Using Big Data to Detect and Reduce Fraud

Fraud is a collaborative criminal issue that requires a collaborative response and so Big Data can have a significant role in enabling organisations to detect and prevent criminal activity.

Delegates of this master class will be introduced to the current fraud and cybercrime landscape which is having an impact to both public and private sector organisations worldwide. Through a series of interactive discussions delegates will learn how the proceeds of fraud is funding global criminal activity and understand the motivations behind the networks that are collaboratively causing disruption to websites, business operations, and critical infrastructure.

There are many challenges in ensuring that organisations are sufficiently equipped to deal with big data in the context of fraud prevention. From a legal and regulatory perspective there are complex considerations to understand when it comes to implementing solutions.

Working under the Chatham House rule, attendees will be encouraged to share experiences on various aspects including detection, prevention, tools and intelligence sharing. 

Why You Should Attend:  This master class is applicable to leaders within Fraud Risk Management, Money Laundering Risk Officers, IT security, Information Security, cyber security and operations, Chief Risk Officers, Chief Information Officers, Chief Technology Officers, Chief Training Officers, legal officers, criminal and forensic investigators. 

Attendees will benefit from understanding the core principles and issues surrounding the use of Big Data for fraud risk management and will leave with valuable knowledge on how to best implement fraud strategies that incorporate Big Data. Through group discussions and networking sessions attendees will also be empowered with the ability to collaborate with thought leaders in the field.