Credit Unions: Learn How to Protect your Members from Fraud

According to TransUnion’s global online fraud trends analysis, digital fraud attempts against financial institutions have seen a spike of 22% in the U.S. and 46% globally since the pandemic began. And in our recent blog post, we have identified the common fraud trends, which include identity theft and spyware, synthetic identity fraud, credit washing, transaction fraud, and data breaches.
Picture of Ritesh Arora

Ritesh Arora

February 15, 2022

With the financial services sector being the second most targeted industry — just behind telecommunications with a 57.49% increase in suspected digital fraud attempts — credit unions must be two steps ahead of fraudsters to protect their members. Failing to do so can be catastrophic to the reputation of and devastating to your members you serve.

Be Predictive and Proactive (Not Reactive)

Instead of being reactive, your credit union must be predictive and proactive. A legacy approach that makes decisions based on historical member data poses great risks. Your credit union needs a mechanism that enables you to collect, analyze, and act on real-time information on your members, be notified of any questionable transactions, and employ analytics to actively detect and defend against fraud without necessitating member intervention.

For credit unions, advanced analytics can be designed to merge multiple data sources, be it internal or external, helping the organization quickly adapt against new fraud trends. At Effectiv, for example, our platform provides automated and detailed reporting analytics on fraud trends, giving credit unions a complete view of the possible fraud’s impact.

Use Multiple 3rd-Party Data Sources for Stricter KYC Controls

Know Your Customers processes and interfaces to 3rd-party data sources are crucial to enabling credit unions to protect their members from fraud. In addition to compliance, KYC procedures help credit unions understand their member’s transactional patterns through a set of procedures for verifying their identity before or while doing business with them to help keep fraud at bay. Knowing your members enables your organization to identify suspicious situations early in a member’s affiliation and prevent the institution from being used for money laundering operations.

To implement stricter KYC controls, your credit union needs to interface with multiple 3rd party data providers to be able to accurately verify the identity of newly onboarding members and their transactions. This can also prove valuable in monitoring existing members’ transactions. With the right member information at hand, credit unions can monitor questionable transactions much more carefully and take proactive measures to prevent fraud whenever required.

Increase Automation with AI

Using advanced analytics and machine learning, credit unions can create, for example, an adaptive set of strategies that analyzes fraud patterns and quickly adapts to changing trends. By combining multiple data sources with member information and their transaction, machine learning can help your organization obtain full visibility into the anomalous money flow and information exchange among your members — in real-time saving hours of manual work for the fraud investigators. It allows you to extract actionable information from a massive amount of data and be able to identify where fraud can be committed. Also, with machine learning, credit unions not only find known fraud but also identify previously unknown patterns and identify inefficiencies in the system.

Meanwhile, multiple sectors— with big players in the financial services included — have adopted automation-driven technologies to deliver secure services to their customers. And so should credit unions. While manual processes such as contacting your members regarding any suspicious activities are still prevalent today, with the technological advancement and changing expectations from the members they no longer serve the intended purpose of the trust and only add up to another layer of suspicion for your members. Needless to say, manual processes can burden resources, which may result in greater risk for human errors, hence more chance for fraudsters to get in.

Smart Case Management

Along with task and process automation, smart case management helps credit unions be ahead of fraudsters by saving time and effort that can be spent in serving underserved members. As fraudsters have evolved in their tactics, using spreadsheets to manage fraud cases is outdated and puts your organization at risk. Spreadsheets may lead to misplacing evidence, omit steps in fraud detection procedures. Without the contextual information and the steps, it could only open more opportunities for fraudsters to attack your organization and put your members at risk. Additionally, putting all the data together into a view that is easy to understand, comprehend, and utilize is just inefficient due to its labor-intensive nature.

Implement a smarter approach to case management using software with case management capabilities. A smart case management system stores all information into centralized access controlled, secure database, keeping case investigations organized and on track. This makes collaboration among teams and departments easier and ensures all information is complete and accurate without compromising security. A McKinsey study found that smart case management systems reduced fraud by 25 percent in organizations that implemented such systems.

Stay Ahead of Fraudsters

Effectiv is built to proactively complete initial fraud assessments during user onboarding and monitor future transactions for fraudulent behavior. In addition, it integrates data from multiple sources for deeper investigations, and it uses intelligent case management to detect and adapt to new fraud patterns. With this solution, fraud investigations, detection, and reporting are simplified.

Effectiv prevents fraud by conducting automated fraud detection of the credentials and authenticity of new users as early as the onboarding process. In addition, the software provides out-of-the-box solutions to prevent fraud across the entire customer lifecycle and can be customized to meet the client’s specific needs. The best-in-class machine learning methods we use can quickly adapt to changing fraud trends without requiring client intervention. Visit for more information.

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