Data Mining for Fraud Detection System
نویسنده
چکیده
INTRODUCTION As a conseguence of expansion of modern technology , the number and scenario of fraud are increasing dramatically. Therefore, the reputation blemish and losses caused are primary motivations for technologies and methodologies for fraud detection that have been applied successfully in some economic activities. The detection involves monitoring the behavior of users based on huge data sets such as the logged data and user behavior. The aim of this contribution is to show some data mining techniques for fraud detection and prevention with applications in credit card and telecommunications, within a business of mining the data to achieve higher cost savings, and also in the interests of determining potential legal evidence. The problem is very difficult because fraudsters takes many different forms and are adaptive, so they will usually look for ways to avoid every security measures.
منابع مشابه
Credit Card Fraud Detection using Data mining and Statistical Methods
Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...
متن کاملFDiBC: A Novel Fraud Detection Method in Bank Club based on Sliding Time and Scores Window
One of the recent strategies for increasing the customer’s loyalty in banking industry is the use of customers’ club system. In this system, customers receive scores on the basis of financial and club activities they are performing, and due to the achieved points, they get credits from the bank. In addition, by the advent of new technologies, fraud is growing in banking domain as well. Therefor...
متن کاملEnsemble Classification and Extended Feature Selection for Credit Card Fraud Detection
Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...
متن کاملMEFUASN: A Helpful Method to Extract Features using Analyzing Social Network for Fraud Detection
Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business. There is a need to propose methods to detect fraud accurately and fast. To achieve to accuracy, fraud detection methods need to consider both kind of features, features based on user level and features based o...
متن کاملIdentification of Fraud in Banking Data and Financial Institutions Using Classification Algorithms
In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...
متن کاملIdentification of Fraud in Banking Data and Financial Institutions Using Classification Algorithms
In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...
متن کامل