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Case Study: How Sift Enabled Banxa to Securely Scale by 30x

Banxa Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Banxa
Industry
Fintech
Challenge
Manual fraud system outpaced by 30x growth
Headline result
5x fewer fraud resources while scaling 30x

Key results

5x
Fewer resources to manage fraud
vs operating without Sift
30x
Secure volume scaling
Kept up with a 30x increase in volume
25 to 120+
Global team growth
In the course of one year

The challenge

Banxa, a payments and compliance infrastructure provider for the digital asset industry, initially built its own fraud function and handled everything manually with rules suited to lower volumes. As the company grew and its volume spiked 30x, the manual model became too limited, introducing friction for trusted customers while its fraud rate rose alongside the growth.

The solution

Banxa built its fraud operations around Sift Payment Protection, using Sift's device intelligence and user session tracking to protect order creation and its machine-learning and data-science capabilities to automatically accept, hold, verify, or decline orders based on routing and rules.

Sift has helped us stabilize our fraud and chargeback rates so we feel in control and in the driver's seat.

I
Igor
Head of Fraud, Banxa

The results, in context

Sift helped Banxa auto-block fraudulent activity and stabilize its fraud and chargeback rates, significantly reducing scam events. Banxa reports it would have taken 5x more resources to keep up with the volume without Sift, and the operational efficiency helped the business securely scale by 30x as its global team grew from 25 to 120+ in a year.

Products used

Sift Payment Protection