Trade Finance Fraud Detection Project in Dual Use Goods with Machine Learning and Visual Analytics

Traydstream has developed three core technology solutions that are set to disrupt global trade finance. A Trade Finance document review by an expert typically takes between 2-3 hours or as much as between 10 and 45 days between the four involved parties i.e. a buyer, a seller and a bank representing each of these.

Traydstream has reduced (currently) a single review to less than 20 minutes. If all four parties used the Traydstream Platform concurrently, then such a saving, even if rounded up to 1 hour and calculated against a 10 day timeframe, would amount to 99.6% reduction or almost 100 times faster.

Traydstream's disruptive ambitions do not end there. The company now wishes to advance its technology by developing a cutting edge software solution in collaboration with Swansea University to prove that it is possible to detect trade finance fraud using human interpretable machine learning and visual analytics in the complex area of Dual Use Goods (DUGs). Current manual paper based practice is resource consuming and often inconsistent. According to the Royal United Services Institute (RUSI) there is a real threat to international security that proliferators of trade finance are able to obtain the component parts of highly regulated and controlled items such as biological or chemical weapons, in pursuit of war or terrorist activities. This project brings together our experience in trade finance and Swansea's expertise in deep learning and visualisation to tackle a complex issue, particularly in face of the trade and regulatory uncertainties associated with Brexit.

A successful outcome from this project has a real potential to disrupt this global practice and place the region and the UK at the forefront of trade finance fraud detection and prevention.