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Ravelin in action: Deliveroo reduces chargebacks by 90%

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With its exponential growth, Deliveroo started to attract attention from fraudsters. The high number of chargebacks were harming the bottom line revenue, becoming remarkably costly. Ravelin’s machine learning approach helped to slash fraud by half in only four months.

Advancements in technology have opened the floodgates to innovation - whether every business sees this an opportunity remains to be answered. There are the pros and cons: adopting new technologies create a more nimble business model which is data-driven, yet on the other hand, some businesses face severe obstacles if they rely on outdated back-end systems, and upgrading these decade-old infrastructures is expensive and risky. Not doing so puts them at risk of losing out. Doing so may create unnecessary problems for business.

The opinion from this conference, as you may have guessed, favoured towards using technology to innovate and revolutionise the way businesses in the industry operate. Here’s our highlights from the event.

“We are now building our processes around Ravelin rather than the other way around. It is central not just to fraud but to customer success.”

The Problem

Deliveroo is growing fast. From a single bike that its founder Will Shu rode in 2013 to tens of thousands of orders per day and a $1bn valuation in four short years. It is now in over 140 cities across the globe and is a very familiar sight in many of  Europe’s cities. In the words of Will Shu, Deliveroo is now part of the lexicon.

In 2016, as the company’s visibility and popularity grew, fraudsters began to target the company in earnest. By the Spring, it was clear that steps were going to have to be taken to secure the business against chargebacks that were becoming extremely costly.

“When we began to realise that we really needed to tackle fraud, we initially assumed we would have to hire a fraud manager and then a team to build capability internally. We really didn’t want to do that for cost, speed and efficiency reasons. We didn’t and don’t see fraud detection as a core function for us. The team at Ravelin told us about their approach and we were immediately convinced that Ravelin was the way to go.” - Emma Whibley, Finance Manager at Deliveroo

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The Solution

Ravelin’s approach is to use machine learning as the principal technique to predict whether any order is likely to be fraudulent or not. Based on Deliveroo’s own historical chargeback data, Ravelin applies its proprietary algorithms to score all activity for fraud in real time and feed the result back to Deliveroo’s ordering system. This means that fraudulent orders are blocked before they are accepted by the restaurant.

Deliveroo sets the risk threshold they are willing to accept and can vary it for different markets. Once set, prevention is entirely automatic. There is no manual review of orders and no escalation process. Deliveroo and Ravelin work together to assess if the threshold is correct per market based on the impact on chargebacks and the incidence of false positives  (where a good customer is blocked by mistake).