Learn how Ravelin detects and prevents payment fraud, and get an overview of the key steps involved in integrating our solution.
Read MoreUnderstand the end-to-end process of integrating Ravelin's payment fraud solution, from initial planning and collaboration to implementation and going live, with dedicated support at every step.
Read MoreBegin your integration with Ravelin by learning how to request payment fraud recommendations and interpret results in the dashboard.
Read MoreExplore the various integration points for Ravelin's fraud detection within your payment flow. Learn how to request recommendations before or after authorization and handle multiple checkout attempts to enhance fraud prevention.
Read MoreIntegrate Ravelin's JavaScript and mobile SDKs to collect device data, generate unique Device IDs, and enhance fraud detection by identifying shared devices and suspicious patterns.
Read MoreLearn how to request payment fraud recommendations at key points in the customer journey, such as during checkout, payment method selection, and payment method registration.
Read MoreLearn how to send post-recommendation updates - such as order acceptance, completion, or refunds - to Ravelin. Keeping Ravelin informed ensures that fraud models remain accurate and effective.
Read MoreLearn how to report disputes and chargebacks to Ravelin to enhance fraud detection and risk modeling.
Read MoreLearn how to test your Ravelin integration by simulating specific fraud actions, introducing network latency, and managing test data to ensure robust and accurate fraud detection before going live.
Read MoreLearn how to handle non-2xx HTTP responses, implement timeouts, manage rate limits, and maintain observability to ensure a resilient integration with Ravelin's payment fraud detection services.
Read MoreExplore strategies for transitioning Ravelin's payment fraud detection from testing to production. Learn about rollout approaches, threshold tuning, handling multiple fraud systems, and best practices for a smooth go-live process.
Read MoreLearn how to perform manual reviews to label customers as genuine or fraudulent, providing critical feedback to Ravelin's machine learning models and enhancing real-time fraud detection.
Read MoreAccelerate your fraud model training by submitting historical transaction and dispute data to Ravelin. Learn when and how to provide this data to enhance the accuracy of fraud detection from the outset.
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