Sift and Chargeback Gurus will partner to better prevent eCommerce fraud, the companies said via a press release. Sift is an eCommerce fraud prevention solution used by more than 34,000 merchant websites around the world. Chargeback Gurus is a chargeback recovery solution that helps merchants to fight chargebacks effectively.
The companies called their new partnership “360 Degree Chargeback Protection”. The press releases cites the continuing increases in both true fraud and friendly fraud as the reasons behind the agreement. Suresh Dakshina, Chargeback Gurus’ President, highlighted their desire to improve its ability to decrease fraud attacks while keeping false decline rates low as a key reason for entering into the agreement.
“Historically, merchants have implemented legacy fraud tools – which rely heavily on hard-coded rules – to combat true fraud,” he said. “Legacy tools are subject to high false positive rates so when we decided to partner to combat true fraud, we sought the only partner who has unmatched accuracy and deep expertise.”
Geoff Huang, VP Product at Sift, stated its interest in Chargeback Gurus’ data analytics expertise as a key reason for their involvement in the agreement. Because Sift is a machine learning eCommerce fraud solution, increased access to transaction data holds out the promise of faster and more accurate order evaluations.
“Mitigating true fraud and friendly fraud chargebacks are key components of a winning Digital Trust & Safety strategy. Chargeback Gurus is at the forefront of comprehensive chargeback analytics,” he said. “Integrating this data into our platform helps our merchants understand the root causes of their chargebacks, prevent revenue loss and increase customer retention.”
In addition, Dakshina stated that the high degree of trust in Sift’s technology — combined with its effectiveness — made it an attractive choice for an agreement.
“Sift is the leader in digital trust and safety,” he said. “They were an obvious choice since their real-time machine learning technology is the best in minimizing true fraud for CNP transactions without false positives.”