scholarly journals The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data

2021 ◽  
Author(s):  
Akos Horvath ◽  
Benjamin Kay ◽  
Carlo Wix
Keyword(s):  
Credit Card ◽  
Consumer Credit ◽  
Credit Card Data

scholarly journals The COVID-19 Shock and Consumer Credit: Evidence from Credit Card Data

2021 ◽  
Vol 2021 (008) ◽  
pp. 1-55
Author(s):  
Akos Horvath ◽  
◽  
Benjamin Kay ◽  
Carlo Wix ◽  
◽  
...  
Keyword(s):  
Interest Rates ◽  
Credit Card ◽  
Negative Impact ◽  
Consumer Credit ◽  
Credit Cards ◽  
Sharp Decrease ◽  
Main Driver ◽  
Credit Card Data ◽  
Pandemic Severity ◽  
The Impact

We use credit card data from the Federal Reserve Board's FR Y-14M reports to study the impact of the COVID-19 shock on the use and availability of consumer credit across borrower types from March through August 2020. We document an initial sharp decrease in credit card transactions and outstanding balances in March and April. While spending starts to recover by May, especially for risky borrowers, balances remain depressed overall. We find a strong negative impact of local pandemic severity on credit use, which becomes smaller over time, consistent with pandemic fatigue. Restrictive public health interventions also negatively affect credit use, but the pandemic itself is the main driver. We further document a large reduction in credit card originations, especially to risky borrowers. Consistent with a tightening of credit supply and a flight-to-safety response of banks, we find an increase in interest rates of newly issued credit cards to less creditworthy borrowers.

Identifying Major Issues of Tourism Analysis Using Big Data : Focused on Mobile and Credit Card Data

2018 ◽  
Vol 30 (3) ◽  
pp. 3-22
Author(s):  
Won-Seop Shim ◽  
Seung-Mook Choi ◽  
Chang-Sup Shim
Keyword(s):  
Big Data ◽  
Credit Card ◽  
Credit Card Data

Why Did Credit Card Balances Decline so Much during the COVID-19 Pandemic

FEDS Notes ◽  
2021 ◽  
Vol 2021 (3025) ◽  
Author(s):  
Robert M. Adams ◽  
◽  
Vitaly M. Bord ◽  
Bradley Katcher ◽  
◽  
...  
Keyword(s):  
United States ◽  
Credit Card ◽  
Consumer Credit ◽  
The United States ◽  
History Of

Consumer credit card balances in the United States experienced unprecedented declines during the COVID-19 pandemic. According to the G.19 Consumer Credit statistical release, revolving consumer credit fell more than $120 billion (11 percent) in 2020, the largest decline in both nominal and percentage terms in the history of the series.

scholarly journals A Survey: Data Leakage Detection Techniques

2018 ◽  
Vol 8 (4) ◽  
pp. 2247
Author(s):  
K. S. Wagh
Keyword(s):  
Credit Card ◽  
Information Leakage ◽  
Leakage Detection ◽  
Sensitive Data ◽  
Detection Techniques ◽  
Personal Credit ◽  
Customer Information ◽  
Other Information ◽  
Effective System ◽  
Credit Card Data

Data is an important property of various organizations and it is intellectual property of organization. Every organization includes sensitive data as customer information, financial data, data of patient, personal credit card data and other information based on the kinds of management, institute or industry. For the areas like this, leakage of information is the crucial problem that the organization has to face, that poses high cost if information leakage is done. All the more definitely, information leakage is characterize as the intentional exposure of individual or any sort of information to unapproved outsiders. When the important information is goes to unapproved hands or moves towards unauthorized destination. This will prompts the direct and indirect loss of particular industry in terms of cost and time. The information leakage is outcomes in vulnerability or its modification. So information can be protected by the outsider leakages. To solve this issue there must be an efficient and effective system to avoid and protect authorized information. From not so long many methods have been implemented to solve same type of problems that are analyzed here in this survey.  This paper analyzes little latest techniques and proposed novel Sampling algorithm based data leakage detection techniques.

Kueski: Revolutionizing Consumer Credit in Mexico

2017 ◽  
pp. 1-10
Author(s):  
Sarit Markovich ◽  
Nilima Achwal
Keyword(s):  
Financial Market ◽  
Financial Services ◽  
Scoring System ◽  
Credit Card ◽  
Consumer Credit ◽  
Credit Scoring ◽  
Loan Approval

This case asks students to step into the role of Adalberto Flores, co-founder and CEO of Kueski, one of the first companies to develop a proprietary algorithm for online loan approval in Mexico. Mexico lacks a standardized credit scoring system, making it difficult for many Mexicans to get approved for a loan or credit card. This, together with the fact that Mexicans generally do not trust traditional banks, makes Mexico an attractive opportunity for fintech companies. Growth, however, could require fintech companies to partner with traditional banks. Students assume the role of Flores to think about the benefits and risks associated with a partnership between Kueski and traditional banks. Students are also challenged to compare the structure of U.S. financial services markets with the Mexican structure and consider the implications on the sustainability of fintech companies in the two markets. The teaching note analyzes the Mexican financial market and the benefits and threats it holds for fintech companies, and outlines a framework for evaluating the risk associated with partnerships.

Knowledge Through Evolution

2008 ◽  
pp. 311-324
Author(s):  
Russell Beale ◽  
Andy Pryke
Keyword(s):  
Artificial Intelligence ◽  
Genetic Algorithm ◽  
Credit Card ◽  
Machine Learning Algorithms ◽  
Statistical Techniques ◽  
Dynamic Visualization ◽  
Telecommunications Network ◽  
Credit Card Data ◽  
Conventional Machine ◽  
Interactive 3D

This chapter argues that a knowledge discovery system should be interactive, should utilise the best in artificial intelligence (AI), evolutionary, and statistical techniques in deriving results, but should be able to trade accuracy for understanding. Further, it needs to provide a means for users to indicate what exactly constitutes “interesting”, as well as understanding suggestions output by the computer. One such system is Haiku, which combines interactive 3D dynamic visualization and genetic algorithm techniques, and enables users to visually explore features and evaluate explanations generated by the system. Three case studies are described which illustrate the effectiveness of the Haiku system, these being Australian credit card data, Boston area housing data, and company telecommunications network call patterns. We conclude that a combination of intuitive and knowledge-driven exploration, together with conventional machine learning algorithms, offers a much richer environment, which in turn can lead to a deeper understanding of the domain under study.

Timing to the Statement: Understanding Fluctuations in Consumer Credit Use

2020 ◽  
Author(s):  
Sumit Agarwal ◽  
Amit Bubna ◽  
Molly Lipscomb
Keyword(s):  
Credit Card ◽  
Consumer Credit ◽  
Liquidity Constraints ◽  
Mental Accounting ◽  
Debit Card ◽  
Mixed Support

We show that consumers spend 15% more per day in the first week following the receipt of a credit card statement than in the days just prior to the statement. This increase in spending includes both an increase in the likelihood that they use the credit card in the first weeks following their statement and an increase in transaction amount on days they use the credit card. In contrast to the effect on credit card spending, debit card spending is unaffected by credit card statement issuance, suggesting that consumers are not simply switching among modes of payment. Our estimates are based on exogenous variation from bank-assigned statement dates. We propose and test several alternative explanations to this spending puzzle: optimization of the free float, salience effect of the credit card statement, mental accounting, liquidity constraints, and automatic payments. We find that the consumers most apt to spend early in the credit card cycle tend to be those who do not revolve balances and are not close to their credit limit. Thus, this paper documents a puzzle with mixed support for several alternative explanations. This paper was accepted by David Simchi-Levi, finance.

The “Everything Card” and Consumer Credit in the United States in the 1960s

2011 ◽  
Vol 85 (3) ◽  
pp. 551-575 ◽  
Author(s):  
Christine Zumello
Keyword(s):  
New York ◽  
Commercial Bank ◽  
Credit Card ◽  
Consumer Credit ◽  
Credit Cards ◽  
The United States ◽  
Retail Banking ◽  
Mass Consumption ◽  
Legislative Action ◽  
The 1960S

First National City Bank (FNCB) of New York launched the Everything Card in the summer of 1967. A latecomer in the field of credit cards, FNCB nonetheless correctly recognized a promising business model for retail banking. FNCB attempted not only to ride the wave of mass consumption but also to capitalize on the profit-generating potential of buying on credit. Although the venture soon failed, brought down by the losses that plagued the bank due to fraud, consumer discontent, and legislative action, this final attempt by a major single commercial bank to launch its own plan did not signify the end of credit cards. On the contrary, the Everything Card was a harbinger of the era of the universal credit card.

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