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Machine learning applications for ac...

Papadakis, Stylianos, (1970-)

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Machine learning applications for accounting disclosure and fraud detection

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning applications for accounting disclosure and fraud detection/ Stylianos Papadakis, Alexandros Garefalakis, Christos Lemonakis, Christiana Chimonaki and Constantin Zopounidis, editor.
其他作者:	Papadakis, Stylianos,
出版者:	Hershey, Pennsylvania :IGI Global, : 2021.,
面頁冊數:	1 online resource (xxi, 270 p.)
內容註:	Chapter 1. Corporate governance as a tool for fraud mitigation -- Chapter 2. Corporate sector fraud: challenges and safety -- Chapter 3. Corporate governance: introduction, roles, codes of corporate governance -- Chapter 4. Fraud governance and good practices against fraud -- Chapter 5. Theoretical analysis of creative accounting: fraud in financial statements -- Chapter 6. Operational risk framework and fraud management: a contemporary approach -- Chapter 7. Current trends in investment analysis -- Chapter 8. A study on various applications of data mining and supervised learning techniques in business fraud detection -- Chapter 9. Detection and prevention of fraud in the digital era -- Chapter 10. Downside risk premium: a comparative analysis -- Chapter 11. Impact of corporate fraud on foreign direct investment?: evidence from China -- Chapter 12. Outsourcing of internal audit services instead of traditional internal audit units: a literature review on transition from in-house to outsourcing -- Chapter 13. Machine learning techniques and risk management: application to the banking sector during crisis -- Chapter 14. Application of adaptive neurofuzzy control in the field of credit insurance -- Chapter 15. Prediction of corporate failures for small and medium-sized enterprises in Europe: a comparison of statistical and machine learning approaches.
標題:	Auditing, Internal - Data processing. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-4805-9
ISBN:	9781799848066 (ebk.)

Machine learning applications for accounting disclosure and fraud detection
Machine learning applications for accounting disclosure and fraud detection[electronic resource] /Stylianos Papadakis, Alexandros Garefalakis, Christos Lemonakis, Christiana Chimonaki and Constantin Zopounidis, editor. - Hershey, Pennsylvania :IGI Global,2021. - 1 online resource (xxi, 270 p.)

Includes bibliographical references and index.

Chapter 1. Corporate governance as a tool for fraud mitigation -- Chapter 2. Corporate sector fraud: challenges and safety -- Chapter 3. Corporate governance: introduction, roles, codes of corporate governance -- Chapter 4. Fraud governance and good practices against fraud -- Chapter 5. Theoretical analysis of creative accounting: fraud in financial statements -- Chapter 6. Operational risk framework and fraud management: a contemporary approach -- Chapter 7. Current trends in investment analysis -- Chapter 8. A study on various applications of data mining and supervised learning techniques in business fraud detection -- Chapter 9. Detection and prevention of fraud in the digital era -- Chapter 10. Downside risk premium: a comparative analysis -- Chapter 11. Impact of corporate fraud on foreign direct investment?: evidence from China -- Chapter 12. Outsourcing of internal audit services instead of traditional internal audit units: a literature review on transition from in-house to outsourcing -- Chapter 13. Machine learning techniques and risk management: application to the banking sector during crisis -- Chapter 14. Application of adaptive neurofuzzy control in the field of credit insurance -- Chapter 15. Prediction of corporate failures for small and medium-sized enterprises in Europe: a comparison of statistical and machine learning approaches.

"This book covers the application of machine learning models to identify "quality" characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. It uses machine learning techniques in accounting disclosure (i.e. corporate financial statements) and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment"--

ISBN: 9781799848066 (ebk.)Subjects--Topical Terms:

1641122
Auditing, Internal
--Data processing.

LC Class. No.: HF5668.25 / .M33 2021

Dewey Class. No.: 657.0285/631

Machine learning applications for accounting disclosure and fraud detection
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050 0 0 $a HF5668.25 $b .M33 2021
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245 0 0 $a Machine learning applications for accounting disclosure and fraud detection $h [electronic resource] / $c Stylianos Papadakis, Alexandros Garefalakis, Christos Lemonakis, Christiana Chimonaki and Constantin Zopounidis, editor.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2021.
300 $a 1 online resource (xxi, 270 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Corporate governance as a tool for fraud mitigation -- Chapter 2. Corporate sector fraud: challenges and safety -- Chapter 3. Corporate governance: introduction, roles, codes of corporate governance -- Chapter 4. Fraud governance and good practices against fraud -- Chapter 5. Theoretical analysis of creative accounting: fraud in financial statements -- Chapter 6. Operational risk framework and fraud management: a contemporary approach -- Chapter 7. Current trends in investment analysis -- Chapter 8. A study on various applications of data mining and supervised learning techniques in business fraud detection -- Chapter 9. Detection and prevention of fraud in the digital era -- Chapter 10. Downside risk premium: a comparative analysis -- Chapter 11. Impact of corporate fraud on foreign direct investment?: evidence from China -- Chapter 12. Outsourcing of internal audit services instead of traditional internal audit units: a literature review on transition from in-house to outsourcing -- Chapter 13. Machine learning techniques and risk management: application to the banking sector during crisis -- Chapter 14. Application of adaptive neurofuzzy control in the field of credit insurance -- Chapter 15. Prediction of corporate failures for small and medium-sized enterprises in Europe: a comparison of statistical and machine learning approaches.
520 3 $a "This book covers the application of machine learning models to identify "quality" characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. It uses machine learning techniques in accounting disclosure (i.e. corporate financial statements) and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment"-- $c Provided by publisher.
650 0 $a Auditing, Internal $x Data processing. $3 1641122
650 0 $a Corporations $x Accounting $x Data processing. $3 3510505
650 0 $a Fraud $x Prevention. $3 713062
650 0 $a Machine learning. $3 533906
700 1 $a Papadakis, Stylianos, $d 1970- $3 3510501
700 1 $a Garefalakis, Alexandros. $3 3510502
700 1 $a Lemonakis, Christos. $3 3510503
700 1 $a Chimonaki, Christiana. $3 3510504
700 1 $a Zopounidis, Constantin. $3 735231
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-4805-9