Identification of fraudulent financial statements through a multi-label classification approach
| Year of publication: |
2024
|
|---|---|
| Authors: | Tragouda, Maria ; Doumpos, Michael ; Zopounidis, Constantin |
| Published in: |
Intelligent systems in accounting, finance & management. - New York, NY [u.a.] : Wiley, ISSN 2160-0074, ZDB-ID 2379344-2. - Vol. 31.2024, 2, Art.-No. e1564, p. 1-19
|
| Subject: | corporate financial fraud | data mining | falsified financial statements | fraud diamond | multi-label classification | Data Mining | Data mining | Betrug | Fraud | Bilanzdelikt | Accounting fraud | Klassifikation | Classification | Bilanzanalyse | Financial statement analysis | Jahresabschluss | Financial statement | Wirtschaftskriminalität | Economic crime |
-
Fraud detection in financial statement : a study using Beneish algorithm
Sankar, B.P. Bijay, (2024)
-
Detecting accounting fraud in companies reporting under US GAAP through data mining
Papík, Mário, (2022)
-
Fraud detection for financial statements of business groups
Chen, Yuh-Jen, (2019)
- More ...
-
Corporate governance and financial fraud detection
Tragouda, Maria, (2023)
-
"Known unknowns" : reducing digital inequalities in the silver economy
José, Mário L. D., (2024)
-
Evaluating the importance of ESG criteria : a multicriteria approach
Eskantar, Marianna, (2023)
- More ...