AML Technology to heighten monitoring efforts in finance
Big data and other data technologies have long been pivotal in Singapore’s development within our financial services industry as we gradually transition ourselves into a smart city. With the data analytics sector said to add USD 1 billion to the Singapore economy by 2017, Know Your Customer (KYC), Know Your Customer’s Customer (KYCC) and Anti-Money Laundering (AML) prevention efforts have now taken on an even bigger significance. This is further complemented with not only robust controls to detect illicit funds, but also stringent penalties of non-compliance iterated by Monetary Authority of Singapore (MAS).
As Singapore commits itself to become a world leading financial centre, expectations around KYC and AML compliance will only continue to escalate. As such, the adoption of smart technology may be the solution to future challenges ahead.
Why AML Tech?
The recent 1MDB scandal may have highlighted a pressing need to tackle money laundering in the South-East Asian market. Yet, banks are still squandering £2.7bn a year because of outdated AML systems. These are costs that could be saved through the adoption of machine learning and big data technologies.
According to WealthInsight, they predicted that global spending on AML compliance will hit £6.4bn billion this year with potential savings of a mere £2.7bn.
Currently, headcount costs represent around 80% of the AML budget for banks as many of these tasks are still being done manually by relatively large teams. While complex cases may still require human oversight, many of the lower-risk checks could easily be handled by RegTech solutions, thus assisting banks in lowering their costs and improving headcount reduction efforts. RegTech also reduces the need for manual checks and processing, minimising occurrences of human error. Additionally, banks can manipulate their mountainous resource of big data whilst future-proofing their organisation as an increasing number of banks start to adopt AI.
OCBC Singapore and AML Tech
Singapore’s OCBC Bank has piloted two fintech solutions from a pair of start-ups as it looks to combat money laundering and terrorism financing via AI.
The two firms involved – BlackSwan Technologies and Silent Eight – were part of OCBC’s second fintech accelerator programme, Open Vault.
Both companies used AI to conduct research on individuals and entities suspected of illegal financing. This is done by searching for information on individual profiles, mapping how suspicious transactions may be linked to one another and if these transactions may be fraudulent or illegal.
Silent Eight helps to automate the desktop research process by enabling analysts to digitally scan internet search engines, news sites, internal and external databases to put together the dossier within a minute. For example, AI enables the system to filter out irrelevant information such as individuals with identical names when a search is being done for a particular individual.
BlackSwan Technologies uses AI to analyse the suspicious transactions, mapping them to a network of related transactions in an attempt to identify possible connections with other individuals or companies which may be atypical or previously unknown. This can simplify the task of analysts and at the same time, provide leads to follow up on.
Future trends in AML Tech
1) Supervised machine learning vs Unsupervised machine learning
Supervised machine learning – when a platform learns from a feedback loop with a human user. When an employee receives an alert for a transaction, they are able to identify and inform the platform on why the particular activity is not suspicious. This information can be used later within the same platform that will later be used as part of a pattern recognition in an attempt to continually evolve and thereby decrease the number of false positives generated.
On the other hand, unsupervised machine learning detects out-of-the-norm behaviour that may not be caught by knowledge-based rules or human review, as well as new types of unusual behaviour.
“This is important in anti-money laundering where new money laundering techniques are invented and organisations need to detect and respond extremely quickly,” Luca Primerano, Head of Strategy at Fortytwo Data adds.
According to Shong Ye Tan, Digital business and Risk assurance Leader at PwC, “Most organisations we see have infrastructure that has been in place for a while. Given the additional requirements, many of them are assessing whether this infrastructure is meeting their needs, very often via audits.”
2) IT specialists in demand
Compliance professionals with specialist knowledge in financial crime compliance, AML and experience in investigation and research will continue to have a high demand amidst tougher bank regulations. The industry may expect more contractual roles with the growing appeal of the gig economy amongst highly-skilled professionals in Singapore.
Now, highly skilled AML and financial-crime experts are highly sought after especially with a global focus on terrorist financing and an increase of complexity on new rules and regulations. Thus, the need for senior compliance professionals especially those with relevant experience will only become more apparent.
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Source: Banking Exchange, Banking Technology, Forbes, GTReview, Lexis Nexis, CAN