Credit card fraud is a broad term for theft and fraud committed using or involving a payment card, such as a credit or debit card, as a fraudulent source of funds in a transaction. The purpose may be to obtain goods without paying or obtaining unauthorized funds from an account. Credit card fraud is also a compliment to identity theft. According to the US Federal Trade Commission, while the identity theft rate had remained stable in the mid-2000s, it increased by 21 percent in 2008. However, credit card fraud, which Most people associate with identity theft, a percentage of all identity theft complaints for the sixth consecutive year.
Although the incidence of credit card fraud is limited to about 0.1% of all card transactions, this has resulted in huge financial losses as fraudulent transactions have been large transactions of value. In 1999, out of 12 billion transactions annually, approximately 10 million - or one out of every 1200 transactions - turned out to be fraudulent. In addition, 0.04% (4 out of 10,000) of all active monthly accounts were fraudulent. Even with the tremendous volume and increased value in credit card transactions since then, these ratios have remained the same or have declined due to sophisticated fraud detection and prevention systems. Today's fraud detection systems are designed to prevent a twelfth of all processed transactions that still translate into billions of dollars in losses.
In the decade to 2008, overall credit card losses have been 7 basis points or less (ie losses of $ 0.07 or less per $ 100 of transactions). In 2007, fraud in the UK was estimated at £ 535 million.
Credit Card Fraud Detection Techniques
1. Decision tree
The idea behind this technique is that of a tree of similarity created using the logic of the decision tree. In this case, a tree of similarity is defined recursively; Nodes are labeled with the use of attribute names, edges are labeled using attribute values, and then there are sheets, which contain an intensity factor that is defined as the proportion of the number of transactions that satisfy the described conditions. The main advantage of this method of fraud detection is that it is easy to implement, understand and display. However, there are disadvantages when you are forced to check each transaction one by one. However, over the years, trees of similarity have been able to deliver tangible results. Therefore, it is an effective method when it comes to fraud detection.
2. Genetic algorithms and a range of additional algorithms
In most cases, algorithms are recommended as predictive methods or means of fraud detection. Most algorithms are created to establish logical rules that classify credit card transactions into suspicious and non-suspicious classes. Basically, this method tends to follow the example in the scoring process. This method of detecting credit card fraud has proven to deliver results when it comes to giving credible home insurance data. It can be a more efficient method when it comes to detecting and combating credit card fraud. This technique also incorporates a range of methods that are used to predict any suspicious behavior.
3. Grouping Techniques
There are two main grouping techniques that are used to detect behavioral fraud. Peer group analysis is a system that allows the identification of accounts that behave differently from each other at any time, particularly when they were behaving in the same way previously. These accounts are indicated as suspicious. Fraud analysts can then proceed to investigate such discrepancies. The assumption in these pooling techniques is that if the accounts behave the same for a certain period of time and then a certain account begins to behave significantly differently, the account holder must be notified. Some signs of suspicious behavior are a sudden high-dollar transaction and a high frequency of use of a credit card.
4. Neural Networks
Neural networks are also recommended as effective methods of detecting credit card fraud. The only problem with this method is that all the data has to be grouped by the type of account to which it belongs.
