Results 101 to 110 of about 112,889 (239)
Mining Bad Credit Card Accounts from OLAP and OLTP
, 2017 Credit card companies classify accounts as a good or bad based on historical data where a bad account may default on payments in the near future. If an account is classified as a bad account, then further action can be taken to investigate the actual ...
Eberle, William +2 more
core +1 more source
Data-driven financial fraud detection using hybrid artificial and quantum intelligence
BenchCouncil Transactions on Benchmarks, Standards and EvaluationsThe unauthorized use of a cardholder’s financial data, resulting in significant losses to individuals and companies, is known as credit card fraud. The increasing frequency and complexity of such fraud in the digital era highlight the absolutely vital ...
Md. Sobuj Mia +4 more
doaj +1 more source
Deep Learning for Credit Card Fraud Detection: A Review of Algorithms, Challenges, and Solutions
IEEE AccessDeep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in ...
Ibomoiye Domor Mienye, Nobert Jere
doaj +1 more source
Melting the Plastic Theories: Advocating the Common Law of Fraud in Credit Card Non-dischargeability Actions under 11 U.S.C. § 523(a)(2)(A) [PDF]
, 1997 If credit card-holders purchase items they cannot afford, they may make minimum payments and avoid default. Most people carry debt on their credit cards,\u27 and card-issuers who profit from interest on these balances encourage consumers to carry a ...
Bruens, Craig A.
core +1 more source
Радіоелектронні і комп'ютерні системиThe subject matter of this article is enhancing credit card fraud detection systems by exploring the impact of oversampling rates and ensemble methods with diverse feature selection techniques.
Mohamed Akouhar +3 more
doaj +1 more source
Credit Card Fraud Detection: An Improved Strategy for High Recall Using KNN, LDA, and Linear Regression. [PDF]
Sensors (Basel), 2023 Chung J, Lee K.
europepmc +1 more source