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Data mining techniques in financial fraud detection

by Rohan Ahmed
Save 15% Save 15%
Current price ₹1,885.00
Original price ₹2,205.00
Original price ₹2,205.00
Original price ₹2,205.00
(-15%)
₹1,885.00
Current price ₹1,885.00

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Book cover type: Paperback
  • ISBN13: 9783668709287
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Grin Verlag
  • Publisher Imprint: Grin Verlag
  • Publication Date:
  • Pages: 20
  • Original Price: USD 22.5
  • Language: English
  • Edition: N/A
  • Item Weight: 37 grams
  • BISAC Subject(s): Languages / General and Data Science / Data Analytics

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.

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