Name
Abstract | ||
|---|---|---|
Along with increasing credit cards and growing trade volume in China, credit card fraud rises sharply. How to enhance the detection and prevention of credit card fraud becomes the focus of risk control of banks. This paper proposes a credit card fraud detection model using outlier detection based on distance sum according to the infrequency and unconventionality of fraud in credit card transaction data, applying outlier mining into credit card fraud detection. Experiments show that this model is feasible and accurate in detecting credit card fraud. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/JCAI.2009.146 | JCAI |
Keywords | Field | DocType |
smart cards,credit card transaction data,fraud detection,credit transactions,risk control,distance sum,credit card fraud,bank data processing,risk analysis,credit card fraud detection model,fraud,credit card,bank risk control,data mining,outlier,outlier mining,credit card fraud prevention,trade volume,outlier detection,credit card fraud detection,security of data,database systems,prediction algorithms,algorithm design and analysis,computer science,data analysis,statistical distributions,accuracy,artificial intelligence,transaction data | Anomaly detection,Credit card interest,Credit card fraud,Actuarial science,Computer science,Computer security,Card security code,Smart card,Credit card,Transaction data,Chargeback | Conference |
ISBN | Citations | PageRank |
978-0-7695-3615-6 | 5 | 0.47 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wen-Fang Yu | 1 | 5 | 0.81 |
| Na Wang | 2 | 5 | 0.47 |