How Advia Credit Union generates $2.7 million in new auto loans with Faraday’s consumer product recommendations

Advia Credit Union's mission is to provide financial advantages to its members through solutions that address life's evolving needs, including mortgage refinancing, debt consolidation, and auto loans.

The problem: engaging customers with the right message

The average American holds eight financial products, yet only 19% of Americans have three or more products with their primary financial institution. For many credit unions, including Advia, growing their "wallet share" with existing members is key to their long term stability and success. The challenge is how to do this effectively. There is brand risk in simply bombarding members with unsuitable offers that could result in members ignoring all communications from the credit union. Worse, it could erode trust, create frustration, and sow overall member dissatisfaction.

For Advia, they needed a way to understand the personalized financial journeys for each of their members so that they could surface the next best product recommendation for each member. Such an approach would ensure optimal use of their marketing budget, minimize member dissatisfaction, and help grow wallet share with their members.

The obstacle: using data and remaining compliant

Advia understood that their member data likely held the key for developing next best product recommendations. Unfortunately, their lead data scientist had recently left the organization, and Advia was looking at a lengthy ramp period to hire and onboard someone new.

Additionally, Advia needed to navigate a complex regulatory landscape. Advertising lending products comes with stringent compliance requirements to ensure fair lending practices and protect consumer privacy. The Equal Credit Opportunity Act (ECOA), for example, prohibits discrimination in credit transactions based on race, color, religion, national origin, sex, marital status, age, or receipt of public assistance. This means any data used for segmentation in advertising must not incorporate these protected classes, either intentionally or unintentionally, to avoid violations.

Why Faraday?

To address these challenges, Advia partnered with Faraday. Advia used the Faraday platform to determine which of their primary retail financial products should be surfaced to each member. They initially tested this by looking at which members should receive information on their auto loan product.

Advia linked its historical member data with Faraday's identity graph, including information on member adoption of Advia's auto loan. With this training data, Advia created a set of predictive models that scored each member's propensity for an auto loan. They also leveraged Faraday's bias identification and mitigation features to address historical bias in their training set, aiding their fair lending compliance efforts.

With Faraday's product recommendations in hand, Advia could segment their audience more intelligently. They identified the top percentile of members most likely to complete an auto loan application and targeted them through both personalized email and direct mail campaigns. This targeted approach ensured that the most relevant offers reached the right members, enhancing engagement and increasing the likelihood of loan applications.

The results

The success of Advia's auto loan campaign was measured by the percentage of recipients that completed auto loan applications. Before using Faraday, Advia's benchmark for success was a 1.19% application rate.

30-Day results: After just 30 days of running the campaign that used Faraday's recommendation, Advia achieved a 2.41% application rate. This significant improvement resulted in $1.1 million in new auto loans.

90-Day results: The application rate continued to grow over the next 60 days achieving a 5.18% application rate after 90 days. This increase in engagement led to a total of $2.7 million in new auto loans, far surpassing the initial benchmark.

Advia Credit Union's use of Faraday's platform demonstrates the power of personalization and predictive analytics. Faraday gave Advia the ability to target the right members with relevant offers, leading to higher engagement and significantly improved loan application rates.

This approach not only boosted Advia's campaign performance, but also boosted Advia's regulatory compliance efforts, while safeguarding member trust. Advia's use of the Faraday platform exemplifies how financial institutions can harness data to drive better outcomes, provide superior service to their members, and use AI responsibly.