SWIFT is asking banks to ramp up their anti-fraud systems by June this year or face expulsion from the international bank messaging co-operative. Here is how technology can help meet SWIFT's tight deadline and protect banks against internal and external fraud, writes Pascal Aerens.
Artificial intelligence and machine learning will change the face and shape of compliance and risk management departments within a decade, slashing their size and massively boosting their detection rates, writes Joël Winteregg
What's blockchain? This article introduces the blockchain, presents what it is in the light of its initial deployment in the Bitcoin project, key problems solved by blockchain, and the blockchain operation principle.
A number of high-profile – and high cost – cyber heists that leveraged the international Swift network to execute large-scale fraudulent transfers prove that banks around the world need multiple layers of defense especially against insider threats and external cybercrime threats.
The rapid growth of MOBILE banking through phones and tablets reflects the central role that these devices now play in the lives of consumers around the world. It also highlights some of the growing challenges that banks face in handling their customers’ migration to new banking channels.
Leveraging big data to meet your regulatory and fraud challenges is complex. Your big data initiative needs to be defined, managed and maintained. And just being able to capture the data isn’t enough. Basically, it’s about being able to make sense of the data you gather. You need to know your challenges and make use of the right technology built to target them.
Trying to fight fraud by screening transactions is a losing battle. It’s already happened. A better place to start is with an understanding of who is committing these crimes. This understanding gives organizations the opportunity to implement fraud mitigation strategies that follow fraud patterns to spot red flags and potentially catch thieves in the act.