Title

The Impact of Data Analytics in Corporate Fraud Detection

Publication Type

Audio

Year

9-2014

Abstract

The amount of data that an organisation uses and stores is growing at an unprecedented pace. Much of this information is largely untagged and unstructured data. This means not only that large quantities of potentially useful data is getting lost, but that fraud, bribery, corruption, money laundering and other white-collar criminal activities may remain either very difficult to spot or, even worse, undetected.

With the incidence of corporate fraud on the rise in Singapore and globally, the real world implications of early fraud detection are too profound to be ignored.

The research of Associate Professor Gary Pan from SMU’s School of Accountancy delves into fraud analytics with an emphasis on mining unstructured data which may include employees’ emails, telephone conversations and many other sources. Simply put, his work involves using digital analysis techniques to look into accounting transactions with the aim of detecting irregular patterns.

In this podcast, Associate Professor Pan shares his insights on corporate fraud and why it is vital that businesses tap on the power of unstructured data.

Disciplines

Accounting

Language

eng

Format

audio