Car Loans Research Articles

Putting Automobile Debt on the Map: Race and the Geography of Automobile Debt in California

Most U.S. metropolitan areas developed alongside the automobile, producing neighborhoods of relatively low density. Consequently, access to opportunities in these neighborhoods is predicated on having an automobile, yet many households do not have the resources to purchase one outright, relying on automobile loans to spread out the purchase price. While automobile loans can enable automobile ownership, they also significantly increase the vehicle purchase price, particularly for non-white consumers subject to discriminatory lending practices.In this study, we rely on data from the University of California Consumer Credit Panel from Experian to examine the determinants and geography of automobile debt and its consequences in California, testing whether various automobile debt measures disproportionately affect non-white neighborhoods.We find that, controlling for other factors associated with automobile lending including income, Black and Latino/a neighborhoods have higher total automobile debt, debt burdens (debt relative to income), and automobile loan delinquency rates. In particular, Latino/a neighborhoods shoulder significant automobile debt, while borrowers in Black neighborhoods have the highest delinquency rates. Factors associated with lower total automobile debt and automobile debt burden include better credit ratings, higher residential densities, urban locations, and proximity to rail stations.The findings underscore the importance of policies to offset the costs of automobile ownership and access. As part of this, policymakers should adopt and enforce fair lending rules to combat discriminatory and predatory practices and facilitate access to high-quality financial institutions and products in communities of color.

Optimizing Financial Decision Support Systems with Machine LearningDriven Recommendations

Introduction: The research investigates the utility of cosine similarity as an innovative recommendation system designed to assist individuals in making financial choices tailored to their unique preferences and objectives. It embarks on an extensive analysis of diverse datasets encompassing a wide array of financial products, including investment portfolios, credit card offerings, insurance plans, personal loan options, and car loan packages. Each dataset undergoes meticulous feature extraction and preprocessing to optimize the accuracy of the cosine similarity model. Method: The research then applies cosine similarity to calculate the similarity scores between individual financial products, thereby producing personalized recommendations. These recommendations are predicated on a comprehensive spectrum of input variables. The outcomes of these case studies demonstrate the potency of cosine similarity as a foundation for the development of tailored financial guidance systems. Such recommendations empower individuals to make informed decisions that are intrinsically aligned with their distinctive financial aspirations. Results: Ridge and lasso regression algorithms are deployed to develop predictive models for assessing investment preferences and evaluating potential investment returns. Conclusion: The study highlights the necessity for financial institutions and advisory platforms to invest in data quality and algorithmic sophistication to enhance the efficacy and accuracy of these financial recommendations.

Research on sales strategies for target customers of electric vehicles based on gradient boosting ensemble trees

This paper focuses on the automotive industry, especially the new energy vehicle sector, which is vital for the economy and needs careful market sales decisions. It analyzes data from 1,964 potential customers, including their satisfaction and personal information. The study uses machine learning to create a math model and give sales advice. The data is first cleaned without changing its original structure, and then normalized using the Z-Score method. For any outlier values in the data, the mean of similar items is used to fill in gaps. Specifically, for 500 missing entries about the number of children (B7), the paper groups customers by age, calculates the frequency of children in each group, and uses these frequencies to fill in missing values.Using the cleaned data, the XGBoost algorithm ranks the factors influencing customer decisions. For Brand 1, the top factors are economy (a3), work experience (B10), and safety performance (a4). For Brand 2, comfort (a2), disposable income (B15), and mortgage expenses (B16) are key. For Brand 3, car loan expenses (B17), battery technology (a1), and again mortgage expenses (B16) are most important.The paper also addresses imbalanced data by using an XGBoost binary classification model. This model predicts the likelihood of buying an electric vehicle using the Sigmoid function on tree node weights. It evaluates the model using Precision, Recall, and Area Under the Receiver Operating Characteristic Curve (AUC), which works well even with imbalanced data. The Precision and Recall rates for all three brands are above 90%, with AUC over 85% for Brands 1 and 2, and over 75% for Brand 3. This shows that the model is effective and can be used in real-world situations.

Driving A-loan: Automobile debt, neighborhood race, and the COVID-19 pandemic

COVID-19 altered travel patterns in the U.S. Studies have analyzed the effect of the pandemic on travel mode, including working from home, but few have focused on automobile ownership—a relationship with potentially long-term consequences for accessibility, household budgets and debt, and policy efforts to meet climate goals.To understand the association between the pandemic and automobile ownership, we rely on a unique credit panel dataset from Experian and examine three different automobile loan-related outcome measures: annualized growth rate of new automobile loan balances, average new loan size, and the number of new loans. We focus specifically on changes across loans in neighborhoods by race/ethnicity, hypothesizing larger increases in automobile debt in Black and Latino/a neighborhoods, where workers are less likely to be able to telework. The annualized growth rate of new automobile loans increased during the pandemic across all neighborhoods by race/ethnicity, increasing most rapidly in Latino/a neighborhoods. Controlling for other factors, loan size increased similarly across neighborhoods by race/ethnicity. The increase in automobile lending in Latino/a neighborhoods, therefore, likely was explained by a significant uptick in the number of new loans.The growth in automobile lending during the pandemic was potentially prompted by pandemic-induced changes in the need for automobiles and facilitated by an expanded social safety net. As the pandemic and its various forms of public financial assistance recede, the findings underscore the importance of ongoing assistance in enabling automobile ownership or shared access among households with limited means whose livelihoods depend on the access that vehicles provide.

One Month Longer, One Month Later? Prepayments in the Auto Loan Market

We document a secular trend of increasing auto loan maturity from 30 months to over 70 months during the past 50 years, partly reflecting improved vehicle durability. Analyzing over half of the auto loans originated during the past 16 years, we find that longer-maturity new car loans have significantly higher interest rates with a yield curve much steeper than comparable-maturity Treasury securities. In addition, we show that the majority of auto loans were prepaid, including loans of zero-interest, and that many prepaying borrowers could have paid less interest by choosing loans of a shorter maturity. We argue that factors such as liquidity constraints, uncertainty about future income, and monthly payment targeting likely account for only a portion of borrowers' choice of long-maturity loans.

Implementasi Simple Multi Attribute Rating Technique untuk Menentukan Kelayakan Pengajuan Kredit Mobil

Increasing consumer demand for car loans requires finance companies to make quick and accurate decisions, so there are obstacles such as sufficient time in deciding whether to accept or reject loan applications by consumers. The purpose of this study is to create a decision support system using the simple multi-attribute rating technique (SMART) to assist in determining the feasibility of car loans. This study used a quantitative approach. The system built applies a waterfall model with stages of analysis, design, implementation, and testing. The analysis is carried out to find the needs of the system created, with design using UML, including class diagrams, entity relationship diagrams, and interface design. The implementation phase was carried out at Indomobil Finance Kisaran using consumer sample data from observations and interviews. System testing uses black box testing to see the performance of the system created. Our findings are that there need to be improvements to the data processing process and the duration of time for making decisions on accepting or rejecting car loans submitted by consumers. From the results of black box testing, no system failure was found, so the system is designed to run well and by expectations is to help the company determine the feasibility of car loans submitted by consumers with fast and accurate results.

Unequally Indebted: Debt by Education, Race, and Ethnicity and the, Accumulation of Inequality in Emerging Adulthood

Emerging adults in the U.S. face significant economic uncertainty during the early life course. Economic uncertainties grew in the 2000s, especially for the Millennial cohort. Access to credit can be a resource to manage the instability that characterizes emerging adulthood. However, debt can also become a burden, making credit like a “double-edged sword.” We study inequality in debt holding for five debt types that provide distinct resources and burdens, including mortgages, car loans, student loans, credit cards, and other debts to businesses. We analyze the extent to which the Millennial cohort accumulated unequal debts by the end of emerging adulthood using the National Longitudinal Survey of Youth, 1997 Cohort. We find strikingly unequal debt holding by education, race/ethnicity, and education-by-race/ethnicity for Millennial emerging adults. We conclude that policies and programs that support emerging adult financial wellbeing will be crucial for healthy development and reduced inequalities during this life course stage.

Politics of household indebtedness in Turkey

ABSTRACT This paper deals with how Justice and Development Party (AKP) governments navigated the politics of household indebtedness in Turkey and utilized it towards the 2023 elections. It argues that household debt is a political tool with positive and negative consequences for incumbent governments. Households have been able to access debt instruments such as credit cards, consumer credit, car loans, and mortgages in Turkey since the onset of financialisation in the 2000s. AKP governments have benefited from the micro-level household wealth/debt accumulation as well as its macro-level economic implications for the construction-led, credit-dependent economic growth model. On the other hand, household debt has had destructive societal consequences such as bankruptcies, divorces, and suicides that became commonplace in the opposition narratives. Pinpointing the responsibility for indebtedness among households, financial system, regulatory agencies, and government, as well as devising policy solutions, has become a political struggle in the months leading up to the 2023 elections.

Практика использования ESG-подходов в сделках секьюритизации

The spread of the sustainable development concept has given rise to sustainable finance, as well as the infrastructure of the financial and consulting industry of valuations, verifications and various databases in the field of ESG. This research is devoted to theoretical and practical study of the accumulated experience of ESG securitization transactions in order to systematize ESG financing instruments and directions of development of this sphere in modern conditions. The study showes that ESG securitization practices are being integrated into capital management processes in line with sustainable development goals, with the most developed centers in the USA, Europe and China. The study systematizes the main types of ESG securitized assets, gives their characteristics and identifies current trends. In Russia, despite its isolation from the world financial markets, the practice of ESG securitization is developing, covering new directions. The study notes the potential for the development of green mortgages, which will contribute to the activation of securitization transactions in the segment of residential and commercial real estate. High potential for development of the social segment of ESG securitization is also noted due to the growing demand for financing social projects in the regions. Expansion of the practice of social mortgage securitization will contribute to the redistribution of risks between the public and private sectors, while active involvement of Russian banks in a variety of ESG lending programs (car loans, lending to small and medium-sized businesses with a green and social focus, e.g. for the construction of social infrastructure, etc.) will expand the market. There is a suggestion that the development of digital ESG securitization platforms will help expand the reach of retail investors, while cooling the junk bond market. The article notes that the expansion of multi-tranche ESG securitization will allow long-term assets of pension funds and various ESG funds to be leveraged into mortgage-backed securities. Overall, ESG securitization improves the structure of transactions, expands the range of derivatives used, improves the quality of credit and interest rate risk management, and contributes to the achievement of sustainable development goals.

Strategies to Improve the Sales Performance of Car Loan Products in Bank Shinhan Indonesia

In internal Bank Shinhan, My Car Loan is one of their top consumer products. However, when compared to other car financing competitors, Bank Shinhan was far behind in terms of sales performance. Hyundai Motors Indonesia has four official financial partners to support its car purchasing, namely: Maybank Finance, Mandiri Tunas Finance, Sunindo KB Finance, and Bank Shinhan. The company is the only bank-based financial partner, while the three others were multi-finance companies that specialized in car financing. Moreover, two of them, Mandiri Tunas Finance and Maybank were already well-known players in the car financing industry. Meanwhile, Bank Shinhan is a new player with low brand awareness among the public. In this research, the data collection methods were interviews and questionnaires. As for the research method, for the questionnaire data, the author used the NPS (Net Promoter Score) method and reliability test. As for the interview data, the author used the TA (thematic analysis) method. With this research, the author aimed to get insights to propose new strategies.

Veblen was Right: Why People Seek Unaffordable Cars

We study the connection between financialization and consumerism, and claim that greater availability of consumer loans affects consumerist culture and promotes the institution of conspicuous consumption. We extend the ideas of Thorstein Veblen who coined the term of “conspicuous consumption” to illustrate our thinking with the empirical evidence on car purchases financed through bank loans in Russia’s Rostov Region. We find that leveraged car buying has become embedded over the past 20 years. Social positioning drives people to seek more expensive cars, whereas getting a bank loan allows to buy an otherwise unaffordable car. We see a sign of conspicuousness in the fact that household income grows slower than the average price of a new car financed by a car loan, as well as the amount of loans. Our contribution is that a basic concept of institutional theory (conspicuous consumption) is combined with elements from other research approaches, namely the social significance of bank lending, functional differentiation of credit, and the effects of financialization.

Проблемы и перспективы развития кредитного рынка России

The article discusses the problems and prospects of the development of the Russian credit market. The author analyzes the main components of the Russian credit market, such as commercial loans for business, mortgage lending, car loans and consumer non-targeted loans. The state of the credit market depends on the state of the economy and the policy of the Central Bank. Possible measures to regulate debt collection activities and the formation of the institution of a public mediator of the financial system (financial ombudsman) are discussed.

MODELLING THE BANK CUSTOMER ACTIVITY DURATION BASED ON THE COX ECONOMETRIC SURVIVAL MODEL

The banking sector is constantly evolving, seeking effective ways to attract and retain clients, especially those with high financial potential. One of the ways to achieve this goal is to provide car loans at low interest rates, such as 0.01%. However, the untimely outflow of clients after repayment of the car loan becomes a significant problem for banks leading to the loss of potential income from other banking services. The research aims to evaluate the impact of selling additional banking services on increasing clients' activity duration. The research used statistics on opening new bank clients, whose first product was a car loan at an interest rate of 0.01%, from 2018 to 2022. The dataset included 9,224 records. The Cox proportional hazards model is used to determine the impact of a credit card on the duration of car loan client activity. The analysis of the model coefficients showed that with a credit card, clients closed at a rate of 0.86 of the rate of closing clients without a credit card. However, during the verification of the proportional hazard assumption, it was determined that the credit card's influence level changes significantly over time, indicating the model's inadequacy. The next phase of the study was the search for an influencing parameter that meets all the quality conditions of the Cox model. Having a credit card with at least one transaction was selected. For this model variation, all indicators of model adequacy were met. The coefficient estimation results showed that clients with an active credit card closed at a rate of 0.36 of the rate of closing clients without it. The evaluation of the active credit card impact confirms that selling a credit card allows for an increase in the bank clients' activity duration. However, a critical success factor is the sale of a credit card and its activation. The obtained research results can be used to optimize the bank's marketing and sales strategies, ensure more effective customer retention and increase the bank's profits.

Workaholism among young people in the ride-hailing travel economy

The effects of precarious jobs on young people's well-being could be enduring. Research into the causes of harmful working behaviours among young people in the ride-hailing economy is limited. We used qualitative data from 40 ethnographic in-depth interviews with drivers in Ghana, Nigeria, Tanzania, and South Africa to explore the root causes of workaholism among them and, in turn, proposed a typology. The framing of the typology was guided by the three-tiered tourism workforce taxonomy, which resulted in seven workaholic types. Beyond technology mediation, the reasons for their workaholism included demanding contractual structures, dependency, limited mandatory breaks, culminating into their reliance on energy drinks. Among other actions, deploying catalytic capital to support car loans, reforming regulations and, implementing universal breaks can help address the casues of overworking among ride-hail drivers.

CAR RENTAL INFORMATION SYSTEM DESIGN AT CV. NUSA RENTCAR BEKASI BASED WEBSITE USING THE WATERFALL METHOD

Processing data manually is felt to be very problematic, including when recording cars that are usually rented out, customer records, recording car loan and return transactions, up to reporting car loan and return transactions. Besides that, the marketing and publication activities carried out by the car rental business CV. Nusa Rentcar Bekasi to the wider community still uses pamphlets and advertisements in print media, the impact of the marketing area obtained is very limited so that CV. Nusa Rentcar Bekasi is less known by the wider community. Based on the explanation above, in order to be able to increase and expand market share, make it easy for the general public to obtain information about the services provided by CV. Nusa Rentcar Bekasi and provide convenience to the service sales department in carrying out data processing, data search to report generation, a media or website-based information system is needed that can overcome the problems faced by CV car rental. Nusa Rentcar Bekasi. In this study the system development model used is the Waterfall model. The results of this study can provide several advantages, namely information processing and data management of sales of car rental services at CV. Nusa Rentcar Bekasi is more efficient and effective.

Perlindungan Hukum Bagi Pihak Yang Meminjamkan Dan Yang Meminjam Dalam Perjanjian Pinjam Pakai

Loan agreements are an important aspect of everyday life, facilitating the borrowing of goods or property for a certain period of time. In this context, legal protection for lending and borrowing parties is crucial. This paper discusses the theoretical and practical aspects of lending and use agreements as well as research methodology in evaluating the effectiveness of existing regulations. The study highlights the challenges and need to balance the rights and obligations of both parties. Referring to the Civil Code, this study examines the rights, obligations, and legal protection of both lenders and loan recipients. Equipped with car loan case studies, this paper highlights the need for clear regulations, including item identification, insurance, time limits, and rights and responsibilities that must be set out in detail in the agreement. With a deep understanding of laws and regulations, lending and use agreements can provide maximum protection for all parties involved.

Sistem Pendukung Keputusan Persetujuan Pengajuan Kredit Mobil di PT Clipan Finance Indonesia Dengan Metode Simple Additive Weighting (SAW)

Abstract
 PT Clipan Finance Indonesia is a car loan financing leasing company. This company has a standard in determining whether or not a customer is eligible for car loan financing. In choosing clients who deserve for car loan financing, it must be done properly to avoid client credit congestion, so it is necessary to select client data analysis. In selecting this client data, a decision support system information was designed that can help determine the priority of clients who are eligible for car loan financing, by using the Simple Additive Weighting (SAW) method as a method of supporting decision making. The SAW method is used to support decision making to evaluate the feasibility value of clients in selecting data for clients who apply for car loans based on the criteria and weight of decision making. Through this system, it is hoped that it can help determine the feasibility of applying for a client's car loan more effectively and efficiently by making the ranking value obtained as a reference for determining client creditworthiness approval.
 Keywords: Car Loan Financing, Decision Support System, Simple Additive Weighting

Product Sales Incentive Spillovers to the Lending Market: Evidence from Subprime Auto Loan Defaults

This paper shows how convex incentives in vertical contracts between manufacturers and retailers can induce sales behavior with costs to consumers. We examine this problem in the automotive sector, where manufacturers commonly motivate new vehicle sales through dealer incentive programs with large discrete bonuses determined by monthly sales targets. Using subprime car loans from over 3,500 dealerships, we document high default rates on new car loans originated at the end of the month—the period when dealerships attempt to secure target-based bonuses by intensifying efforts to sell new cars. We provide evidence consistent with the observed higher default rates resulting from customers purchasing new vehicles at month end. New car purchases stretch borrower budgets and expose borrowers to rapid depreciation, which consigns the borrower with negative equity through much of the loan term. Our results imply that the quartile of customers with the highest payment-to-income ratio see default rates increase from 13.6% to 19.7% on the last day of the month. Although consumers bear high costs from increased defaults, we find no evidence that lenders that purchase the loans are hurt by the default increase. Our results demonstrate how the behaviors induced by convex incentive schemes for sales are borne by customers. This paper was accepted by David Simchi-Levi, business strategy. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4935 .

Prevalence and Clinical Characteristics of Recreational and At-Risk/Problematic Gambling Among Low-Income U.S. Veterans: Results from the National Veteran Homeless and Other Poverty Experiences (NV-HOPE) Study.

This study examined associations between recreational gambling (RG) and at-risk/problem gambling (ARPG), and clinical measures of mental illness and substance use, functionality, homelessness, in a nationally representative sample of U.S. military veterans. Data were analyzed from 781 veterans who participated National Veteran Homeless and Other Poverty Experiences (NV-HOPE) study conducted in 2021. Chi-square tests, analyses of variance (ANOVAs) and logistic regressions analyses were conducted to examine unadjusted and adjusted associations between gambling group status and sociodemographic, psychiatric, substance use, functioning, and homelessness measures. A significant minority of low-income U.S. veterans reported gambling, with 24.9% (95% confidence interval [CI] 95% CI 21.12-28.76%) exhibiting RG and 6.7% (95% CI 3.88-9.42%) screening positive for ARPG. The prevalence of ARPG was higher among younger, non-White veterans. ARPG was associated with greater symptoms of substance use and anxiety; poorer physical functioning; history of any mental illness; lifetime history of homelessness; and having any student or car loans relative to NG. Veterans who had RG were more likely to screen positive for drug use disorders relative to NG. Results of the current study provide an up-to-date estimate of the current prevalence of RG and ARPG among low-income U.S. veterans and underscore the importance of routine screening, monitoring, and development of interventions for problematic gambling severity, as well as interventions for ARPG in this population. These findings may inform targeted intervention strategies for this vulnerable subpopulation.

A Feast in Time of Plague: Debt-Financed Spending Spree during the Pandemic

The paper explores the nexus between household consumption, financialization, and socio-economic policy. We focus on the recent episode of debt-financed buying of passenger cars which took place in Russia in 2020–21, amidst the Covid pandemic. We collect statistics on car sales, car loans and household income, and construct metrics to gauge leveraged car buying. The latter is found to be relatively inelastic to the price of a car and personal income. Two specific factors are highlighted: (a) speculation, alias hedging, to which households resort under financial instability; and (b) government policy aiming to facilitate household access to car loans. Conceived as a palliative against the pain of economic downturn, loan availability might instead bolster speculative demand and inflate price bubbles. The paper contributes to the body of literature on the sociology of consumption, household financialization, and the political economy of lending.