The fraud taxonomy in financial reports in the brazilian stock market

The fraud taxonomy in financial reports in the brazilian stock market

Purpose: To explore the types of fraud in financial reports that occur in publicly traded Brazilian companies. Methodology: The Sanctioning Proceedings (Processos Administrativos Sancionadores - PAS) of the Brazilian Securities and Exchange Commission (Comissão de Valores Mobiliário - CVM) were...

Full description

Saved in:

Bibliographic Details
Main Authors:	Noel Kentinus Olokodana, Rodrigo de Souza Gonçalves, Monize Ramos do Nascimento
Format:	Article
Language:	Portuguese
Published:	Universidade Federal do Rio Grande do Norte 2025-01-01
Series:	Revista Ambiente Contábil
Subjects:	Taxonomy, Fraud in Financial Reports, B3.
Online Access:	https://periodicos.ufrn.br/ambiente/article/view/38664
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A taxonomia de fraudes em relatórios financeiros no mercado acionário brasileiro
by: Noel Kentinus Olokodana, et al.
Published: (2025-01-01)

Financial statement fraud based on Hexagon Fraud Approach
by: Prima Apriwenni, et al.
Published: (2023-09-01)

The effect of political will, information technology, and the quality of financial reporting information on fraud prevention
by: Haliah, et al.
Published: (2025-01-01)

The Effect of the Fraud Triangle and Sharia Compliance Disclosure on Financial Statement Fraud in Indonesian Islamic Banks
by: Dhea Marella Aulia, et al.
Published: (2024-12-01)

MEASURES TO COUNTERACT MODERN METHODS OF FRAUD AGAINST THE POPULATION
by: Maria S. Tikhomirova, et al.
Published: (2024-07-01)

Fraud triangle dimensions on academic fraud behavior
by: Mulyati Akib, et al.
Published: (2023-09-01)

The role of internal auditors in preventing financial fraud in the Republic of Serbia
by: Jeremić Nebojša, et al.
Published: (2023-01-01)

The Effect of Internal Control, Professionalism, Pressure, and Anti-Fraud Awareness on Fraud Prevention
by: Veronika Rasdiana Toja, et al.
Published: (2024-12-01)

FRAUD RISK IN TIMES OF CRISIS AND THE DEVELOPMENT OF ITS MITIGATION TOOLS
by: Agnieszka Skoczylas-Tworek
Published: (2022-12-01)

ANALYSIS OF THE RISK OF FRAUD IN PROJECTS FINANCED FROM EUROPEAN FUNDS
by: Mihaela SUDACEVSCHI, et al.
Published: (2023-06-01)

Cyber security and need to change the model of monitoring fraud and financial crime
by: Radić Nikola
Published: (2020-01-01)

Fraud in a digital society in the context of social change
by: A. Yu. Sergeyev, et al.
Published: (2023-04-01)

Cloud-Based Transaction Fraud Detection: An In-depth Analysis of ML Algorithms
by: Ali Alhchaimi
Published: (2024-06-01)

Cryptocurrencies as a subject of financial fraud
by: Małgorzata Kutera
Published: (2022-01-01)

Some problems of investigating street fraud and the ways to solve them
by: K. D. Zaiats
Published: (2018-12-01)

Credit card fraud detection through machine learning algorithm
by: Agyan Panda, et al.
Published: (2021-09-01)

IMPACT OF FORENSIC ACCOUNTING SERVICES ON PREVENTING AND DETECTING FRAUD IN NIGERIAN DEPOSIT MONEY BANKS
by: Abdul-Hakeem Shuaib, et al.
Published: (2023-11-01)

Nature of viruses and the radical change in viral taxonomy
by: V. V. Makarov, et al.
Published: (2021-11-01)

FORENSIC ACCOUNTING AND PUBLIC PROCUREMENT FRAUD PREVENTION: EVIDENCE FROM OSUN STATE, NIGERIA
by: Aderemi Olalere ADEBAYO, et al.
Published: (2024-10-01)

Peculiarities of the investigation of frauds disguised as civil legal relations
by: K. D. Zaiats, et al.
Published: (2023-07-01)

Multi-Relational Graph Representation Learning for Financial Statement Fraud Detection
by: Chenxu Wang, et al.
Published: (2024-09-01)

A systematic review of AI-enhanced techniques in credit card fraud detection
by: Ibrahim Y. Hafez, et al.
Published: (2025-01-01)

Fraud Research in Economic Entities – A Conceptual Perspective
by: Alexandru Adrian TUNSU
Published: (2025-02-01)

Harnessing artificial intelligence and machine learning for fraud detection and prevention in Nigeria
by: Oluwaseun Isaac Odufisan, et al.
Published: (2025-03-01)

Does gambling preference level affect occupational fraud behavior?—Evidence from a survey study in China
by: Shihua Huang, et al.
Published: (2025-02-01)

E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review
by: Abed Mutemi, et al.
Published: (2024-06-01)

MANAGING FRAUD IN CONTEMPORARY BUSINESS ENVIRONMENT, THE ROLE OF INFORMATION SECURITY MANAGEMENT: A STUDY OF QUOTED DEPOSIT MONEY BANKS (DMBs) IN NIGERIA
by: Onajero Kensington OHWO
Published: (2024-05-01)

Contract and Procurement Fraud Investigation Guidebook /
by: Piper, Charles E., 1957-
Published: (2017)

“fraude da locadora” e suas implicações no direito penal
by: Michele Kuchar Matte, et al.
Published: (2020-12-01)

Preventing fraud in crypto payments
by: Louise Damkjær Christensen
Published: (2025-03-01)

Analysis of Islamic Financial Articles Published in Scientific and Research Journals of Accounting and Finance: Content and Taxonomy Analysis
by: Hossein Rajabdorri
Published: (2022-05-01)

EVOLUSI TEORI FRAUD DAN RELEVANSINYA TERHADAP STRATEGI PENCEGAHAN KORUPSI DANA DESA
by: Satya Fauziah
Published: (2024-07-01)

RELEVANCE OF FORENSIC ACCOUNTING PROFESSIONAL CERTIFICATIONS ON FRAUD REDUCTION IN NIGERIAN DEPOSIT MONEY BANKS
by: Kamaluddeen Funsho Adisa IBRAHIM
Published: (2023-11-01)

Does the Occasion Justify the Denunciation?: a Multilevel Approach for Brazilian Accountants
by: Bernardo de Abreu Guelber Fajardo, et al.
Published: (2014-01-01)

Reinforced Cost-Sensitive Graph Network for Detecting Fraud Leaders in Telecom Fraud
by: Peiwen Gao, et al.
Published: (2024-01-01)

Encoding of Variant Taxonomies in TEI
by: Helena Bermúdez Sabel
Published: (2019-12-01)

Paying for crime: frauds in DPVAT insurance and their impacts on society
by: Beatriz Peres Lopes, et al.
Published: (2022-01-01)

Coming to Accounts: Fraud and Muckraking in Charles W. Chesnutt’s The Marrow of Tradition
by: Mark David Kaufman
Published: (2013-11-01)

Data mining process for fraud detection in mobile communication
by: Jelena Mamčenko, et al.
Published: (2004-12-01)

Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention
by: Fawaz Khaled Alarfaj, et al.
Published: (2025-01-01)