Challenge

Within two months of launching in the US – Sendle’s first international market – the company started to experience sophisticated and costly incidents of fraud previously unseen in its Australian operations.

Sendle set out to combat the fraud activity on its own, but obstacles appeared at every turn. Bad actors were creating multiple accounts on the Sendle platform through automated and manual tactics, which were mainly used for label reselling and placing shipments using stolen card details. These accounts rotated between hundreds of credit and debit cards across different banks, resulting in chargebacks. Sendle realised building a fraud prevention toolset on its own was going to be a challenge, requiring deeper fraud expertise and a significant investment of time and resources.

Solution

Fortunately, Sendle already partnered with Stripe to power its payments processing since its inception. This enabled the business to quickly and easily implement Stripe’s fraud prevention tools to minimise the financial and resourcing impact fraud was having on the business.

Sendle chose Stripe Radar for Fraud Teams to provide the critical first layer of fraud protection and discern bad actors from legitimate customers. Radar’s machine-learning scoring algorithm detects and blocks fraud, and because Sendle had already partnered with Stripe Payments, minimal implementation was required, making the rollout smooth and straightforward.

Stripe’s team worked closely with Sendle’s fraud analysts to create a workflow tailored to Sendle’s unique business and fraud challenges. As a result, Sendle was able to add a series of custom rules, leverage rule attributes like 3DS, and setup block and allow lists to fine-tune its fraud protection.

By focusing on building rules around validation, 3DS requirements, IP and geolocation matching, and card validation, the Sendle team received better risk insights of customer transactions even before the charges on the cards were made. In addition, having block lists set up for IP, email domains, and card fingerprints, has greatly reduced the occurrences of fraud and abuse across the Sendle platform, thus preventing future chargebacks.

The combination of Stripe’s machine-learning algorithm and Sendle’s custom rules enabled Sendle to improve fraud protection and get the company back on track for its US expansion strategy.

Results

Since using Stripe Radar for Fraud Teams, Sendle has achieved an ROI of 11x and reduced fraud loss by nearly 30% in the US. The increased level of protection meant Sendle could focus on balancing its ambitious US growth strategy while maintaining low levels of fraud.

Within one year of implementation, Stripe Radar for Fraud Teams thwarted significant attacks on Sendle’s US operation, complementing the company’s own strict security measures and the development and expansion of its internal fraud prevention team.

Today, the tool has become an integral part of the way Sendle does business. With busy e-commerce periods such as Black Friday, the holiday season, and the overall increase in post-pandemic online shopping, Sendle can now manage increased package volumes without worrying about the financial losses from fraud. Combining Radar with its internal fraud model, Sendle proactively protects its small business customers, partners, and revenue.