Data mining techniques in financial fraud detection

Data mining techniques in financial fraud detection PDF Author: Rohan Ahmed
Publisher: GRIN Verlag
ISBN: 3668709270
Category : Computers
Languages : en
Pages : 18

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Book 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.

Data mining techniques in financial fraud detection

Data mining techniques in financial fraud detection PDF Author: Rohan Ahmed
Publisher: GRIN Verlag
ISBN: 3668709270
Category : Computers
Languages : en
Pages : 18

Get Book Here

Book 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.

Encyclopedia of Organizational Knowledge, Administration, and Technology

Encyclopedia of Organizational Knowledge, Administration, and Technology PDF Author: Khosrow-Pour D.B.A., Mehdi
Publisher: IGI Global
ISBN: 1799834743
Category : Business & Economics
Languages : en
Pages : 2734

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Book Description
For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.

Data Mining for Intelligence, Fraud & Criminal Detection

Data Mining for Intelligence, Fraud & Criminal Detection PDF Author: Christopher Westphal
Publisher: CRC Press
ISBN: 1420067249
Category : Computers
Languages : en
Pages : 450

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Book Description
In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isn‘t worth much unless we can determine that these systems are being effectively and responsibly employed.Written by one of the most

2018 4th International Conference on Computing Communication and Automation (ICCCA)

2018 4th International Conference on Computing Communication and Automation (ICCCA) PDF Author: IEEE Staff
Publisher:
ISBN: 9781538669488
Category :
Languages : en
Pages :

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Book Description
School of Computing Science & Engineering of Galgotias University Uttar Pradesh, invites you to associate with us for upcoming conference, ICCCA2018, a two day International Conference to be held on December 14 15, 2018 ICCCA2018 International Conference on Computing, Communication and Automation team with pleasure invites you to contribute with original research papers, to this blind and peer reviewed conference

Fraud Analytics

Fraud Analytics PDF Author: Delena D. Spann
Publisher: John Wiley & Sons
ISBN: 1118282736
Category : Business & Economics
Languages : en
Pages : 176

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Book Description
Proven guidance for expertly using analytics in fraud examinations, financial analysis, auditing and fraud prevention Fraud Analytics thoroughly reveals the elements of analysis that are used in today's fraud examinations, fraud investigations, and financial crime investigations. This valuable resource reviews the types of analysis that should be considered prior to beginning an investigation and explains how to optimally use data mining techniques to detect fraud. Packed with examples and sample cases illustrating pertinent concepts in practice, this book also explores the two major data analytics providers: ACL and IDEA. Looks at elements of analysis used in today's fraud examinations Reveals how to use data mining (fraud analytic) techniques to detect fraud Examines ACL and IDEA as indispensable tools for fraud detection Includes an abundance of sample cases and examples Written by Delena D Spann, Board of Regent (Emeritus) for the Association of Certified Fraud Examiners (ACFE), who currently serves as Advisory Board Member of the Association of Certified Fraud Examiners, Board Member of the Education Task Force of the Association of Certified Anti-Money Laundering Specialists ASIS International (Economic Crime Council) and Advisory Board Member of the Robert Morris University (School of Business), Fraud Analytics equips you with authoritative fraud analysis techniques you can put to use right away.

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques PDF Author: Bart Baesens
Publisher: John Wiley & Sons
ISBN: 1119133122
Category : Computers
Languages : en
Pages : 406

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Book Description
Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

Machine Learning Applications for Accounting Disclosure and Fraud Detection

Machine Learning Applications for Accounting Disclosure and Fraud Detection PDF Author: Papadakis, Stylianos
Publisher: IGI Global
ISBN: 179984806X
Category : Business & Economics
Languages : en
Pages : 270

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Book Description
The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.

Investigative Data Mining for Security and Criminal Detection

Investigative Data Mining for Security and Criminal Detection PDF Author: Jesus Mena
Publisher: Butterworth-Heinemann
ISBN: 9780750676137
Category : Business & Economics
Languages : en
Pages : 476

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Book Description
Publisher Description

Artificial Intelligence Systems and the Internet of Things in the Digital Era

Artificial Intelligence Systems and the Internet of Things in the Digital Era PDF Author: Abdalmuttaleb M.A Musleh Al-Sartawi
Publisher: Springer Nature
ISBN: 3030772462
Category : Technology & Engineering
Languages : en
Pages : 536

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Book Description
This book brings together intelligence systems and the Internet of Things, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI and IoT to develop future strategies and to achieve sustainability goals. EAMMIS 2021 was organized by the Bridges Foundation in cooperation with the Istanbul Medeniyet University, Istanbul, Turkey, on March 19–20, 2021. EAMMIS 2021 theme was Artificial Intelligence Systems and the Internet of Things in the digital era. The papers presented at the conference provide a holistic view of AI education, MIS, cybersecurity, blockchain, Internet of Ideas (IoI), and knowledge management.

Applications of Artificial Intelligence in Engineering

Applications of Artificial Intelligence in Engineering PDF Author: Xiao-Zhi Gao
Publisher: Springer Nature
ISBN: 9813346043
Category : Technology & Engineering
Languages : en
Pages : 922

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Book Description
This book presents best selected papers presented at the First Global Conference on Artificial Intelligence and Applications (GCAIA 2020), organized by the University of Engineering & Management, Jaipur, India, during 8–10 September 2020. The proceeding will be targeting the current research works in the domain of intelligent systems and artificial intelligence.