KUALA LUMPUR, July 13 -- Featurespace, the leading provider of Enterprise Financial Crime prevention technology for fraud and anti-money laundering, has filed two global patents that will enable new levels of customer protection in the financial industry.
The first patent is for Featurespace’s Automated Deep Behavioral Networks for the card and payments industry. Automated Deep Behavioral Networks are a deep neural network architecture of connections and updates that recognise and prevent significantly more fraud cases.
Deep neural networks have revolutionised areas such as image recognition and text understanding by creating specific architectures (connections and weights) designed to extract meaning from the underlying data presented to the network.
Meanwhile, Featurespace’s second patent is for Behavioral Anomaly Score, which identifies anomalies in individual customer behaviour without having any prior knowledge of contextual high-risk behaviour.
This technology appreciably amplifies the ability to identify when a person’s behaviour is out of character without any labelled data, according to a statement.
“The Automated Deep Behavioral Networks patent and associated technologies deliver the right levels of model performance the industry needs to decrease fraud and protect consumer accounts before attacks happen,” said Featurespace founder, Dave Excell.
“The fight against fraudsters and the organisations that commit financial crime on a large scale is challenging and ever-evolving.
“Technology, specifically machine learning will continue to be central in this fight and these two patents from Featurespace advance our leading market position and our capacity to help progressive financial institutions protect the consumer.”
Full public patent applications have been filed in the US, UK, EU and Patent Cooperation Treaty (PCT).
More details at www.featurespace.com.
-- BERNAMA
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