Credit Unions Fight Fraud by Connecting Member Data Faster

Criminals are no longer concentrating on a single payment channel or one weak point.

Instead, they are stitching together attacks that stretch from account opening through authentication and payment activity, placing pressure on systems that were often designed to examine isolated events rather than connected patterns.

The PYMNTS Intelligence report “Defending the Member: How Credit Unions Are Responding to a New Fraud Landscape,” a collaboration with Velera, found that the challenge extends beyond higher fraud volumes. Fraud is becoming more sophisticated, coordinated and harder to detect because digital interactions now occur across a growing number of channels.

The report revealed that 77% of credit unions experienced unauthorized network access during the past year, underscoring how broadly the problem now reaches across the industry.

Fraud is an issue that touches member confidence, operating costs and long-term relationships. As members conduct more of their financial lives digitally, they expect suspicious activity to be identified before losses occur, while still receiving the speed and convenience they associate with modern financial services.

These expectations create a difficult balancing act. Security measures that introduce delays or unnecessary friction may discourage legitimate transactions, yet insufficient protection exposes institutions and members to growing financial losses. According to the research, 82% of credit union members said their payment method choice is primarily influenced by which option feels most secure, highlighting how closely security and member trust have become intertwined.

Connecting Data Before Criminals Connect the Dots

Many traditional fraud programs struggle because they rely on disconnected systems, the report showed. Information often remains separated across card operations, digital banking platforms, authentication tools and core processing systems. These gaps can prevent institutions from recognizing that seemingly unrelated events are actually part of the same attack.

Modern fraud strategies attempt to address the weakness by combining real-time data, artificial intelligence-driven analytics and integrated operational systems. Rather than evaluating transactions individually, these approaches analyze activity across channels to identify unusual behavior earlier in the attack cycle.

AI has become important because many emerging threats develop too quickly for manual review alone. AI-generated identity fraud, synthetic identities and convincing impersonation attempts are examples of attacks that require continuous monitoring and adaptive analytics, the report found.

Criminals can also imitate legitimate customer behavior more effectively than in previous years, making conventional rules-based detection less reliable on its own.

AI also enables investigators to prioritize high-risk events, reduce unnecessary reviews and concentrate attention where human judgment adds the greatest value. When paired with comprehensive transaction data, AI can improve detection accuracy while shortening response times.

Integrated data reduces operational strain. Breaking down data silos provides a broader view of member activity across accounts, devices and payment channels, allowing institutions to identify relationships that would otherwise remain hidden. Better information can produce more consistent decisions while reducing duplicate investigations and repetitive manual work.

Collaboration is becoming increasingly valuable, the report revealed. Many credit unions lack the resources to independently build sophisticated fraud detection capabilities across every channel. Shared technology platforms and ecosystem partnerships can provide access to broader datasets, specialized expertise and continuously updated analytical tools without requiring each institution to develop those capabilities internally.

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