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Transformation of AML promises rich rewards

AML Modernisation will involve more data, more analytical sophistication and more automation. At a time of change in the industry; transformation of AML promises rich rewards.
AML TransformationIncreased regulatory scrutiny and new obligations around beneficial ownership are commanding greater senior management attention, especially in larger financial institutions. New beneficial ownership rules have been introduced to help crack down on legitimate corporate vehicles, such as trust, companies, foundations, partnerships, etc, which have in certain conditions been misused for illicit purposes  as a way to disguise and convert the proceeds of crime before introducing them into the financial system to circumvent anti-money laundering (AML) and counter-terrorist financing (CFT) measures.
88% of executives polled on AML report that their boards of directors are committed to shrinking compliance risk; while 59% of banks expect to increase spend on AML systems in the coming year.
Clearly, the will and determination are there – and they need to be. The nature of illicit fund flows  is such that an accurate measure of the amounts involved is impossible – with various authorities reckoning sums in the trillions. The National Crime Agency estimates £100bn a year of corrupt foreign money is laundered in the UK alone.
AML platforms installed over the last decade are ageing – with many organisations now planning replacements. There is more competition for staff – especially highly skilled staff – and a desire to ensure that operations teams are working efficiently. But limitless funds are not available and additional investments are always scrutinised in a world of competing priorities.

AML Modernisation

AML modernisation will involve more data, more analytical sophistication and more automation. Data from the new beneficial ownership registries will be needed to assess risk – especially in complex corporate structures. A transition from a pure rules-based approach into one that applies a well controlled use of machine learning techniques will improve alert quality. As Big Data goes mainstream, data volume becomes an ally, not an adversary, in combatting financial crime. Big Data reduces up-front infrastructure costs, hugely speeds up processing times and enables AML analytics teams to trial new detection typologies across large datasets. Finally, smarter automation will eliminate repetitive and labour-intensive steps, freeing up those scarce operations teams to work on the greatest risks.
AML modernisation occurs at a time of change in our industry. National Financial Intelligence Units (FIUs) are themselves growing in sophistication, looking to update suspicious activity reporting standards and cascade changes down to financial institutions. And, of course, new beneficial ownership rules are upon us – looking to make an impact on that trillion dollar problem.
Learn more about the state of play in money laundering - How Dirty Money Moves
John Dalton, VP, Product Management for Financial Crime January 11, 2017