• Corpus ID: 8491844

Survey on Credit Card Fraud Detection Methods

@inproceedings{Tripathi2012SurveyOC,
  title={Survey on Credit Card Fraud Detection Methods},
  author={Krishnavijay Tripathi and Mahesh A. Pavaskar},
  year={2012}
}
Due to a rapid advancement in the electronic commerce technology, the use of credit cards has increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of credit card fraud also rising. Financial fraud is increasing significantly with the development of modern technology and the global superhighways of communication, resulting in the loss of billions of dollars worldwide each year. The fraudulent transactions are scattered with genuine… 

Figures from this paper

A Review on Credit Card Fraud Detection Techniques

A review of different methods utilized as a part of different credit card fraud detection systems based on Artificial Intelligence, Fuzzy Logic, Neural Network, Logistic Regression, Naive Bayesian, Bayesian Genetic programming and so on.

Credit Card Fraud Detection Using Decision Tree Induction Algorithm

This research is totally concerned with credit card application fraud detection by performing the process of asking security queries to the persons intricate with the transactions and as well as by eliminating real time data faults.

Credit card fraud detection using fuzzy logic and neural network

F fuzzy database is used to detect credit cards fraud and the results indicates that the ANN method is 33% more accurate than the fuzzy logic.

Credit Card Fraud Detection System Based on User Based Model with GA and Artificial Immune System

The user based model is an adaptive self-learning based on the historical details of transactions that helps in reducing the massive financial losses to the cardholder and card issuer or the banks.

A Comparative Study and Performance Analysis of ATM Card Fraud Detection Techniques

This study aims to review alternative techniques that have been used in fraud detection and compare and analyze these techniques that are already used in ATM card fraud detection, to build a hybrid approach for developing some effective algorithms which can perform properly on fraud detection mechanism.

An intelligent credit card fraud detection approach based on semantic fusion of two classifiers

Experimental results indicate that the proposed model can enhance the classification accuracy against the risk coming from suspicious transactions, and gives higher accuracy compared to traditional methods.

Survey on Methods for Credit Card Fraud Detection Systems

Technology has developed tremendously. The technology has been developed in such a way that it keeps in mind the new inventory will be comfortable and will be easy to use for the human beings. One

A bio-inspired credit card fraud detection model based on user behavior analysis suitable for business management in electronic banking

  • S. Darwish
  • Computer Science
    J. Ambient Intell. Humaniz. Comput.
  • 2020
Experimental findings show that the suggested model can improve the precision of ranking against the danger of suspect operations and provide higher accuracy relative to traditional techniques.

Hybrid Methods for Credit Card Fraud Detection Using K-means Clustering with Hidden Markov Model and Multilayer Perceptron Algorithm

The focus of this paper is to model a fraud detection system that would attempt to maximally detect credit card fraud by generating clusters and analyzing the clusters generated by the dataset for anomalies.

Survey on Various Types of Credit Card Fraud and Security Measures

The aims of this paper are discussing various types of credit card fraud and how to reduce the fraud by taking security measures and using alternative data mining algorithms.

References

SHOWING 1-10 OF 39 REFERENCES

Analysis on credit card fraud detection methods

A survey of various techniques used in credit card fraud detection mechanisms is presented and each methodology is evaluated based on certain design criteria.

A review of Fraud Detection Techniques: Credit Card

This paper shows how data mining techniques can be combined successfully to obtain a high fraud coverage combined with a low or high false alarm rate.

Analysis on Credit Card Fraud Detection Techniques: Based on Certain Design Criteria

A survey of various techniques used in credit card fraud detection and evaluates each methodology based on certain design criteria is presented.

Fraud Detection of Credit Card Payment System by Genetic Algorithm

The aim is to develop a method of generating test data and to detect fraudu- lent transaction with this algorithm, an optimization technique and evolutionary search based on the principles of genetic and natural selection, heuristic used to solve high complexity computational problems.

Novel Artificial Neural Networks and Logistic Approach for Detecting Credit Card Deceit

Classification model based on Artificial Neural Networks (ANN) and Logistic Regression (LR) are developed and applied on credit card fraud detection problem.

Identifying online credit card fraud using Artificial Immune Systems

This paper investigates the effectiveness of Artificial Immune Systems (AIS) for credit card fraud detection using a large dataset obtained from an on-line retailer and suggests that AIS algorithms have potential for inclusion in fraud detection systems but that further work is required to realize their full potential in this domain.

Credit Card Fraud Detection Using Neural Network

This paper tries to detect fraudulent transaction through the neural network along with the genetic algorithm to show that artificial neural network when trained properly can work as a human brain, though it is impossible for it to imitate the human brain.

Credit Card Fraud Detection Using Hidden Markov Model

This paper model the sequence of operations in credit card transaction processing using a hidden Markov model (HMM) and shows how it can be used for the detection of frauds and compares it with other techniques available in the literature.

Artificial immune system for fraud detection

A case-based genetic artificial immune system for fraud detection (AISFD) is proposed, a self-adapted system designed for credit card fraud detection that can perform online learning with limited time and cost, and update the capability of fraud detection in the rapid growth of transactions and commerce activities.