Artificial Intelligence and Fraud Detection

37 Pages Posted: 5 Jan 2021

See all articles by Yang Bao

Yang Bao

Shanghai Jiao Tong University (SJTU) - Antai College of Economics and Management

Gilles Hilary

Georgetown University - Department of Accounting and Business Law

Bin Ke

National University of Singapore

Date Written: November 24, 2020

Abstract

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 of big data and artificial intelligence, new opportunities have arisen in using advanced machine learning models to detect fraud. This chapter provides a comprehensive overview of the challenges in detecting fraud using machine learning. We use a framework (data, method, and evaluation criterion) to review some of the practical considerations that may affect the implementation of ma-chine-learning models to predict fraud. Then, we review select papers in the academic literature across different disciplines that can help address some of the fraud detection challenges. Finally, we suggest promising future directions for this line of research. As accounting fraud constitutes an important class of fraud, we will discuss all of these issues within the context of accounting fraud detection.

Keywords: Artificial Intelligence, Faraud detection

Suggested Citation

Bao, Yang and Hilary, Gilles and Ke, Bin, Artificial Intelligence and Fraud Detection (November 24, 2020). Available at SSRN: https://ssrn.com/abstract=3738618 or http://dx.doi.org/10.2139/ssrn.3738618

Yang Bao

Shanghai Jiao Tong University (SJTU) - Antai College of Economics and Management ( email )

No.1954 Huashan Road
Shanghai Jiao Tong University
Shanghai, Shanghai 200030
China

Gilles Hilary (Contact Author)

Georgetown University - Department of Accounting and Business Law ( email )

McDonough School of Business
Washington, DC 20057
United States

Bin Ke

National University of Singapore ( email )

Mochtar Riady Building, BIZ 1, #07-53
15 Kent Ridge Drive
Singapore, 119245
Singapore
+6566013133 (Phone)

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