Moneycorp appoints Leeds start-up for AI data strategy

International foreign exchange giant Moneycorp – which manages £35.5bn worth of transactions a year for consumers and businesses –is rolling out an artificial intelligence-driven data strategy to identify customer behaviours and improve the global brand’s online performance.

The new strategy has been devised by Third Foundation – a Leeds based start-up which only officially launched in October – and has already seen a 32% boost in customer acquisition performance.

The system, which has been built and is owned by Third Foundation, uses AI and machine learning to extract insight from media data to better understand customer-specific types of patterns – and where, when and what customers are buying or researching.

It is claimed that the tech further analyses customers’ lifetime interactions across on/offline channels to glean “critically intuitive insight” to shape future marketing strategy.

Additionally, Third Foundation insists its tech will help Moneycorp to enhance brand loyalty and drive market performance.

A Moneycorp spokesperson said: “Having such sophisticated technology on board means we’re able to spot extremely pivotal trends that we could never have managed previously.

“The insight we’ve gathered has helped us to drive our marketing strategy and make decisions based on patterns we simply couldn’t see before.”

Third Foundation was officially launched in October by three former directors of Leeds-based agency Home; ex-tech director Phillip Midwinter is chief technology officer, former managing director (digital) Michael Ward is CEO and ex-head of media tech Paul Roberts is director of media and adtech.

Ward said: “Moneycorp already has exceptionally capable marketing and data teams at its heart, so we knew exactly how we could complement that set-up and provide a complete experience for those it serves.

“Adapting to AI and ML should not only give Moneycorp an advantage within a really challenging sector but our ML-led predictive modelling also allows us to automate forecasting based on external events such as market volatility or political uncertainty.”