In the world of online payments and bank transfers, timeliness is more than just a nice-to-have. Real-time transactions and cross-country connections mean money is moving at the speed of modern commerce, and that waits for no manual review. Online payments network Dwolla works to enable its users to more quickly and frictionlessly make bank transfers. But when scammy users, stolen credentials, and other forms of transactional fraud began to cost them time and – more painfully – the trust of their legitimate users, Dwolla’s team turned to a machine learning-based solution that could meet the needs of their on-demand business.
“Sift’s ability to compare data on its own without needing an investigator to query is so powerful. We get new insights all the time without Dwolla’s team having to think of specific needs.” – Ryan Hodge, Financial Intelligence Unit Director
Learn how the Dwolla team cut fraud by 50% and drastically reduced their average manual review time in our newest case study.
Stop fraud, break down data silos, and lower friction with Sift.
Achieve up to 285% ROI
Increase user acceptance rates up to 99%
Drop time spent on manual review up to 80%
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