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Chargebacks are a serious issue in today's ecommerce industry, affecting any site that accepts payments. Merchants are always looking for new tools and resources they can leverage to streamline fraud prevention and lower lost products, chargeback fees, and overall disputes. Spending less time managing fraud and manually reviewing payments is the ultimate goal as that time can be better spent on more productive tasks.
According to a report by Card Not Present, chargebacks caused an estimated $31 billion in losses in 2017 alone. This is a substantial figure that impacts large and small companies alike. Ecommerce is by far the worst industry impacted by online fraud. Online payment fraud is expected to continue growing in 2019 and beyond. Tackle chargebacks and payment fraud with IPQS suite of easy to use anti-fraud tools. Deploy our fraud prevention tools in just minutes and let our automated process handle scoring your transactions and payments.
Stop Payment Fraud
Automatic Quality Control
Chargebacks, like all types of fraud, follow patterns and behavior models. IPQS' machine learning algorithms detect orders likely to result in chargebacks and can predict malicious behavior to identify high risk transactions. An overall Fraud Score is calculated in real-time based on the IP reputation, device reputation, email address history, and over 200 data points. This risk score along with other data our API outputs can provide a wealth of information to enhance your decision making and business logic for automatically blocking high risk transactions or requesting more details to verify an order.
With IPQS, you can score every aspect of your transactions to enhance the likeliness of detecting fraudulent transactions or payments. Tap into our network of fraudulent email addresses, devices, IP addresses, user info (names, phones, physical addresses, etc.) all gathered by scoring hundreds of millions of transactions per day for the internet's largest websites. When our system notices fraudulent behavior or any high risk activity, it will be reflected in the overall risk score provided for each user or transaction. 25+ additional data points for transaction scoring are provided to indicate how risky the user is rated for each category mentioned above, such as email reputation, device reputation, etc. Machine learning models regulate the scoring process to avoid false-positives and align our algorithms to account for typical user behavior on your site.
Not all audiences behave the same, and IPQS understands this. Our machine learning algorithms automatically adjust to your traffic so valid users are never penalized and irregular behavior can easily be detected. Manual scoring settings can also be fine tuned directly from your account so you'll always be in control. This ensures our system is performing up to par, detecting every fraudulent payment and high risk transaction without impacting the user experience.
Implementing real-time detection for chargebacks is actually quite easy. IPQS' ecommerce plugins and easy-to-use API services can be integrated into any third party platform, app, or website. If your site already has anti-fraud tools, IPQS can enhance your existing algorithms to make decisions with greater confidence and accuracy.