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JULY 2013
IBM
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Current Systems Will not Suffice So why are many banks falling behind the curve? Basically, traditional AML transaction monitoring systems generate alerts based on patterns and rules which can quickly become outdated, as criminals find new and sophisticated ways to evade the system. In addition, many of these systems generate high numbers of False Positive alerts that will tie up analysts’ time working on alerts that are not likely to generate Suspicious Activity Reports (SARs)
This means that the investigation teams are under a lot of pressure to maintain high levels of diligence and consistency as they sift through False Positives to apply objective – and subjective – judgement to the alerts. Several major banks employ over 2000 resources to analyse such alerts. The imperative of ensuring consistency of decisioning and governance is, therefore, paramount.
As organisations have grown and merged over time, internal fractures have occurred which has led to a duplication of data and technology used to tackle financial crime. It is the financial crime analysts who therefore struggle with huge amounts of information and, as a result, crimes slip through the cracks and go undetected. Such fragmented approaches to AML challenge the integrity of an organisation, but history shows that unless these risks turn into a crisis very little will be done to renew the systems and processes currently in place.
Making the Haystack Smaller & the needle Bigger AML transaction-monitoring systems may be able to provide some useful information into the nature of financial crimes, but only if the system can make connections and recognise patterns in the data. This makes the analysis and interpretation of data key to preventing future crimes. IBM’s recent experience with a major banking institution has driven the development of a robust, flexible solution that combines predictive analytics, case management, advanced visual analysis and investigation with the mining of unstructured text and data to reduce False Positive alerts and resolve entities across multiple business units and geographies. IBM i2 Anti-Money Laundering Solution is
different in that it complements existing Transaction Monitoring functionality as it unlocks the intelligence in AML data, allowing users to simultaneously capture and import massive amounts of data from multiple sources into a central analysis repository This provides an extra layer of enriched intelligence to the AML process, thereby empowering analysts to uncover patterns and trends that would otherwise go undetected. This means the needle in the haystack is now bigger and easier to detect. The IBM solution allows analysts to gather data from disparate, unstructured sources (social media, biometrics and criminal databases) and visualise the connections making it easier to present their findings and report in a common language to law enforcement agencies.
Moreover, IBM’s AML solution is helping make the haystack smaller. Almost 40% of the output from traditional monitoring systems can be assigned a ‘Low Priority’ status, allowing analysts to concentrate on a lower number of False Positives which allows companies to enjoy increased efficiencies and cost savings.
Additionally, used to complement an incumbent sanctions screening process, IBM i2 systems can be deployed to reduce False Positives on legitimate transactions as part of the sanction screening process. Organisations can therefore move closer to restoring both regulator and client faith in the sector.
Preventing Crime By using IBM i2 technology together with the Predictive Analytics functionality integrated in IBM’s AML solution, companies can make the critical step from the detection of financial crimes towards prevention. The enriched data provided, in addition to traditional analysis, can be fed back by means of a learning loop to enhance algorithms and rules on which the transaction monitoring systems are based. Therefore, the overall system can be maintained at a more pro-active state and is able to detect newer attempts to perpetrate financial crimes. More importantly, erecting stronger barriers to financial crimes deters criminals and ensures that they seek paths of less resistance
However, technology is not the ultimate panacea. It requires human intelligence to be part of the detection and analysis systems and take the critical decision of which transactions should be investigated. This confirms the value of the analysts’ role and the ability to share findings with regulators and law enforcement agencies.
As the financial services sector comes under increasing scrutiny, banks need to demonstrate that full measures have been put in place to prevent financial crimes. With IBM i2’s investigative capabilities, banks can demonstrate that they are moving beyond traditional tools and are using the same rigour and diligence that is applied by law enforcement agencies. All 43 police forces in the UK use IBM i2 technology in some capacity for crime detection.
the Path of Right Compliance With today’s market volatility and increased pressure from regulators to detect and prevent financial crime, organisations can easily find themselves guilty of doing the bare minimum to comply. It would therefore be prudent to consider a longer term view, and whether an integrated and more holistic approach to data analytics would improve the quality of financial crime intelligence, whilst reducing costs. The synergies, when doing so, can create significant opportunities for operational improvement with the consequent reduction in AML risk. LM
About the Author Richard Collard joined IBM as part of the 2009 acquisition of enterprise software company, ILOG. Richard draws on a business-based career with major global fraud analytics
organizations and specializes in the provision of fraud detection solutions and consulting for credit/debit card issuers and for Anti-Money Laundering.