Securing the Consumer Lifecycle With a Layered View of Digital Risk

Combat evolving digital fraud with AI — powered by diverse risk signals

Identity-based fraud is evolving rapidly, exposing your organization to increased risk and costs. In fact, 41% of organizations reported having direct identity fraud costs of over $1 million annually. How can you improve your fraud detection approach to adapt to shifting threats?

To answer that question, this on-demand webinar from TransUnion^® focuses on improving fraud detection performance using a layered insights across the consumer lifecycle. From onboarding to ongoing authentication and transaction monitoring, we’ll demonstrate performance lift using layered AI models powered by more diverse risk signals.

Learn to improve fraud detection by combining multiple fraud risk scores

Protecting digital channels is critical to your organization’s success. Fighting fraud while maintaining friction-right customer experiences is essential, capturing more fraud and reducing false positives to keep good customers happy. Boosting fraud detection requires more diverse risk signals — including behavioral signals — offering more insight into risk. During this session, our fraud experts covered:

Digital identity-based fraud trends and costs to organizations

Why improving fraud detection requires signal diversity across touchpoints and channels

Key measures to assess fraud detection performance

How combining multiple fraud models provide additional lift in fraud detection

Why continuous optimization is essential for capturing evolving fraud threats

How layering insights across the consumer lifecycle enhances fraud performance and adaptability to evolving threats