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The Sift Score is a benchmark for us to decide on fraud investigations. It helps us enable decisions with much higher confidence.

NateDirector of Operations

Overview

  • Financial services remittance company

  • International audience

Challenge

  • Reduce manual review rate for “card not present” fraud

  • Better manage regulation and compliance (KYC, AML) in fraud review workflow

  • Spend less time performing customer phone verifications

Solution

  • Seamless Sift API integration into current workflow

  • Intuitive Fraud Dashboard to see data in one place

  • Sift’s real-time email alerts to manage work queue

Results

  • Reduced manual review rate from 5% to 2.5%

  • Over 70% of fraud caught in top 2% transactions

  • Retired dozens of hard coded rules

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 for pick 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 Science, 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.

“Data is king in the fraud world. What we needed was a best-in-class tool to prevent fraud.”

That’s when Nate turned to us.

Solution

Data-Driven Decision Making

Nate’s team was able to quickly integrate the API in an afternoon and start teaching our 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.

“Today, we process tens of thousands of transactions each month and it only takes a few days to see statistical relevance.”

Nate says that in order to really get the maximum benefits of integrating with Sift Science, customers will need to commit to managing their data.

“Your results will only be as good as the effort you put in. If you’re not serious about your data, then you’re not serious about fighting fraud.”

Results

The Sift Science Advantage

After working with a few fraud prevention vendors, Nate ultimately chose Sift Science for its sophisticated machine learning approach that used predictive models based on Remitly’s own data to combat fraud.

Using Sift Science, Nate says that 70% of fraud is caught in the top 2% of transactions. “That’s a big deal for us”.

“Sift Science helps makes it very accessible to fight fraud on a world-class level.”