Credit Card Fraud Detection
Banking Sector involves a lot of transactions for their day to day operation and they have now realized that their main disquietude is how to detect fraud as early as possible. Due to fulsome advancement in technology, it is imperative for bank to save its money from fraud. The primary motive of this paper is to represent technologies that can be redounding to detect credit card fraud. These technologies will help to diagnose the credit card fraud and give the acquiescent result. The use of these techniques will help to distinguish the credit card transactions generally into two types as legitimate and fraudulent transactions. These techniques are generally based on the Supervised and Unsupervised Learning. The approach on which we are working is based on Unsupervised, in which we train our network so that it is able to detect fraudulent transactions.
Authors
- Anuradha
Publication Details
- Journal
- Kaggle
- Published
- 2026-03-23
- DOI
- https://doi.org/10.34740/kaggle/dsv/15334478
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article