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Quantexa Syneo Revolutionizes Risk Detection To Enable 80% Faster Investigations and Over 75% Fewer False Positives

Quantexa, the data and analytics software company pioneering Contextual Decision Intelligence, has today launched the latest version of its Contextual Monitoring and Investigations solution to set a new revolutionary standard in Financial Crime & Fraud detection and investigation.

Quantexa Syneo provides financial institutions (FIs) with an all-in-one solution for the monitoring and investigation of financial crime and fraud. Quantexa Syneo automates time-intensive manual data gathering and analysis, empowers investigations with intuitive visualization tools for exploration and decision making, and proactively improves enterprise-wide risk detection.

Mitigating risk with Contextual Monitoring

With an industry average rate of 95% false positive alerts, traditional monitoring systems are internal looking, reactive systems which only look at transactions, behaviors and individuals/businesses in isolation. Quantexa has pioneered a new approach called contextual monitoring, which connects internal intelligence across the enterprise with external data. This allows FIs, for the first time, to gain automated knowledge of counterparties or their customers’ customer, creating a holistic view of risk. This game changing approach enables a single coordinated and pre-emptive response to financial crime and fraud threats. It moves the needle from a “reactive detection first, investigate later” approach, to enabling the ability to research threats using actionable intelligence to proactively find previously unknown risk.

Underpinned by Quantexa’s Dynamic Entity Resolution and advanced analytics platform technology, the Quantexa Syneo solution:

• Enhances detection rates with advanced models that leverage network-based context to reduce false positives by more than 75% and generate more meaningful alerts for investigation.

• Enriches alerts for investigators, who can assess the wider context and identify mitigating or escalating risk factors, leading to faster, trusted decisions.

• Automates time-intensive manual data gathering and analysis, freeing up investigators to focus on real risk.

• Uses the enriched data compiled by investigators post-alert for all customer pre-alert generation, finding new risk and removing false positives.

• Empowers teams with powerful visualization tools to make more accurate risk decisions, reducing investigation times by up to 80%.

With a new easy to use data exploration tool called Quantexa Explorer, investigators can make sense of big data and uncover hidden patterns and trends to find the needle in the haystack.

Revolutionizing financial crime investigations

Using this new approach to Financial Crime investigations, Standard Chartered Bank has transformed its investigative capabilities. Global Co-Head of FinCrime Compliance at Standard Chartered, David Howes, said: “What would have taken us manually six or seven weeks with some attendant risks to errors in identification, we are able to execute literally in a matter of hours using the Quantexa platform”.

Discussing Quantexa’s innovative approach, Alexon Bell, Chief Product Officer, said, “In the old world of traditional monitoring, systems take a one-dimensional approach to risk detection, looking at internal behaviors in isolation and unable to look externally to see the bigger picture.  In the new world of contextual monitoring, a holistic picture is created between internal data, external data, and their connections. By building context, Quantexa Syneo transforms the monitoring and investigation of financial crime and fraud threats by alleviating current problems of high false positives, low disclosure rates and not being able to find new AML risk.”

Vishal Marria, CEO of Quantexa commented: “Financial crime and fraud have devastating impacts on our society and the risks are constantly changing. Organizations need to rethink the use of traditional rules-based monitoring systems which are inflexible and incapable of dealing with the complexity and scale of today’s enterprise data demands.”