Fraudulent financial statements (FFS) are the results of manipulating financial elements by
overvaluing incomes, assets, sales, and profits while underrating expenses, debts, or losses …

Financial statements are analytical reports published periodically by financial institutions
explaining their performance from different perspectives. As these reports are the …

Financial statement fraud (FSF) is a challenging issue in capital markets and severely affects
their overall health and stability. The effective prediction of FSF has become an urgent need …

This study aims to review the use of data analytics and artificial intelligence in fraud
detection to support internal audits. This study employs a qualitative method with a scoping …

Resumen Identifying Financial Statement Fraud (FSF) events is very crucial in text mining.
The researcher's community is mostly utilized the data mining method for detecting FSF. In …

The auditing of financial documents, historically a labor-intensive process, stands on the
precipice of transformation. AI-driven solutions have made inroads into streamlining this …

Data mining is an efficient methodology for uncovering and extracting information from large
databases, which is widely used in different areas, eg, customer relation management …

The risk of material misstatement is closely related to the types of audit opinions on the
financial statements for listed companies. Consequently, investors or Certified Public …

The aim of this study is to investigate financial fraud in companies listed on the Athens Stock
Exchange during the period 2008–18, in which a major economic crisis took place in …

By combining the similarity matching (SM) method with the utilities additives discriminates
(UTADIS) method, we propose a hybrid SM‐UTADIS approach to detect falsified financial …