Go ahead and build advanced systems to progress but pay heed to the other side of the coin too. Thankfully, tech experts are coming up with solutions to counter the problem of ‘evolved’ crimes. UOB in collaboration with the Singaporean bank has widened the application of the new AI-based anti-money laundering technology (AML). The most impressive and useful feature of this technology is that it can help to identify suspicious transactions.
According to the sources, UOB has crafted this technology in such a manner that it can go one step further and give a clue about the chain parties involved in certain financial fraudulent undertakings. The technology as UOB says works by using two AML risk dimensions that is name screening and transaction monitoring to track an average of more than 5700 suspicious transactions monthly.
The AI system first picks out suspicious transactional activities followed by a thorough investigation under the bank’s compliance officer. After the relevant investigation has been carried out, the report of the case is referred to the concerned authorities to cease the criminal activities as early as possible.
The technology has been quite fruitful in delivering results as the positive prediction rate stands at 96% especially in terms of the most suspicious cases demanding immediate and detailed inquiries. In fact, criminals can be deceptive and pose as customers. Fortunately, the system is also efficient enough to filter details of 60,000 accounts to decide whether the global regulatory watch lists have them on their hit list.
The way forward from here is as UOB puts it is to increase the computational powers and machine learning of the system so that the detection capacities are upgraded over time. It can be achieved successfully as the model adjusts itself according to the transactional activities, customer behavioral patterns, and profiles.