A Comprehensive Survey of Data Mining-Based Accounting-Fraud Detection Research

By Shiguo Wang. 2010

127 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Anazida Binti Zainal
2. Mohd Aizaini Maarof
3. Aisha Abdallah

In Management Science and Operations Research

1. Anazida Binti Zainal
2. Mohd Aizaini Maarof
3. Aisha Abdallah

Citations in the corpus

• Deep Learning for Financial Applications : A Survey (2020, neutral): “[109], Phua et al.”
• Tool Learning with Foundation Models (2023, unknown): “, fraud detection (Wang, 2010)), users expect fast and accurate responses within milliseconds.”
• Fraud detection system: A survey (2016, methodology): “Wang, 2010; Richhariya, 2012; Ngai et al., 2011 Data mining and statistical techniques.”
• Data mining techniques and applications — A decade review (2017, background): “Fraud and other related crimes can be categorized to solve and detect through data mining [26].”
• A Review of Financial Accounting Fraud Detection based on Data Mining Techniques (2012, unknown): “Although the latest revision auditing standards is enlarging auditors‘ fraud detection responsibility, effective detecting accounting fraud has always been a problem for accounting profession [5].”