Refund abuse protection

Stop losing to refund abuse.

Give good customers a frictionless refund experience. Rehabilitate opportunistic abusers. Block fraudsters and their networks.

Explainable machine learning
+ real-time link analysis
+ customizable rules

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Read our customers' stories

With third-party fraud under control, we can leverage Ravelin to tackle other types of fraud that erode profit for River Island, such as refund abuse, which has the potential to save us a significant amount of revenue.”

Working with Ravelin since 2021

Lacey Cole

Fraud Analyst

River Island

Get deep customer intelligence

Confidently know the intentions of each customer.

Run detailed analysis straight from the dashboard.

Automate better decisions to support good customers and block abusers.

Stop fraud rings
and multi-accounting

Going beyond most link analysis tools, Ravelin’s real-time graph network maps a customer’s entire network – so abusers using burner accounts and refund fraud rings can be stopped in their tracks.

Learn more

Build your policy rules

Automate your refund policy enforcement with our rules engine.

Build any rule you need using 100s of data points such as rate of refund requests, supplier information, and connections observed in the graph network.

Apply the appropriate intervention

Tailor what action you wish rules to trigger – for example, removing self-serve refund capability, sending an automated email, blocking future transactions and/or new account creation.

Modify your customers' journey

Rules can trigger actions at the point of account creation, checkout and point of refund request, so you can modify the digital journey for different customer segments.

Push rules live with confidence

Experiment with policy rules with our backtesting capabilities. Simulate rules on live traffic to confidently push rules live without unintended consequences.

Apply the appropriate intervention

Tailor what action you wish rules to trigger – for example, removing self-serve refund capability, sending an automated email, blocking future transactions and/or new account creation.

Modify your customers' journey

Rules can trigger actions at the point of account creation, checkout and point of refund request, so you can modify the digital journey for different customer segments.

Push rules live with confidence

Experiment with policy rules with our backtesting capabilities. Simulate rules on live traffic to confidently push rules live without unintended consequences.

Tackle the gray areas

Machine learning identifies new and hard-to-detect patterns of abusive and fraudulent behavior that your policy rules may miss.

To ensure your defences are robust and continually adapt to the latest trends.

We’ve worked very closely with Ravelin in developing a best-in-class solution to protect Trainline and our partners from refund abuse. We’re excited to continue this collaboration as we work towards a fully automated solution.”

Watch the case study

Working with Ravelin since 2021

Nick Aiken

Director of Fraud & Payments

Trainline

Get your refund abuse problem under control

Book a chat to find out how more about about Ravelin's Refund Abuse solution can help your company.

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FAQ

Will Ravelin help me define and set up my refund abuse strategy?

Absolutely.

During your onboarding, Ravelin’s Data Science team will work with you to analyze your refund abuse problem and recommend an optimal setup, including which rules to build.

Our team will continually analyze the performance of your refund abuse strategy, making ongoing recommendations on how to improve your setup to drive continual improvements in performance.

Can I use Ravelin’s refund abuse as a standalone product?

Yes! You can use Ravelin’s Refund Abuse solution as a standalone product.

You can always onboard other Ravelin products in the future to bolster your fraud protection stack and benefit from having all your fraud solutions in one place.

What makes Ravelin’s Refund Abuse solution different?

Ravelin offers machine learning, a powerful rules engine, and best-in-class graph network visualization, while providing you with more contextual customer data than any competitor, including customers’ net spend calculation.

Best of both worlds (ML and rules)

Ravelin is the only tool in the market that utilizes machine learning and a rules engine to give you both the control to enforce your policies and real-time predictions on the likelihood of refund abuse.

Having ML in addition to rules will identify more instances of refund abuse than rules alone.
Best-in-class network visualization

Our merchants see enormous value in how we present connections between customers via our Graph Network visualization.

Analysts utilize our graph network visualization to intuitively detect clusters of suspicious activity, connections between multiple actors, and multi-accounting.
Extensive graph network mapping

Our graph network link analysis infrastructure enables extensive mapping of connections at speed.

Ravelin permanently tracks several layers of connections between data points, making it extremely hard for refund abusers to circumnavigate your defences by creating new accounts.
More contextual data

Ravelin exposes significantly more contextual data about your customers, including related chargebacks, account age, and even itemized order history timelines, so that you can make accurate and informed investigations.

As far as we are aware, we are the only provider in the market to offer net spend calculations and associated data that allows you to gauge how profitable a customer is (or isn't).