Why Day Zero Risk Matters and Which Tools Achieve It

Onboarding customers in the digital age means trusting certain identity signals to verify they are who they say they are. Many of those signals have been around for decades, which is understandable as they are based on the criteria we’ve always used to verify individuals. Things like address, Social Security number, email, and phone number are easy to check against existing information and verify users.

But as fraudsters have gotten more sophisticated, they’ve learned clever ways to trick these signals. Synthetic IDs today are made up of real information for each of these identifiers. AI can even help scammers deepfake the appearance of a real person.

As these cyber threats only continue to evolve, financial institutions (FIs) must adopt robust measures to safeguard their operations and their customers. Central to this effort is the concept of “Day Zero Risk”—the ability to mitigate fraud from the very beginning of the customer journey. A customer-centric approach is not just beneficial but critical to achieving this early-stage fraud prevention.

DataVisor and Mastercard hosted a webinar that dives deep into this strategy, titled “Day Zero Risk and the Beginning of the Customer-Centric Journey.”

To get you primed for that insight-packed discussion, this blog post will explore a few key topics the webinar will expand on: what Day Zero Risk is, why we need to reimagine identity verification, and how advanced technologies can help us do it.

Understanding Day Zero Risk

The term Day Zero Risk means exactly what it says—ensuring no fraud risk from day zero of the customer journey. Through proactive prevention measures, FIs can mitigate identity verification and fraud risks from the very first interaction with a customer.

The goal in practice is about aiming to get as close to zero risk as possible right from the start. While achieving absolute zero risk may be unattainable, leveraging advanced technologies like machine learning (ML) allows financial institutions to significantly minimize these risks.

Unlike traditional rules-based systems, ML excels at identifying patterns and anomalies in large datasets, making it a powerful tool in the fight against fraud. Addressing Day Zero Risk is the foundational step toward creating a seamless and secure customer-centric experience.

Reimagining identity verification

Traditional identity verification methods often rely on data elements of Personally Identifiable Information (PII) such as names, addresses, Social Security numbers, and dates of birth. However, these standard elements can be exploited to create synthetic identities. Rules-based approaches, including passwords, security questions, and multi-factor authentication (MFA), while essential, are increasingly inadequate in the face of sophisticated fraud tactics like account takeovers.

Modern identity verification leverages machine learning to enhance these traditional methods. Behavioral biometrics and ML improve both the accuracy and efficiency of verification processes, enabling a smoother user experience. This holistic approach considers the entire customer journey, leveraging data to build risk-based product offerings and comprehensive account management strategies.

The Role of Advanced Technologies

AI and ML significantly enhance fraud prevention capabilities. Data orchestration systems centralize data from all sources, allowing views of the customer journey at a granular level that enable AI and ML to identify fraud patterns in datasets that are invisible to traditional investigators or rules-based systems. These technologies allow fraud teams to create custom workflows, add multiple layers of identity verification, and conduct behavior analysis to catch suspicious activities during onboarding.

Advanced technologies like AI and ML automate rule tuning and adjust strategies in real time, effectively preventing emerging onboarding fraud. They enrich existing data and identity verifications, combining behavioral and device intelligence to confirm identities and detect synthetic IDs. Additionally, these systems can track payment histories and previous abuse instances to prevent cross-channel fraud.

Dive deeper: Watch the Mastercard and DataVisor Webinar

To explore customer-centric strategies that truly enable day zero risk, join me and Mastercard’s Sarah Strano for our upcoming webinar. You’ll hear:

• Practical tips for implementing Day Zero Risk strategies
• Insights from industry experts on leveraging AI and ML in fraud prevention
• Success stories and case studies from leading financial institutions