TSYS is a Global Payments company (NYSE: GPN) and a leading provider of seamless, secure and innovative solutions for payment card issuers, financial institutions and retail companies in approximately 80 countries worldwide.
TSYS succeeds by putting people and their needs at the heart of every decision to help them unlock payment possibilities. Continuing this mission is the catalyst that steered TSYS to partner with Featurespace to develop and implement a machine learning, transactional fraud scoring system fit for the future. The TSYS Foresight Score℠ is built with Featurespace’s proprietary Adaptive Behavioral Analytics engine at its core and combines statistical algorithms with advanced machine learning, that monitors individual transactions — one customer at a time — to deliver real-time decision capabilities.
The seemingly endless conflict of reducing market share of fraud and bringing down business risk without adding friction to the payment journey, was disrupted through the creation of the TSYS Foresight ScoreSM. This groundbreaking technology partnership between TSYS, a Global Payments Company, and Featurespace, the world leader in Adaptive Behavioral Analytics transformed a global card issuer’s fraud detection accuracy, significantly improving customer happiness and business performance.
An exclusive, intelligence-led case study collaboration between TSYS and Featurespace, details the volatility of consumer behavior experienced at the beginning of the global COVID-19 pandemic and demonstrates how the TSYS Foresight Score℠ powered by Featurespace, quickly pivoted, and performed as the pandemic emerged and progressed.
Capital One UK pioneered the TSYS Foresight Score℠ with Featurespace: an innovative, real-time fraud risk score providing enhanced customer card and payments protection – increasing fraud detection by 35%, while also reducing blocked cards by 47%. The machine learning approach – which uses Featurespace’s unique ARIC™ platform technology – understands and predicts individual customer behavior, even in new payment fraud areas such as online and contactless payments.