Fraud Detection Web Service APIFraud Detection Web Service API
Fraud detection web service API allow you to automate much of your transaction security and work around the clock to keep your sites safe from malicious abuse including mitigating credential stuffing attacks. These tools are also typically easy to integrate into your website and require minimal training to operate. They can help reduce costs by eliminating the need for large teams of specialists to manually review transactions.
These services monitor data to flag suspicious activity and alert you when potential fraudulent activity has been identified. Examples of fraud include: opening many accounts to claim promotion codes, purchasing items using stolen credit cards and chargeback requests from customers who have received goods that were not delivered or are defective. These crimes can cost your business a lot in lost revenue, customer refunds and compliance fines. They also pose a risk to the reputation of your brand.
Unleashing the Power of Fraud Detection: Integrating a Web Service API for Enhanced Security
The key to catching these activities is to be proactive and detect them before they cause real damage to your business. Ideally, you should use a system that is able to process a high volume of data almost instantaneously so that anomalies can be detected in real-time. Cloud-based systems like Fraudio offer unlimited scalability to handle this kind of demand without impacting your business operations.
SEON provides a wide range of tools to protect your business from fraud including Bot Detection, Proxy & VPN Detection, Email Validation and Device Fingerprinting. Its risk analysis looks at 25+ different data points to give your business insights that can help you make decisions on how to respond to fraudulent activities. Its user and transaction scoring allows you to know whether a customer is the genuine article or not before they proceed with a purchase. This makes the service ideal for ecommerce and other businesses that rely on real-time sales.