Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis.
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …

The great losses caused by financial fraud have attracted continuous attention from
academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus …

Over the past few decades, fraud has been increasingly prevalent, with large businesses
like Satyam, Enron, and WorldCom making headlines for their deceptive financial reporting …

Fraud exists in all walks of life and detecting and preventing fraud represents an important
research question relevant to many stakeholders in society. With the rise in big data and …

Abstract Machine learning offers empirical methods to sift through accounting datasets with
a large number of variables and limited a priori knowledge about functional forms. In this …

With the advent of flexible electronics and sensing technology, hydrogel-based flexible
sensors have exhibited considerable potential across a diverse range of applications …

Develo** models to detect financial statement fraud involves challenges related to (1) the
rarity of fraud observations,(2) the relative abundance of explanatory variables identified in …

The paper contributes to a growing body of empirical work on regulatory technology by
proposing machine learning models to detect fraud in financial markets. The recent spate of …

This study aims to develop a better Financial Statement Fraud (FSF) detection model by
utilizing data from publicly available financial statements of firms in the MENA region. We …

Objective: Financial fraud has been a big concern for many organizations across industries;
billions of dollars are lost yearly because of this fraud. So businesses employ data mining …