If robust data analytics programs existed 20 years ago, would Enron, WorldCom or the countless other major corporate fraud scandals ever have reached the magnitude they did? Would they have occurred at all? Using effective data analytics as part of an organization’s fraud management program can reduce a fraud scheme’s average duration from 18 months to mere weeks or, in some cases, eliminate it. More importantly, a robust fraud data analytics program can be the strongest deterrent in an organization.
This session will introduce you to the techniques currently being used by leading data analytics programs to detect fraud. It will also address how visualization can help us analyze data and communicate our results. Finally, it will cover the evolution of data analytics to artificial intelligence (AI). You will also walk through a real-world case study where AI solved significant challenges with labor, the chain of custody, quality of evidence and more. You will go from the whistleblower complaint to the conclusion of the case and examine the analytics and AI used throughout.
You will learn how to:
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Cybercrime and Social Engineering
Cybercrime is the No. 1 fraud threat in today’s technology-reliant world. Organisations pay large sums for cyber protection and expertise, but cybercrime continues to occur and is increasing not decreasing. Why? Cyber experts often focus on the technology, while hackers and fraudsters have a wide array of methods they use, not all technology based, and frequently they include social engineering. If organisations do not address their cyber protection programs with this in mind, they are still at risk of a breach regardless of how sophisticated their protection is. This session will look at real-world case studies where technology breaches were the direct result of social engineering, and you will learn what every organisation should be doing to prevent this from happening to them.
You will learn how to: