Case Study: iwantmyname achieves 75% fraud reduction and frees up customer support time with Sift

How iwantmyname cut fraud losses and freed up time and resources

iwantmyname is a New Zealand–based global domain registrar with around 100,000 users, known for simple, transparent registration, free DNS, robust support, and one‑click DNS imports. Despite this customer focus and an ethical brand, the company was losing roughly 2% of revenue to fraud and spending as much as 30% of staff time on manual fraud checks; broad country blacklists used to block fraud were costing legitimate sales and degrading the user experience.

They implemented Sift’s machine‑learning fraud prevention—two developers completed the integration in a day—and began using Sift Scores within days. The solution quickly cut fraud and credit‑card testing, delivering a 75% reduction in fraud losses, enabling removal of country blacklists, increasing approved orders with less friction, saving money, and freeing staff to focus on customers and community initiatives.

iwantmyname

Paul Spence

COO and Co-founder