CashFlows selects Featurespace to protect online payments

Source: Featurespace

Featurespace, the world-leading Adaptive Behavioural Analytics fraud prevention company, has entered into an agreement with CashFlows, the fast-growing, innovative provider of merchant payment solutions, to deliver an embedded enterprise fraud and risk management solution.

Featurespace’s real-time, machine learning platform, ARIC, will be integrated into CashFlows issuing platform and core acquiring business. The ARIC platform will replace CashFlows’ existing system with the latest risk management technology, providing real-time transaction monitoring and business decision making.

This strategic partnership is aimed at increasing card acceptance rates for CashFlows’ merchants' customers and will provide greater security and privacy for consumers in their online transactions.

Featurespace’s machine learning fraud prevention platform will bolster CashFlows’ merchant on-boarding capabilities and will provide visibility and analytics across its merchant portfolio. The ARIC platform detects individual anomalies in behaviour to automatically evaluate risk and identify fraud in real-time, constantly analysing and adapting to new events and behaviour.

Neil Graham, CEO at CashFlows, commented:

“I’m delighted that CashFlows will be working with Featurespace. They are an important strategic partner, as we continue to enhance our Financial Crime Detection and Risk Management capabilities.

“Featurespace are at the forefront of their industry, challenging the conventions of an ever more complex landscape. This is an instrumental relationship that will undoubtedly greatly assist CashFlows in maximising payment success for our customers and ensuring that we continue to be a safe place for our customers to do business.”

Martina King, CEO at Featurespace, commented:

“We are thrilled to have been chosen as CashFlows’ partner following a competitive selection process - two great Cambridge-based companies working together to protect customers against fraud.”

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