BAE Systems today launches Match Exclusion, a new algorithm engine within its flagship NetReveal Transaction Filtering solution, a major update to the capabilities of its Anti-Money Laundering (AML) and Watch List Management (WLM) solutions.
According to one study by Celent, banks typically report between 50 and 65 per cent of their analysts’ time is spent doing low level tasks of data collection, cleaning, and aggregation. Some banks placed this figure at 80 per cent of an investigator’s time[1]. Reducing the volume of false alarms to be sorted by hand can dramatically improve the effectiveness of investigators.
BAE Systems Match Exclusion uses a combination of algorithms and rules to distinguish between legitimate and suspicious transactions, reducing the number of false positive alerts between 40 and 60 per cent.
Neal Watkins, Chief Product Officer at BAE Systems Applied Intelligence said:
“Money laundering is how criminals disguise money generated from human trafficking, fraud and slavery into appearing as legitimate funds - damaging society and defrauding citizens from their hard earned money. Helping financial institutions detect and prevent more of this activity is a moral imperative.
“But all too often banks and other institutions are hampered by the need to sift through false alerts, costing investigators crucial minutes, hours and days. Cutting down on the number of false alerts frees up investigators to look into crimes. The net result is that banks and other financial institutions can then be more effective at stopping money being laundered through their systems and breaking down the criminal supply chain.”
Numerous major banks are already deploying BAE Systems Match Exclusion.
• By configuring just 20 rules within a Transaction Filtering solution, a major bank in Northern Europe saw a 50 per cent reduction in false positive alerts.
• A second major financial services company in Continental Europe specialising in corporate and retail banking applied 15 Match Exclusion rules to the top 20 per cent of its alerts and managed to remove 83 per cent of 24,000 alerts.
According to a recent study by Dow Jones and SWIFT[2], over 70 per cent of AML professionals are concerned about an increase in alerts, an issue made worse by staff shortages and inadequate, insufficient or outdated technology.
By using the Transaction Filtering solution with Match Exclusion, financial institutions will be able to improve detection effectiveness, increase investigator efficiency and realise transformational cost savings.
Match Exclusion is a complementary feature that is used to define exclusion rules for recurring false positives. Alerts based on known recurring false positive matches are still generated but marked as an exclusion. Depending on customer expectation, alerts can be removed, immediately closed or just hidden from the main investigator screens. The system will not only mark the alert, it will also log what rules were used to exclude the match. The log allows for maximum traceability - all data is retained and can be retrieved for audit - but means that only the most relevant alerts are presented to, and pursued by, investigators.
Joan McGowan, Senior Analyst at Celent said:
“Banks are between a rock and a hard place when it comes to false positives. AML operations at financial institutions have become increasingly complex, with some large banks admitting to 99 per cent false positive alerts across their watchlist screening and AML systems. If institutions are to reduce the burden on their investigation teams they must rethink their approach and move from an operational to a strategic play and embrace new technologies.”