How Remitly safely sends millions of dollars overseas every month
50%
Fewer manual reviews
20%
Reduction in new user reviews
OVERVIEW
Helping loved ones back home
Remitly’s mission is to build modern solutions that empower people to send money and interact more personally. Customers are able to transfer money internationally to their loved ones back home, all online and using their mobile phone. Money can be sent or picked up at over 10,000 locations or deposited directly into a bank—all in under two minutes.
When Nate Spanier, Director of Operations at Remitly, reached out to Sift, he was already running a tight ship. Remitly’s loss rates were much lower than the industry standard. Every staff member on the risk team had several years of fraud investigator experience and focused full time on reviewing cases and fielding customer calls.
CHALLENGE
Scaling risk operations with confidence
With a bold 100% money back guarantee, Remitly must ensure that each transfer is reviewed systematically with rigorous investigation. From the very beginning, Remitly knew that fraud was going to be a major problem before writing a single line of code. With $350 billion in money transfers from developing countries alone every year, instant money transfers require Remitly to be constantly vigilant with fraud prevention.
When Remitly started to ramp up its services in the Philippines, fraud activity started to heat up. Nate’s biggest challenge was reducing the number of hours spent on manual reviews, which included lengthy call verifications, while maintaining a stringent filter for catching fraud. The review process soon became overwhelming. His team had much more data than they could humanly work with. They had already set up 80-100 rules to capture suspicious activity, but given the company’s current and future growth trajectory, scaling would be challenging. He also lamented the system’s inability to learn from the company’s data. That’s when Nate turned to Sift.
SOLUTION
Data-driven decision making
Nate’s team was able to quickly integrate the API in an afternoon and start teaching Sift’s machine learning models with Remitly’s data.
Remitly integrated Sift’s score API into its review workflow. Using the Insights Dashboard, Remitly settled on a risk score threshold that was right for them. They also used Sift’s customizable alerts to add review tasks in the work queue. The Sift Score helped the team tip the scale in the decision making process.
Over time, the scoring mechanism “was really fun to watch” as the system started to detect more nuanced fraud patterns over time. Remitly was able to rely less on its complicated rules engine and started to see improvement. Nate says that in order to really get the maximum benefits of integrating with Sift, customers will need to commit to managing their data.
RESULTS
The Sift advantage
After working with a few fraud prevention vendors, Nate ultimately chose Sift for its sophisticated machine learning approach that used predictive models based on Remitly’s own data to combat fraud. Using Sift, Nate says that 70% of fraud is caught in the top 2% of transactions. “That’s a big deal for us.”
