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UBS partners with PredictX to forecast travel spend and monitor ongoing expenditure

Today PredictX, the predictive analytics and data intelligence specialists, announces that UBS, the global financial services company, has deployed its AI and predictive analytics platform to build more accurate travel budget forecasts and provide more contemporary and complete spend reporting.

UBS has recently rolled out a new global travel strategy to make the business function more efficient. The global travel team is now focused on building accurate budget forecasts that recognise individual or team’s seasonality, identifying and curtailing leakage, ensuring compliance with supplier agreements, and providing more accurate spend reports to division heads. PredictX’s platform will be at the heart of providing this unprecedented intelligence.

PredictX has collected and rationalised five years of travel data from across the business, including data from travel management companies, direct vendors, corporate credit cards and expense management systems. This will then enable the team to create an accurate prediction of total required trip cost, incorporating anticipated week-by-week spend fluctuations based on individual teams’ seasonal activity trends. This prediction is then balanced against actual spend, including both travel costs and credit card expenditure on the trip, enabling proactive management of costs with true calculations of Total Cost per Trip (TCT), while protecting the bottom line.

UBS deployed PredictX’s automated travel cost analysis platform to go beyond its previous static and out-of-date business intelligence capability, which was impacting its ability to resource and plan travel spend effectively. Because UBS’ business travel data is typically stored across multiple sources, many of which are external, previous attempts to aggregate and reconcile data were a largely manual process. This made it impossible to deliver timely information. Reports on travel spend could only ever be based on eight-week-old data at best, preventing stakeholders from making informed decisions on travel plans or from preventing non-compliant or excessive spend.

“For us accurate and transparent data analytics is mission critical, especially in a high spend category such as travel,” said Mark Cuschieri, Global Travel Lead at UBS.

“Previously, it was impossible for our category managers to make proactive, vital business decisions on future spending. Typically, we were receiving static reports on trip spend eight weeks post-event. Slow data consolidation and single layer reporting just couldn’t provide the insight needed - and certainly not in a way that would support our new global travel strategy and business requirements. With PredictX, we can be far more precise with our preferred suppliers when negotiating new rates.”

Additional benefits of the predictive analytics platform include being able to have better informed negotiations with suppliers. Complete and unequivocal historic spend data allows for accurate predictions of likely future spend, allowing mutually-beneficial rates to be agreed.

“UBS and PredictX have worked together tirelessly to fix the traditional retrospective business intelligence approach that had come to be accepted. Unstructured data that requires time-consuming manual analysis to uncover business value is just not acceptable, especially within a high-spend department such as travel,”

said Keesup Choe, CEO of PredictX. “Machine learning and predictive analytics in contrast have the potential to uncover insights that would otherwise remain invisible, immeasurably improving the accuracy of forecasting and real-time decision-making. In business functions that inherently generate and rely on enormous amounts of data - and there are few that do not fit this description this degree of analysis has now become so prevalent that it is practically an expectation.”

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