How to do more with less: insights from Avyse Financial Crime Conference
Team Xapien had a great time at Avyse Partners Financial Crime Conference this week. We’re proud to have sponsored an event full of productive conversations and practical insights.
Our CCO Chris Green spoke alongside Barry Good, Head of Financial Crime & MLRO at the Bank of Ireland, Andy Caines, MLRO from DNB and Vladimir Petrov, Head of Financial Crime Governance at Danske Bank on the panel ‘How MLROs can do more with less‘.
The panel discussed how increased regulatory scrutiny has come at a time of economic pressures for most organisations, meaning that Money Laundering Reporting Officers (MLROs) are having to meet ever-higher compliance standard with restricted resources. So how can firms address this need?
Barry Good from the Bank of Ireland spoke about how the pandemic-induced shift to work from home has enabled firms to hire remote workers, often based outside of big cities like London and Dublin where talent is more expensive due to the higher cost of living. This can result in big cost savings.
But that doesn’t really address the root cause of the constraints. The “pain point” that all panellists raise was the increasing amount of manual research that firms were having to hire teams of analysts to do. The problem is that highly skilled (and therefore expensive) individuals were being hired to do hours worth of research work. This pain is particularly severe when false positive rates are at 90-95% on most automated many risk flagging solutions, meaning that hours of highly skilled analyst time is spent screening out false positives.
This calls for a new approach. Rather than turning away from automation and becoming more reliant on human investigators, automated solutions need to get a whole lot better. And they can. The latest advances in Artificial Intelligence, Natural Language Processing and cloud computing have combined to bring a new solution to the market place.
Xapien uses all of these technologies to find and collect data points from across the internet from sanctions screening lists to Wikileaks, blogs and media sites. By using this vast array of sources and reading all the content with understanding, using advanced natural language processing, the tool is able to distinguish between different individuals, entities and risky or non-risky events and affiliations, just like a human can, only at incredible speed and scale.
“Two days of work now takes 30 minutes.” – Senior Due Diligence Specialist, Cambridge University
When met with the overwhelming quantity of information available to analysts and researchers in today’s digital world, automation is the only way that firms can do more with less.
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