Featurespace launches international behavioural analytics fraud technology into Singapore

Featurespace, a leading international provider of Adaptive Behavioural Analytics for fraud detection and risk management, has launched its ground-breaking anti-fraud technology into the Singapore market.

Its technological platform “ which uses machine learning to detect anomalies in individual behaviour for fraud and risk management “ was first developed by world-leading computer scientists in the laboratories of Cambridge University. With the rise of more sophisticated fraud schemes, Featurespace uses its decades of experience to get out ahead and outsmart the criminals.

Martina King, Featurespace CEO, commented: Featurespace is the world leader in Adaptive Behavioural Analytics technology, which helps financial institutions stop fraud faster. Millions of Singapores citizens have been victim of many large-scale fraud attacks in the recent past “ by implementing machine learning technology, we can help banks and credit card providers outsmart the criminals and build a safer banking infrastructure.

Our financial services customer base is growing fast, and we are now are working with 17 banks across continental Europe, the UK, US and Latin America. Our technology is also being embedded by payment processors and merchant acquirers who use our real-time fraud prevention technology in their anti-fraud solutions.

“Singapores banking community has made it clear to us that it believes that the smart use of data is paramount in combatting and mitigating fraud. We look forward to sharing our proven capabilities and deep knowledge with the financial institutions of Singapore.

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Singapore currently has one of the highest rates of card fraud in the world. To combat this, in 2017 Singapores financial industry came together to commit to data analytics as a means of fighting financial crime.

In 2017, a report released by the Anti-Money Laundering and Countering the Financing of Terrorism Industry Partnership (ACIP), which is made up of Singapore’s banks, financial regulator and police, found that lenders are looking at using data analytics to detect suspicious transactions, because current systems mistakenly identify fraud, resulting in declined transactions. Further, DBS Group Holdings, one of Singapore’s three major banks, reported in 2018 that the current situation yields a false positive in nine out of 10 cases.1

Featurespaces real-time ARIC„¢ platform uses Adaptive Behavioural Analytics to self-learn and continuously responding to new customer data. By understanding the behaviour of each individual banking and credit card customer, ARIC identifies new and known attacks, and blocks fraud at the moment it occurs while accepting more genuine business. As such, ARIC reduces false positives, by 70%, increasing revenue and reducing customer friction.

Earlier this year, Featurespace raised US$32.3 million from a funding round to support its international expansion and continued development of the companys software capabilities.

ENDS

Headquartered in the U.K. and U.S. and with offices in Cambridge, London and Atlanta, Featurespace„¢ is the world-leader in fraud prevention and creator of the ARIC„¢ platform, a real-time AI machine learning software that risk scores transactions and other events in more than 180 countries.

Featurespace was created out of Cambridge Universitys Engineering Department, co-founded by world-renowned experts in applied statistics, the late Professor Bill Fitzgerald and Dave Excell, Featurespace CTO.

The ARIC platform combines adaptive behavioral analytics and anomaly detection to automatically identify risk and catch new attacks as they happen. The increased accuracy of understanding behavior strikes the balance between improving fraud detection and operational efficiencies, while also reducing the number of genuine transactions that would be incorrectly declined due to traditional rules by as much as 70 percent. www.featurespace.com

1Adopting Data Analytics Methods for AML CFT;

Featurespace
Matt Mills
Chief Commercial Officer
[email protected]
+44
(0) 1223 345940