Common types of online payment fraud and how to prevent them
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Don't stop at blocking bad actors. Engineer compounding gains with a modular fraud ecosystem designed to improve acceptance, cut operational costs, and filter for trust.
We offer two tiers of protection, allowing you to tailor your risk strategy to your exact business needs, industry, and team size.
Protect your bottom line without getting in the way of legitimate customers. Our foundational security is powered by global network intelligence for every Checkout.com merchant. It screens transactions silently, neutralizes known threats without adding latency, and allows you to intuitively manage velocity limits and targeted allow/block lists.
Our advanced prevention offers scalable control, machine learning precision, and deeper explainability. Designed for merchants who want to actively turn risk management into a commercial advantage, Fraud Detection Pro puts you in the driver's seat with powerful ML network properties, custom logic, and transparent transaction-level insights.
From foundational controls to advanced machine learning properties, our ecosystem gives you the exact features required to shape your traffic, stop bad actors, and approve more genuine customers.
Every transaction receives a precise risk score. Powered by our global network models and deep device data (via Risk.js), these scores instantly identify complex fraud patterns and can automatically trigger dynamic routing or authentication.
Build multi-layered velocity rules based on cumulative spend, relative occurrences (e.g. multiple emails used per cardholder), and cross-merchant network velocities (e.g. blocking devices that have multiple disputes on the Checkout.com network).
Get granular control of your strategy. Group rules into comprehensive Risk Profiles, assign positive or negative scores to specific triggers, and set custom thresholds to accept, decline, or challenge (3DS) payments based on your logic.
Never guess how a rule will impact revenue. Use shadow testing (Standard) to simulate outcomes silently on live traffic, or upgrade to backtesting (Pro) to instantly run a new strategy against months of historical data and prove its ROI in minutes.
Reduce manual reconciliation work by automatically splitting funds - at authorization or capture - into multiple accounts.Easily manage referral lists to block known bad actors or bypass friction for VIP customers. Pro users can expand this by building custom lists, using historical templates, and deploying dynamic high-risk country lists directly into their rule logic.
Fraud Detection Pros machine learning and flexible rules allow us to quickly respond to attacks and find the right balance between lowering fraud and maximizing acceptance rates. Shadow mode testing allows us to safely experiment with new strategies without impacting customer experience.
Every business is different. Some need silent, foundational security to protect their baseline without adding friction, others need an advanced suite to actively recover margin. From essential network defense to enterprise-grade AI, compare the capabilities to see which solution fits your strategy.
[]Machine learning is the first line of defense against fraud. Using data from the billions of transactions Checkout.com processes globally, Fraud Detection learns to differentiate between legitimate and fraudulent behavior, and to adapt to ever-changing fraud tactics. This boosts your fraud-fighting capacity by reducing the amount of manual work youre required to do.
However, machine learning isn't a silver bullet, which is why it works in tandem with the rules you create to block or accept transactions, or to ask for further verification. Fraud Detections robust rules engine allows you to build rules from an infinite range of types and combinations (custom rules are only available with Fraud Detection Pro).
For example with Fraud Detection Pro you can decide on outcomes for specific risk scores, segment customers and apply unique strategies based on their risk level.
With Pro, you also get powerful analytics, reporting and testing, so you can continually optimize your fraud prevention strategy.
Our Fraud Detection solutions can help you tackle fraud by giving you control over how you accept transactions. This works in parallel to our disputes product which helps you view and fight any disputes that arise.
You can develop risk strategies by building rules and outcomes to deal with specific scenarios. For example, you can ensure that any transaction over a particular value requires 3D Secure (3DS) authentication.
Or, if you detect that a card has been used more than three times within an hour, you can flag it as suspicious or automatically decline the transaction. Additionally, by implementing 3DS, the issuer becomes liable for any costs incurred as a result of fraud or chargebacks.
We also offer Rapid Disputes Resolution (RDR) in partnership with Visa company Verifi. RDR helps you to automatically resolve transaction disputes with a pre-dispute resolution that follows your pre-defined rules. This means the transaction will not be classed as a chargeback by Visa, which can help to avoid you being placed on a chargeback program.
Built directly into our platform, Fraud Detection protects your business and reduces false positives. You can create flexible rules and approve and deny lists to stop fraud while ensuring legitimate transactions are authorized. Meanwhile, dynamic machine learning works to identify and stay ahead of fraudulent trends.
We offer both a free and a paid fraud management solution.
Fraud Detection, the free version, comes with preset configurations, so you can go live immediately. Its best for businesses that dont yet have a significant fraud problem and have only limited internal fraud-fighting resources.
Fraud Detection Pro, our premium product, allows you to fully customize your risk setup so you can tailor your strategy to the level of threat you face. Its designed for larger merchants with internal fraud teams.
For information on how to implement Checkout.coms Fraud Detection solution see our documentation.
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