How ChowNow Keeps Fraud Below 0.03% While Fueling Growth for Independent Restaurants
<2% average block rate
0.03% average fraud rate
Overview
A platform built to fight for independent restaurants
ChowNow is a platform that fights for the success of independent restaurants. It brings ordering, marketing, and operations together in one place, so restaurant operators can grow revenue, own their diner relationships, and run every channel without juggling disconnected tools. From direct online ordering and catering to automated email and SMS marketing, order aggregation, and delivery, ChowNow gives independent restaurants everything they need to grow on their own terms.
Kirsten O. is ChowNow’s Fraud Operations Manager, responsible for the daily operations of the company’s fraud prevention program, including workflow rule set architecture, model training, and dispute response.
Sift’s model performance enables us to skip review queues that would otherwise slow down real-time food ordering, keeping approval and conversion rates high.
Kirsten O.
Fraud Operations Manager, ChowNow
Challenge
Protecting a multi-channel marketplace across two countries, while covering the cost when fraud gets through
In 2025 alone, ChowNow processed more than 2.8 million orders across web, mobile, and guest checkout in the United States and Canada. That scale brings regional complexity: legitimate ordering patterns, and the fraud schemes that mimic them, look different from one market to the next, so ChowNow’s fraud program has to adapt region by region rather than apply a single rule set everywhere.
The stakes are higher than for a typical marketplace, too. As part of its commitment to independent restaurants, ChowNow covers all chargeback and fraud expenses on their behalf, so any fraud that gets through comes directly out of ChowNow’s own margin, not the restaurant’s. At the same time, increasingly sophisticated, machine learning-enabled friendly fraud and promo abuse schemes have made it harder to tell risky activity apart from legitimate diners.
We use Sift’s network signals to quickly identify not just the scale of fraud attacks, but also to root out promo abuse, providing confident links between accounts even when those accounts are trying to operate independently.
Kirsten O.
Fraud Operations Manager, ChowNow
Solution
Real-time decisioning and network-level insight for a lean fraud team
ChowNow’s fraud team uses Sift for order analysis and risky-account actioning, spotting emergent fraud trends, and building workflow rules that segment its marketplace by region and cuisine-specific risk level. Because Sift’s model performs reliably enough to bypass manual review queues, ChowNow keeps approval and conversion rates high without slowing down real-time food ordering.
Sift’s Payment Protection queues give the team both a macro view of emerging fraud trends and a micro view of the specific accounts and orders carrying the riskiest signals, giving the team insight it turns directly into new workflow rules and routing logic. Before rolling out a workflow change, the team tests it first, confirming the update catches more fraud without over-flagging legitimate orders and customers.
Network signals help the team see the connections between accounts, even when those accounts are structured to look independent, which is critical for catching both large-scale fraud attacks and promo abuse. Sift’s Global Insights, added more recently, gives the team executable intelligence on new-to-ChowNow customers, adding confidence to decisions and lowering the chances of both false positives and false negatives.
For reporting to the rest of the business, ChowNow relies on Sift’s business reporting to answer the questions leadership asks most often: what the platform’s block rate and chargeback rate look like at any given time.
Results
A stable, low block rate
With daily management from a small, dedicated fraud team, ChowNow has held a stable average block rate below 2% and an average fraud rate below 0.03%. Keeping fraud losses minimal lets ChowNow keep covering chargeback and fraud costs for its restaurant partners, so operators can spend their time running their business instead of managing fraud.
Sift allows resource-scarce fraud departments to readily scale operations, balancing the time spent on fraud management with efficient decisioning and workflow rule sets. The insights provided by Global Insights are immeasurable in identifying false positives and negatives, keeping confidence high when deciding how to train the model.
Kirsten O.
Fraud Operations Manager, ChowNow
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