Read Data mining techniques in financial fraud detection

Data mining techniques in financial fraud detection

Rohan Ahmed

4.9/5 (12120 ratings)

Description:Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data mining techniques in financial fraud detection. To get started finding Data mining techniques in financial fraud detection, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 20

Format: PDF, EPUB & Kindle Edition

Publisher: Grin Verlag

Release: 2018

ISBN: 3668709289

Description: Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data mining techniques in financial fraud detection. To get started finding Data mining techniques in financial fraud detection, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Special Offer | $0.00

Special Offer! | $0.00

Data mining techniques in financial fraud detection

Data mining techniques in financial fraud detection

More Books

Fraud Detection in White-Collar Crime

Fraud Detection in White-Collar Crime