The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature

2011 ◽  
Vol 50 (3) ◽  
pp. 559-569 ◽  
Author(s):  
E.W.T. Ngai ◽  
Yong Hu ◽  
Y.H. Wong ◽  
Yijun Chen ◽  
Xin Sun
Keyword(s):  
Data Mining ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Review Of Literature ◽  
Data Mining Techniques ◽  
Classification Framework ◽  
Academic Review

A complete literature review on financial fraud detection applying data mining techniques

2016 ◽  
Vol 3 (4) ◽  
pp. 336
Author(s):  
Palash Mandal ◽  
Animesh Mahata ◽  
Biswajit Biswas ◽  
Utpal Pal ◽  
Md. Asif Sarfaraj ◽  
...  
Keyword(s):  
Data Mining ◽  
Literature Review ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Data Mining Techniques

A complete literature review on financial fraud detection applying data mining techniques

2016 ◽  
Vol 3 (4) ◽  
pp. 336 ◽  
Author(s):  
Subhas Barman ◽  
Utpal Pal ◽  
Md. Asif Sarfaraj ◽  
Biswajit Biswas ◽  
Animesh Mahata ◽  
...  
Keyword(s):  
Data Mining ◽  
Literature Review ◽  
Fraud Detection ◽  
Financial Fraud ◽  
Data Mining Techniques

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

A Classification Framework for Data Mining Applications in Criminal Science and Investigations

2020 ◽  
pp. 277-293
Author(s):  
Mahima Goyal ◽  
Vishal Bhatnagar ◽  
Arushi Jain
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Mining Techniques ◽  
Road Map ◽  
Classification Framework ◽  
Challenges And Opportunities ◽  
Crucial Information ◽  
Tools And Techniques ◽  
Day By Day ◽  
Mining Tools

The importance of data analysis across different domains is growing day by day. This is evident in the fact that crucial information is retrieved through data analysis, using different available tools. The usage of data mining as a tool to uncover the nuggets of critical and crucial information is evident in modern day scenarios. This chapter presents a discussion on the usage of data mining tools and techniques in the area of criminal science and investigations. The application of data mining techniques in criminal science help in understanding the criminal psychology and consequently provides insight into effective measures to curb crime. This chapter provides a state-of-the-art report on the research conducted in this domain of interest by using a classification scheme and providing a road map on the usage of various data mining tools and techniques. Furthermore, the challenges and opportunities in the application of data mining techniques in criminal investigation is explored and detailed in this chapter.

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