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Machine Learning Applications for Accounting Disclosure and Fraud Detection
Machine Learning Applications for Accounting Disclosure and Fraud Detection
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Machine Learning Applications for Accounting Disclosure and Fraud Detection

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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.

Author Biography:

Constantin Zopounidis has been elected to the prestigious The Real Academia de Ciencias Económicas y Financieras (RACEF). He joins the ranks of Daniel Kahneman (Nobel Laureate), Romano Prodi, and Joseph E. Stiglitz (Nobel Laureate) who belong to this Institution. It is with pride and delight that we communicate that Professor Constantin Zopounidis, Editor-in-Chief of Operational Research and Editor of the renowned Handbook of Multicriteria Analysis, has been elected to the RACEF – Royal Academy of Economic and Finance Sciences of Spain. The Royal Academy of Economic and Finance Sciences of Spain was officially established in Spain, in 1958, but its roots can be traced back to the 18th century when King Ferdinand VI of Spain set up the Royal Private Board of Commerce. RACEF promotes the cooperation between researchers of the most important institutions and academies around the world, and seeks to advance the scientific knowledge and the existing decision and policy making practices in the fields of economics and finance. The members of RACEF include prestigious researchers, senior policy makers, and top executives from all over the world. Among others, the Academicians of RACEF include Valéry Giscard d'Estaing (former President of France), Romano Prodi (former President of Italy and the European Commission), José Ángel Gurría (Secretary General of OECD), as well as Nobel Prize laureates Robert Aumann, Daniel Kahneman, Finn Kydland, Eric Maskin, and Joseph Stiglitz (https://www.racef.es/ ). Also, Professor Zopounidis has been elected as Academician, in the Royal Academy of Doctors (Spain, June 2014). As and Academician, Constantin was elected to the Executive Committee of the International Society on Multiple Criteria Decision Making following a vote in which 677 people participated from all over the world. This Society brings together 2200 people from 100 countries. The term of office shall be for four years from 2015 to 2019. Professor C. Zopounidis was also honored by the same Society with Edgeworth - Pareto Award in 2013.
Release date NZ
October 30th, 2020
Audiences
  • Professional & Vocational
  • Tertiary Education (US: College)
Contributors
  • Edited by Alexandros Garefalakis
  • Edited by Christiana Chimonaki
  • Edited by Christos Lemonakis
  • Edited by Constantin Zopounidis
  • Edited by Stylianos Papadakis
Pages
270
Dimensions
216x279x16
ISBN-13
9781799857853
Product ID
34508889

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