Role of Data Science and Data Analytics in Forensic Accounting and Fraud Detection

Author:

Odia James Osabuohien1,Akpata Osaheni Thaddeus1

Affiliation:

1. University of Benin, Nigeria

Abstract

The chapter examines the roles of data science and big data analytics to forensic accountants and fraud detection. It also considers how data science techniques could be applied to the investigative processes in forensic accounting. Basically, the current increase in the volume, velocity, and variety of data offer a rich source of evidence for the forensic accountant who needs to be familiar with the techniques and procedures for extracting, analysing, and visualising such data. This is against backdrop of continuous global increase in economic crime and frauds, and financial criminals are getting more sophisticated, taking advantage of the opportunities provided by the unstructured data constantly being created with every email sent, every Facebook post, every picture on Instagram, or every thought share on Twitter. Consequently, it is important that forensic accountants are constantly abreast with developments in data science and data analytics in order to stay a step ahead of fraudsters as well as address evolving vulnerabilities created by big data.

Publisher

IGI Global

Reference98 articles.

1. Accenture. (n.d.). Financial crime: Data science to the rescue. Accenture.com.

2. Detecting financial fraud using data mining techniques: A decade review from 2004 to 2015.;M.Albashrawi;Journal of Data Science : JDS,2016

3. Drivers of the Use and Facilitators and Obstacles of the Evolution of Big Data by the Audit Profession

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