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

Traydstream开发了三种核心技术解决方案，将颠覆全球贸易融资。专家对贸易融资文件的审查通常需要2-3小时，或多达10 - 45天，涉及四方，即买方，卖方和代表他们各自的银行。Traydstream已经将（目前）一次审查减少到不到20分钟。如果所有四方同时使用Traydstream平台，那么这样的节省，即使舍入到1小时，并以10天的时间框架计算，也将减少99.6%，或者几乎快了100倍。Traydstream颠覆性的野心还不止于此。该公司现在希望通过与斯旺西大学合作开发尖端软件解决方案来推进其技术，以证明在复杂的双重用途物品（DUGs）领域使用人类可解释的机器学习和视觉分析来检测贸易融资欺诈是可能的。目前基于手工纸张的实践是消耗资源的，而且经常不一致。英国皇家三军联合研究所（RUSI）表示，贸易融资的扩散者能够获得生物或化学武器等受到高度监管和控制的物品的组成部分，以从事战争或恐怖活动，这对国际安全构成了真正的威胁。该项目汇集了我们在贸易融资方面的经验和斯旺西在深度学习和可视化方面的专业知识，以解决一个复杂的问题，特别是面对与英国脱欧相关的贸易和监管不确定性。该项目的成功成果有可能颠覆这一全球惯例，并将该地区和英国置于贸易融资欺诈检测和预防的前沿。

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.