Simudyne has been featured in SC Magazine.
Excerpt
It is possible to reproduce fraud dynamics using virtual ‘agents’ within a simulated system. These simulated criminals can be analysed and the data can then be used to train real world AML detection systems.
This year scientists were able to share an image of a black hole for the very first time. We have understood the nature of these interstellar anomalies for more than a century, but we have never been able to see one. However, thanks to developments in hardware and software technologies, astronomers can now shed light on this unique phenomenon.
It’s difficult to imagine that something 6.5 billion times the size of our Sun needed our most advanced technologies to even see but like many things, scale is not directly related the ease with which something is detected.
Take money laundering for example. The United Nations Office on Drugs and Crime and the IMF estimates the amount of money laundered globally annually is roughly US$ 2 trillion (£1.575 billion), or five percent of global GDP – yet existing technology fails to identify even a small percentage of this illegal activity. Worse, we don’t even know enough to say how much has been missed. It is an estimate of an unknown.
Why is this? And crucially what technological developments are needed to improve the detection of this financial black hole?
