Contextual Monitoring: The New Standard for FinCrime and Fraud Detection and Investigations

As the cracks in the traditional approaches to financial crime and fraud detection and investigation deepen, a period of seismic disruption is underway – and Contextual Monitoring is at its forefront.
 

The ‘Old World’ Methods of Detection and Investigations Are Fraught with Challenges 

When it comes to detecting and investigating financial crime and fraud, traditional rules-based monitoring methods are no longer viable.  

Anti-Money Laundering (AML) is in a unique regulatory space, meaning that every alert generated by transaction monitoring (TM) systems has to be investigated. These systems look at transactions in isolation – if something is more than three standard deviations away from the norm or breaches a certain threshold for rules or scenarios, it triggers an alert. A human investigator then picks up the case and asks all the questions that the TM system should have asked: Who sent the money to my customer? And who is my customer sending money to?  The lack of this critical data means that 95% of these alerts turn out to be false positives.   

Similarly, fraud threats continuously evolve and having cross-channel intelligence in real-time is critical to the effectiveness of any response. Criminals do not respect organizational or jurisdictional boundaries so having connected view of customers, their digital journeys and their transactions is more important than ever before.

‘Old world’ approaches are too reactive and disconnected. As a result, financial institutions are prevented from seeing the bigger picture – and cannot find new risk. For investigations teams to shift from a reactive ‘detect and investigate’ process to a proactive approach to finding and disrupting financial crime, more relevant data or context is needed.  As context becomes core to effective detection and investigation, a Contextual Monitoring approach becomes the answer.  

Contextual Monitoring: The Next Generation of Financial Crime & Fraud Detection 

Unlike traditional monitoring systems, a contextual monitoring platform uses entity resolution to resolve counterparties and better understand the relationships between them by using Network Analytics or Graph Theory.  This platform continually asks the most pertinent questions such as – who is the originating counterparty and who is the beneficiary counterparty?, what do we know about them? – and by applying network analytics, determines whether the entity has any connection (direct or indirect) to criminal activity. Contextual monitoring essentially takes all the data collated manually post-alert generation by investigators on a subset of customers, and applies this at-scale to all customers and parties for detection.  This advanced ‘investigate to detect’ process leverages shared data and intelligence from law enforcement and police agencies, and signals a new way of tackling financial crime and fraud.

Context Creates a Holistic View Across Financial Crime and Fraud 

In recent years, there has been a new addition to the financial crime lexicon: FRAML encompasses an important trend particularly seen in financial services organizations – the coming together of Fraud and Anti-Money Laundering. 

Traditionally, the solutions for managing fraud and money-laundering have differed, similar to the intent of its criminals. A money launderer’s goal is to fly under the radar and move money without being detected; a fraudster’s is to defraud the bank of money. While their outcomes differ, both go about achieving it using the same tools and Modus Operandi. 

There are therefore many benefits to taking a holistic approach to FRAML. As fraud is a predicate offence for money laundering, the data collected in a contextual monitoring platform to investigate and detect AML can also be used to uncover fraud. By creating a true single view of data, reducing false positives, and automating time-intensive manual data gathering, contextual monitoring is revolutionizing investigations to deliver faster, more accurate risk decisions. 

Why now for Contextual Monitoring

Following the FinCEN leaks of 2020 – where leaked documents involving $2tn of transactions revealed how some of the world’s biggest banks allowed criminals to transfer dirty money across the globe – now is the time to leverage the power of contextual monitoring. One of the biggest criticisms that emerged from the leaks was that banks lacked the intelligence to know who they were doing business with. But with contextual monitoring, visibility across all counterparties is now possible.

Of course, if a customer or their counterparties transactions are in-line with industry expectations, there are unlikely to be any links to criminal wrongdoing. But when a transaction volume fails to match up with an organization’s outward appearance, entity resolution and network analytics can provide an opportunity to delve deeper into the risk. Unlike platforms that only have the capability to identify ‘Known Known’ risks, the use of external intelligence means contextual monitoring platforms can also uncover both ‘Known Unknowns’ and ‘Unknown Unknown’ risks. It’s this unique perspective that is transforming the AML and Fraud and investigation landscape.

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Contextual Monitoring: A New Standard for Financial Crime & Fraud Detection 

Quantexa is pioneering change, setting a new standard for financial crime and fraud detection. As criminals grow smarter, so too must the platforms used to monitor and detect financial crime and fraud. Quantexa’s innovative contextual monitoring platform, Syneo is designed to disrupt the current landscape by offering a new ‘investigate to detect’ approach based on actionable intelligence. Syneo is a complete, end-to-end platform for system-led risk detection including monitoring, alert management, and investigations. In time sensitive situations, the platform’s capability to return a set of results in a matter of hours rather than weeks is truly game changing.  

Contextual monitoring platforms like Syneo provide all the intelligence you need to see the full picture of risk in one-integrated platform. The future of Financial Crime and Fraud detection and investigations starts here.