Building a Custom Risk Engine with Mobile SDK Telemetry Data

Proactive fraud detection through mobile SDK telemetry offers businesses the ability to identify and mitigate fraud attempts in real-time by analyzing user behavior and device characteristics, thus enhancing decision-making and providing a seamless user experience. Didit's AI-native and modular identity platform integrates telemetry data with other identity verification checks, allowing businesses to create customized workflows that improve risk management strategies. Mobile SDK telemetry collects diverse data points from user interactions with applications, transforming them into meaningful features for sophisticated risk engines that combine rule-based systems, machine learning models, and orchestration logic to assess fraud risk dynamically. The platform's no-code environment and developer-first approach facilitate the integration and optimization of custom risk engines, ensuring businesses can adapt to evolving fraud tactics while maintaining compliance with data protection regulations. By leveraging Didit's capabilities, including advanced machine learning and customizable verification workflows, businesses can automate trust, reduce fraud, and maintain a seamless user journey, all while benefiting from a cost-effective, pay-per-successful-check model.

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