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CardSim: A Bayesian Simulator for Payment Card Fraud Detection Research
Data included as part of a paper that introduces CardSim, a flexible, scalable payment card transaction simulation methodology that extends the small but emerging body of simulators available for payment fraud modeling research.
The data are from the 2022 and 2023 Survey and Diary of Consumer Payment Choice public use datasets, published by the Federal Reserve Bank of Atlanta.
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"920:00"
]
|
| contactPoint |
{
"fn": "Katherine Tom",
"hasEmail": "mailto:ogda-data@frb.gov"
}
|
| description | Data included as part of a paper that introduces CardSim, a flexible, scalable payment card transaction simulation methodology that extends the small but emerging body of simulators available for payment fraud modeling research. The data are from the 2022 and 2023 Survey and Diary of Consumer Payment Choice public use datasets, published by the Federal Reserve Bank of Atlanta. |
| identifier | FRBC0021 |
| keyword |
[
"Financial crimes",
"Payment cards, Fraud detection, Bayesian analysis, Simulation, Machine learning, Payment systems"
]
|
| landingPage | https://www.federalreserve.gov/econres/feds/cardsim-a-bayesian-simulator-for-payment-card-fraud-detection-research.htm |
| modified | 2025-02-28 |
| programCode |
[
"920:000"
]
|
| publisher |
{
"name": "Board of Governors of the Federal Reserve System"
}
|
| title | CardSim: A Bayesian Simulator for Payment Card Fraud Detection Research |
