Transaction Anomalies

The main business reasons for improving credit transaction anomaly detection is to enhance control and monitoring of payments, alert operations teams of anomalies for further investigation and analysis of the cause of the anomaly, to stop outlier payments before they are sent to the beneficiary, help detect malfunctions instantly and to improve the evaluation of the success rate of payments. Singapore is a hub for trade finance connecting with many foreign players and this research could have a large relevance for many industries and a positive economic relevance for Singapore. Global trade finance, e.g. global value of trade finance transactions is about USD 9 trillion / 90% of trade finance is processed by 13 banks globally. In addition, illicit finance flows to and from 148 Developing Countries in 2006-2015 are estimated to be worth 100’s billions of dollars with some countries having over 40% of total trade and there is an estimated mis-invoicing of around 1 trillion USD in Asia alone. With only a 1% improvement on this project to finding mis-invoicing earlier in the transaction cycle, over USD 9 billion could be saved in opportunity cost due to money held incorrectly. 

This project will contribute to this problem area by exploring what quantum computing can do that is different from current classical approaches, provide algorithms that will likely be able to improve on finding anomalies in the future, show results on simulators and current quantum hardware detailing what future quantum hardware will be need in order to be of use to the industry.