| Autor: |
Patel Amit, Patel Manish, Patel Pankaj |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
ITM Web of Conferences, Vol 65, p 03006 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2271-2097 |
| DOI: |
10.1051/itmconf/20246503006 |
| Popis: |
Given the current situation of the economy, credit card use has increased significantly. Users can make significant cash payments with these cards without carrying a lot of cash on them. They have simplified the process of conducting cashless transactions and enabled consumers to make payments of any kind with greater ease. While there are many benefits to using this electronic payment method, there are also some risks. In tandem with the expansion of the consumer base. A specific person’s credit card information may be unlawfully acquired and used in fraudulent purchases. To tackle this issue, certain machine learning methods may be applied to gather information. This research offers a comparative analysis of many supervised learning method for identifying real from fake transactions. In this article, we have covered a variety of techniques for spotting credit card fraud. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
