Download PDF
Sift > Case Studies > How Favor Delivery achieved growth while reducing risk
Sift Logo

How Favor Delivery achieved growth while reducing risk

Technology Category
  • Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
  • Retail
Applicable Functions
  • Sales & Marketing
Use Cases
  • Fraud Detection
Services
  • System Integration
The Challenge
As Favor Delivery expanded, they experienced an increase in the number of chargebacks. The growth of fraudulent accounts and account takeover (ATO) attempts were becoming more frequent. Favor Delivery was using their internal heuristic system to manually search for fraud, which wasn’t scalable and couldn’t keep up with the volume of incoming orders. They needed a proactive solution that could automate and keep them ahead of fraud – not struggling to keep up with it.
About The Customer
Favor Delivery is a Texas-based on-demand delivery service. Via the mobile app or desktop site, users can place orders for anything from takeout food to last-minute needs from the drugstore, and Runners (delivery assistants) make the delivery in under an hour while keeping users updated every step of the way. Users get what they need in good time and at a great price, while Runners have the freedom to either supplement their income or replace a traditional job by delivering with Favor Delivery. Favor Delivery operates within all major cities in Texas and is continuing to expand throughout the state.
The Solution
Favor Delivery turned to Sift Payment Protection; the integration took less than two months, and within a month after integration Favor Delivery started to see powerful results. Favor Delivery’s Account Review Team began utilizing Sift Workflows to manage their fraud logic, auto-accepting most orders and auto-blocking the riskiest. With Sift Insights, the team used the Routes metrics to determine how many orders were hitting a given route and whether that was effective or causing too many false positives. And the Network and Activity features within an order accelerated manual reviews, as the team could determine whether an order shared risky attributes with other fraudulent orders and quickly decide whether they wanted to accept or reject the order.
Operational Impact
  • Since implementing Sift Payment Protection, Favor Delivery’s chargeback rate has decreased significantly.
  • Thanks to accurate, automated decisions, the Account Review team is saving significant time in manual review.
  • With their chargeback rate under control, Favor Delivery has scaled throughout the state of Texas and continues to grow steadily.
Quantitative Benefit
  • 77% Reduction in chargebacks
  • 3.5x ROI using Sift
  • 300 Hours in manual review saved monthly

Related Case Studies.

Contact us

Let's talk!

* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.