Why Credit Unions Struggle to Identify First-Party Fraud – And How to Fix It

By Shanthi Shanmugam, CEO, Casap
February 25, 2025

First-party fraud, also known as friendly fraud, is on the rise and becoming a growing challenge for financial institutions. Mastercard reports that it accounts for up to 70% of all credit card fraud and costs the industry over $100 billion annually.

Unlike traditional fraud, friendly fraud can be accidental (billing confusion) or intentional (seeking reimbursement on a valid payment). Identifying it requires a combination of internal data, member behavior insights, and industry-wide intelligence. However, many credit unions struggle to leverage these resources effectively.

Having worked with credit unions nationwide to improve dispute resolution, chargeback management, and fraud prevention, I’ve identified five key reasons why credit unions struggle to detect friendly fraud – and how to fix them.

Data Silos and Fragmentation

Many credit unions rely on disconnected systems to manage transactions, fraud detection, and disputes. Core banking platforms, card processors, and dispute management systems often function independently, making it difficult to identify fraud patterns.

Without a centralized approach, repeat disputes and suspicious behaviors go unnoticed. Integrating fraud detection, transaction monitoring, and dispute resolution systems allows credit unions to build a unified fraud profile and more effectively distinguish between legitimate claims and abuse.

Overreliance on Rule-Based Fraud Detection

Traditional fraud detection relies on rule-based systems and manual processes, which often fail to recognize first-party fraud. Since friendly fraud doesn’t follow traditional fraud patterns, it frequently slips through undetected.

For example, a member who repeatedly disputes subscription charges may not raise red flags in a rule-based system. However, an AI-driven fraud model could detect patterns at scale, assign risk scores, and flag high-risk cases early – allowing fraud teams to take action before losses accumulate.

Limited Industry Data Sharing

Fraudsters take advantage of gaps between financial institutions. While card networks and payment processors collect extensive fraud data, credit unions often lack direct access to real-time fraud intelligence.

Collaborating with fraud consortiums, industry networks, and data aggregation platforms provides a broader perspective on fraud trends. Credit unions that leverage shared fraud intelligence can better anticipate emerging threats and proactively prevent friendly fraud.

Inefficient Dispute Workflows

Strict regulatory deadlines require credit unions to process disputes quickly, often at the expense of thorough fraud analysis. Without automation, fraud teams become overwhelmed by high dispute volumes, leading to the approval of fraudulent claims simply to stay compliant.

Automating dispute workflows and incorporating fraud-scoring models help credit unions prioritize high-risk disputes, reduce manual workload, and allocate resources efficiently – ensuring fraud teams can focus on complex cases instead of routine approvals.

Balancing Fraud Prevention With Member Trust

Credit unions prioritize strong member relationships, making fraud disputes particularly sensitive. Many hesitate to challenge questionable claims out of concern for damaging trust – even when internal data suggests abuse.

By establishing clear fraud policies, educating members on dispute procedures, and leveraging fraud analytics, credit unions can protect themselves while maintaining positive member experiences. Proactive communication about fraud policies can also help reduce unintentional friendly fraud by setting clear expectations upfront.

How Technology Partnerships Can Help

To effectively combat friendly fraud, credit unions must move beyond isolated data and manual processes. Partnering with technology providers that aggregate fraud data across institutions and merchants provides a competitive advantage by offering:

• Industry-wide fraud intelligence to detect emerging trends
• AI-driven dispute analysis for more accurate fraud detection
• Automated workflows to improve efficiency and reduce manual errors
• Enhanced member insights to differentiate fraud from legitimate disputes

By leveraging external fraud intelligence and automation, credit unions can reduce losses, strengthen fraud detection, and build long-term member trust. A data-driven approach is no longer optional – it’s essential for financial security and operational efficiency.

Connect with Casap to learn more.

About Casap

Casap integrates with financial institutions' existing systems and uses its AI platform to automate payment disputes and prevent first-party fraud. It supports various transaction types, including card payments, digital payments, EFT, ATM, check, and ACH, ensuring seamless compatibility with banks, credit unions, and fintechs. The platform's built-in regulatory expertise and network integrations enable it to intelligently analyze evidence, predict outcomes, and automate key actions such as issuing credits and filing chargebacks.