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Data mining techniques in financial fraud detection - Softcover

 
9783668709287: Data mining techniques in financial fraud detection

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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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Ahmed, Rohan
Published by Grin Verlag, 2018
ISBN 10: 3668709289 ISBN 13: 9783668709287
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Rohan Ahmed
Published by GRIN Verlag Jun 2018, 2018
ISBN 10: 3668709289 ISBN 13: 9783668709287
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 20 pp. Englisch. Seller Inventory # 9783668709287

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Rohan Ahmed
Published by GRIN Verlag, 2018
ISBN 10: 3668709289 ISBN 13: 9783668709287
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783668709287

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 20 pp. Englisch. Seller Inventory # 9783668709287

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Published by GRIN Verlag, 2018
ISBN 10: 3668709289 ISBN 13: 9783668709287
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Taschenbuch. Condition: Neu. Data mining techniques in financial fraud detection | Rohan Ahmed | Taschenbuch | 20 S. | Englisch | 2018 | GRIN Verlag | EAN 9783668709287 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 113973995

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