed by the correlation of the different interest rates.

Permanent layoff and consumer credit card loss forecasting

PurposeThe unemployment rate (UR) is the leading macroeconomic indicator used in the credit card loss forecasting. COVID-19 pandemic has caused an unprecedented level of volatility in the labor market variables, leading to new challenges to use UR in the credit risk modeling framework. This paper examines the dynamic relationship between the credit card charge-off rate and the unemployment rate over time.Design/methodology/approachThis study uses quarterly observations of charge-off rates on credit card loans of all commercial banks from Q1 1990 to Q4 2020. Univariate, multivariable, machine learning, and regime-switching time series modeling are employed in this research.FindingsThe authors decompose UR into two components – temporary and permanent UR. The authors find the spike in UR during COVID-19 is mainly attributed to the surge in temporary layoffs. More importantly, the authors find that the credit card charge-off rate is primarily driven by permanent UR while temporary UR has little predictive power. During recessions, permanent UR seems to be a stronger indicator than total UR. This research highlights the importance of using permanent UR for credit risk modeling.Originality/valueThe findings in the research can be applied to the credit card loss forecasting and CECL reserve models. In addition, this research also has implications for banks, macroeconomic data vendors, regulators, and policymakers.

Shared and Crowded Housing in the Bay Area: Where Gentrification and the Housing Crisis Meet COVID-19

Amid the growing affordable housing crisis and widespread gentrification over the last decade, people have been moving less than before and increasingly live in shared and often crowded households across the U.S. Crowded housing has various negative health implications, including stress, sleep disorders, and infectious diseases. Difference-in-difference analysis of a unique, large-scale longitudinal consumer credit database of over 450,000 San Francisco Bay Area residents from 2002 to 2020 shows gentrification affects the probability of residents shifting to crowded households across the socioeconomic spectrum but in different ways than expected. Gentrification is negatively associated with low- socioeconomic status (SES) residents’ probability of entering crowded households, and this is largely explained by increased shifts to crowded households in neighborhoods outside of major cities showing early signs of gentrification. Conversely, gentrification is associated with increases in the probability that middle-SES residents enter crowded households, primarily in Silicon Valley. Lastly, crowding is positively associated with COVID-19 case rates, beyond density and socioeconomic and racial composition in neighborhoods, although the role of gentrification remains unclear. Housing policies that mitigate crowding can serve as early interventions in displacement prevention and reducing health inequities.

Privatizing Financial Protection: Regulatory Feedback and the Politics of Financial Reform

Consumer credit is a crucial source of financial support for most Americans—part of what scholars dub the “credit-welfare state.” Yet, borrowers have been reluctant to take political action to demand better consumer financial protection, even as subprime lending proliferates. This paper articulates a broad theory of regulatory feedback effects, proposing specific mechanisms through which regulatory policy making shapes consumers’ politics. Drawing on the case of consumer financial protection, I argue that consumer credit regulations produce feedback effects that diminish political engagement by encouraging borrowers to blame and subsequently target market actors—including financial institutions and consumers themselves—for both systemic and individual problems with predatory lending. I analyze an original policy dataset, original survey of 1,500 borrowers, and two survey experiments to test this hypothesis. I find that borrowers’ experiences with credit regulation diminish their political engagement, even for reforms they support, limiting the prospects for safeguarding Americans’ financial security.

Repeat use of short‐term credit: The case of deposit advance products

AbstractEvery day, consumers borrow using short‐term credit products. Relatively little is known about “Deposit Advance Products” (DAP), short‐term, small‐dollar loans offered to checking account customers. We examine (1) how DAP borrowing changes with repeat use and (2) how consumers use DAP in conjunction with other credit. By analyzing transaction‐level data on more than 100,000 checking accounts over an 18‐month period, we find that consumers' DAP borrowing evolves. With repeat borrowing, consumers take credit for a longer time, increasingly withdraw new loans within a week of repaying prior ones, and borrow more. Additionally, consumers with repeat DAP use are more likely to simultaneously borrow using overdraft. Together, this evidence suggests that DAP may provide inadequate credit for consumers. We discuss implications for the short‐term credit market.

Macroeconomic Determinants of Credit Risk: Evidence on the Impact on Consumer Credit in Central and Eastern European Countries

Although empirical studies show that different types of loans have different risks (moreover, consumer credit risk is higher compared to other types of loans), it is common to study the credit risk of the banking sector as a whole, or of an individual bank’s whole loan portfolio, and the macro-economic factors affecting it (without grouping them by type of loan). Thus, an analysis of the credit risk of the whole loan portfolio (measured by all non-performing loans) is insufficient. Therefore, the aim of this research is to identify the macroeconomic determinants of the consumer loan credit risk and quantitatively assess their impact in Central and Eastern European countries. After the analysis of scientific literature in the field of credit risk determinants, a detailed classification of factors influencing banking credit risk is proposed. The distinguishing feature of the classification is that the factors influencing credit risk are classified at five different levels; twelve groups of general macroeconomic conditions variables were selected as the potential factors of NPLs. This classification can be useful to better understand and investigate the factors influencing banking credit risk for the whole loan portfolio (in the same way as the factors that affect the credit risk of different types of loans, e.g., consumer loans). Using the methods of constant, fixed and random-effects panel analysis, simple OLS, least squares with breakpoints regression analysis and Markov regime-switching models, the impact of the macroeconomic variables from twelve separate groups is evaluated. The data from 11 CEE countries are used, and the period from 2008 to 2020 is covered. The results of this assessment reveal that in the group of CEE countries, such variables as GDP and labour market variables appeared to have contributed to the increase in the share of non-performing consumer loans, while inflation and real estate market variables were related to the decrease in consumer NPLs; at the same time, the impact of variables form other groups appeared to be mixed-nature or insignificant. The results of this research are useful in that they allow the identification of the most important determinants of consumer loan credit risk and thus allow making assumptions about NPL changes due to the changing macroeconomic situation. In the case of Lithuania, this kind of study (assessment of macroeconomic determinants of consumer loan credit risk) was conducted for the first time. Consumer loan credit risk assessment is especially relevant in an increasing interest rate environment, and deeper analysis can help banks and other financial institutions to manage credit risk. On the other hand, a better understanding of the main influencing factors of the macroeconomic environment can help central banks and other official institutions take appropriate monetary and fiscal policy decisions to ensure a good credit transmission channel for sustainable economic growth.

The Influence of Online Consumer Credit on College Students' Consumption Behavior

There is nearly a universal consensus that fintech more so in terms of credit services is convenient, besides serving as an official credit service for learners in colleges. However, in the case of convenience, it also produced a series of social difficulties, resulting in unrestricted spending among college students following obtaining financial assistance from Ant Huabei to spend money. Irrationality eventually emerged, and some students' exorbitant expenditure resulted in exceeding the payback time restriction. It has an effect on learning as well as physical and mental wellness. This issue has piqued the interest of educators and parents.

Milton Friedman and the Road to Monetarism: A Review Essay

Milton Friedman and the Road to Monetarism: A Review Essay

. Prospects of Digital Technology Introduction in Work of Credit Consumer Cooperatives

Today, when digital technologies keep proliferating and integrating in different spheres of human activity, relations among entities, including economy and finance, are being transformed, which makes them more convenient and effective. Digital technologies extend communicative possibilities, simplify movement of information and finance flows and reveal a broad range of lines in further improvement of mechanisms providing better interaction between key entities of finance market, including credit consumer cooperatives. The principle goal of the research is to identify and substantiate the most promising directions of digitalization in functioning of self-regulating bodies of credit consumer cooperatives (CCC), to extend the number of mechanisms of raising extra investment into their work and to improve general finance accessibility in the Russian Federation. Fast development of Russian economy during the last decade, proliferation of digital, finance, banking services and technologies exercised a great impact on the system of cash circulation and credit relations, which shapes a modern outlook of the finance sector in Russia, including the sector of credit cooperation. The article demonstrates two key lines in introducing digital technologies into CCC work and depicts major vectors of their practical application: 1. Digitalization of CCC organization and management processes, as well as optimization of interaction between its members, executive body and selfregulating organization; 2. Use of advanced digital technologies in CCC functioning.

The Impact of Economic Openness on Economic Growth in Aceh Province

Economic openness is part of the demands that impact the entire region on economic development. This research aimed to analyze the impact of Economic Openness on Economic Growth in Aceh Province. The data used in this research was time-series data from 2005-2019. The variables used were exports, imports, domestic credit such as investment credit, consumer credit, working capital credit, and foreign investment (FDI). The data analysis tool used was a dynamic model with a specific approach to Autoregressive Distributed Lag (ARDL) model. The results of this research showed that in the long term, export, import, consumer credit, and working capital credit significantly affected Aceh’s economic growth. Then, the estimation results in the short term showed that import and consumption credit directly affect economic growth. Likewise, the result of Foreign Direct Investment (FDI) in the short term had a significant impact on Aceh’s economic growth. The government must strive to improve Economic openness because the impact is interrelated to national income and affect Aceh’s economic growth.How to Cite:Magfirah, N., Irawan, T., & Anggraeni, L. (2022). The Impact of Economic Openness on Economic Growth in Aceh Province. Signifikan: Jurnal Ilmu Ekonomi, 11 (2), 239-252. https://doi.org/10.15408/sjie.v11i2.21091.

Consumption Loan Augmented Divisia Monetary Index and China Monetary Aggregation

Simple sum monetary aggregates are based on accounting conventions and have no aggregation theoretic foundations in economic theory. In contrast, Divisia monetary aggregates are directly derived from aggregation and index number theory. Credit card services cannot be included in simple sum monetary aggregates since accounting conventions cannot aggregate over assets and liabilities. However, microeconomic aggregation theory aggregates over service flows, not stocks, regardless of whether from assets or liabilities. As a result, it has recently been shown that Divisia monetary aggregates can be augmented to include credit card services and are available from the Center for Financial Stability in New York City. Other sources of consumer credit cannot be included in Divisia monetary aggregates for the United States since other sources of consumer credit in the United States are linked to specific groups of consumer goods and hence, violate the weak separability condition for the existence of an aggregator function. However, China produces a unique opportunity to broaden the Divisia monetary aggregates since sources of consumer credit, not limited to credit cards, are applicable to all consumption purchases and hence, do not violate the existence condition for an aggregator function. We report initial results with a broader Chinese Divisia monetary aggregate, including not only credit card services but also other broadly acceptable consumer loan services.

Student Consumer Culture in Nineteenth-Century Oxford, by Sabine Chaouche

Reviewed by: Student Consumer Culture in Nineteenth-Century Oxford by Sabine Chaouche Emily Rutherford (bio) Student Consumer Culture in Nineteenth-Century Oxford, by Sabine Chaouche; pp. xv + 318. Cham, Switzerland: Palgrave Macmillan, 2020, $109.99, $109.99 paper, $84.99 ebook. In 1848, a twenty-two-year-old man named Edward Napleton Jennings appeared before the London Insolvent Debtors' Court in connection with debts of £1,865 that he had incurred while a student at Oxford—a sum over seven times the annual allowance he received from his father. Among other things, Jennings had spent £56 on wine, £40 on billiards, and—to the astonishment of the press reporting on the case—£98 on hats. Jennings was evidently a highly unusual nineteenth-century Oxford student, with his case provoking a furor about unscrupulous merchants who extended too much credit to naïve undergraduates who were too young to possess sound financial judgment. But the details about his spending habits are indicative of how Student Consumer Culture in Nineteenth-Century Oxford recovers what nineteenth-century Oxford undergraduates wanted to buy, what they bought, how they bought it, and how much they spent. Sabine Chaouche has delved into the accounts of Oxford colleges, the records of the Chancellor's Court (which, instead of the county sessions, heard legal cases involving members of the university), students' personal papers, commercial directories, and the national and regional press to reconstruct a fine-grained picture of the spending habits of one specific group of elite young men amid the rise of a mass consumer culture. A monograph that began its life as a PhD thesis, Chaouche's book is organized thematically, with chapters covering topics including the overall cost of attending Oxford; masculinity, the social relations of undergraduate culture, and how they influenced consumption habits; the economic relationships between the university and the city of Oxford; the roles of debt and credit in the Oxford economy; and some students' opposition to consumer culture. Over the course of these chapters, a narrative of continuity and change in student consumer habits emerges. Chaouche demonstrates with convincing detail and precision that the Oxford economy continuously ran on credit over the course of the nineteenth century and did so to a greater extent than wider British commerce in this period. Layers of credit governed the relationships between town and gown, as shopkeepers secured business by extending generous long-term credit to their student customers, but then needed to borrow themselves from banks or wholesale suppliers to cover the risk they took on through their extension of consumer credit. Chaouche identifies two spikes in student spending and indebtedness, for which she offers two very different explanations. The first occurred in the 1830s, when the Chancellor's Court sued as many as twenty percent of students for repayment of truly enormous consumer debts, and it came at a time when the percentage of Oxford students who were noblemen was at a peak. At this time, indebtedness indicated extravagant spending associated with the performance of a lifestyle of extreme privilege. But when student indebtedness rose again in the 1870s, the debts were smaller and reflected significant changes in the university's constitution and student body that followed a series of mid-nineteenth-century university reforms. Chaouche offers two broadly convincing explanations for these latter debtors: a new class of aspirational bourgeois students who spent beyond their means in their efforts to keep up with the conspicuous consumption of their wealthier peers; and a shift to more students living out of college, meaning that [End Page 478] they were more liable to participate in the urban economy—and to fall prey to the temptation of easy credit. It is unusual for literature on Oxford to span the entire nineteenth century, including both sides of the period of university reform. By doing so, Chaouche is able to offer new insights into how both student experiences and the social and economic world of the city of Oxford changed over the course of this dynamic and consequential period. Her sources allow her to say much more about the relationships between town and gown, and about how the city of Oxford and its local economy depended on the...

Credit Card Fraud Detection Using LSTM Algorithm

With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI) techniques to help banks and financial institutions to support their financial decisions. Neural networks are considered as a mostly wide used technique in finance and business applications. Thus, the main aim of this search is to help bank management in scoring credit card clients using machine learning by modelling and predicting the consumer behavior with respect to two aspects: the probability of single and consecutive missed payments for credit card customers. The proposed model is based on the bidirectional Long-Short Term Memory (LSTM) model to give the probability of a missed payment during the next month for each customer. The model was trained on a real credit card dataset and the customer behavioral scores are analyzed using classical measures such as accuracy, Area Under the Curve, Brier score, Kolmogorov–Smirnov test, and H-measure. Calibration analysis of the LSTM model scores showed that they can be considered as probabilities of missed payments. The LSTM model was compared to four traditional machine learning algorithms: support vector machine, random forest, multi-layer perceptron neural network, and logistic regression. Experimental results show that, compared with traditional methods, the consumer credit scoring method based on the LSTM neural network has significantly improved consumer credit scoring.