Case Study: Paf achieves 40% fewer deny rates for trustworthy players with TransUnion TruValidate

Predictive Analytics in Gaming Identifies Trustworthy Customers

Paf, the cause-driven online gaming company, needed a better way to identify trustworthy customers without adding friction to account creation, login, and payments. Working with TransUnion, Paf used TruValidate Device Risk and Machine Learning Device Model to reduce large review queues, cut denials for good players, and improve how it targeted promotions and offers.

TransUnion’s solution gave Paf predictive trust scoring for new and returning device interactions, helping fraud and VIP teams make real-time decisions. The results included a 40% decrease in deny rates for trustworthy customers, 33 hours saved each month in manual review time, and faster access to the revenue pipeline; in the first three months, Paf processed 3 million transactions and found about 13% of denied transactions could have been accepted.

Paf

Jessica Hård af Segerstad

Segerstad Data Analyst