- Featurespace’s real-time ARIC™ Adaptive Behavioral Analytics anti-fraud and risk management platform available in Singapore for the first time
- Using world-leading technology first developed at Cambridge University, the firm will work with Singapore financial institutions to outsmart fraud and mitigate risk
- Solution meets the demands of Singapore’s Anti-Money Laundering and Countering the Financing of Terrorism Industry Partnership (ACIP) data analytics initiative
- UK firm realising global expansion after a successful US$32.3m funding round
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Featurespace, a leading international provider of Adaptive Behavioral 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 behavior 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 Behavioral Analytics technology, which helps financial institutions stop fraud faster. Millions of Singapore’s 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 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.
"Singapore’s 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.”
Singapore currently has one of the highest rates of card fraud in the world. To combat this, in 2017 Singapore’s financial industry came together to commit to data analytics as a means of fighting financial crime.
Led by the Singapore Police Force and the Monetary Authority of Singapore, the Anti-Money Laundering (AML) and Countering the Financing of Terrorism (CFT) Industry Partnership (ACIP), it noted that as many as nine out of 10 cases where fraud was identified resulted in declined transactions, known as a false positive, and smart analytics should be implemented in Singapore in an attempt to reduce these numbers.
Featurespace’s real-time ARIC™ platform uses Adaptive Behavioral Analytics to self-learn and continuously responding to new customer data. By understanding the behavior 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 company’s software capabilities.
Adopting Data Analytics Methods for AML CFT
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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 University’s 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