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Machine Learning Applications for Accounting Disclosure and Fraud Detection

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Title: Machine Learning Applications for Accounting Disclosure and Fraud Detection
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.
Authors: Stylianos Papadakis, Alexandros Garefalakis, Christos Lemonakis, Christiana Chimonaki, Constantin Zopounidis
Resource Type: eBook.
Subjects: Corporations--Accounting--Data processing, Auditing, Internal--Data processing, Machine learning, Fraud--Prevention
Categories: BUSINESS & ECONOMICS / Accounting / Financial, BUSINESS & ECONOMICS / Accounting / General, COMPUTERS / Data Science / Machine Learning
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-epub
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 2708901
RelevancyScore: 1103
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1103.19409179688
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  Data: Machine Learning Applications for Accounting Disclosure and Fraud Detection
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  Data: 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.
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  Data: <searchLink fieldCode="AR" term="%22Stylianos+Papadakis%22">Stylianos Papadakis</searchLink><br /><searchLink fieldCode="AR" term="%22Alexandros+Garefalakis%22">Alexandros Garefalakis</searchLink><br /><searchLink fieldCode="AR" term="%22Christos+Lemonakis%22">Christos Lemonakis</searchLink><br /><searchLink fieldCode="AR" term="%22Christiana+Chimonaki%22">Christiana Chimonaki</searchLink><br /><searchLink fieldCode="AR" term="%22Constantin+Zopounidis%22">Constantin Zopounidis</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Corporations--Accounting--Data+processing%22">Corporations--Accounting--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Auditing%2C+Internal--Data+processing%22">Auditing, Internal--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Fraud--Prevention%22">Fraud--Prevention</searchLink>
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  Data: <searchLink fieldCode="ZK" term="%22BUSINESS+%26+ECONOMICS+%2F+Accounting+%2F+Financial%22">BUSINESS & ECONOMICS / Accounting / Financial</searchLink><br /><searchLink fieldCode="ZK" term="%22BUSINESS+%26+ECONOMICS+%2F+Accounting+%2F+General%22">BUSINESS & ECONOMICS / Accounting / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Machine+Learning%22">COMPUTERS / Data Science / Machine Learning</searchLink>
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RecordInfo BibRecord:
  BibEntity:
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      – Code: 657.0285631
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Corporations--Accounting--Data processing
        Type: general
      – SubjectFull: Auditing, Internal--Data processing
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Fraud--Prevention
        Type: general
    Titles:
      – TitleFull: Machine Learning Applications for Accounting Disclosure and Fraud Detection
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Stylianos Papadakis
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          Name:
            NameFull: Alexandros Garefalakis
      – PersonEntity:
          Name:
            NameFull: Christos Lemonakis
      – PersonEntity:
          Name:
            NameFull: Christiana Chimonaki
      – PersonEntity:
          Name:
            NameFull: Constantin Zopounidis
      – PersonEntity:
          Name:
            NameFull: Stylianos Papadakis
      – PersonEntity:
          Name:
            NameFull: Alexandros Garefalakis
      – PersonEntity:
          Name:
            NameFull: Christos Lemonakis
      – PersonEntity:
          Name:
            NameFull: Christiana Chimonaki
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          Name:
            NameFull: Constantin Zopounidis
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
            – D: 17
              M: 12
              Type: profile
              Y: 2020
          Identifiers:
            – Type: isbn-print
              Value: 9781799848059
            – Type: isbn-electronic
              Value: 9781799848066
            – Type: isbn-electronic
              Value: 9781799848073
          Titles:
            – TitleFull: Machine Learning Applications for Accounting Disclosure and Fraud Detection
              Type: main
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