People helping people – Where is the room for AI?

The credit union movement was founded on the ‘People helping People’ philosophy. It has been over a hundred years since the incorporation of the first credit union in the US – still, credit unions continue to operate with the same philosophy. Millions of Americans and under-served communities have benefited immensely from the credit union movement.

These not-for-profit institutions serve more than 131 [1] million members by always putting their members’ needs first and helping them achieve their personal goals through sound financial practices and targeted advice.

Behind the ideology of people helping people lie many challenges. Credit unions must stay profitable, efficient, and provide the best services for their members. They experience economic, technological, and financial pressures. With ever-evolving behavior, members expect credit unions to adapt their offerings to the changing needs. Failing to adapt quickly results in sub-optimal service to members and a struggle to manage operations efficiently. In many instances, these issues lead to losing members, driving up losses, and ultimately, dissolving. There were nearly 24,000 credit unions in the US at the peak of the credit union movement; this has since dropped to just over 4,900 [2] today.

Even though all credit unions operate with the people helping people philosophy and employ a large support team, most cannot actively engage and support over 60% of their members [3][4], leading to a loss in revenues and poor member satisfaction.

Member services challenges have increased

One of the most significant challenges credit unions have recently faced is the increase in call volumes. Traditionally, call center and support operations have been challenging due to staff attrition, hiring, and training issues. Since the pandemic, there has been a change in member behavior resulting in increased call volume which has remained even after the reopening of branches. This increased stress on call centers has led to increased abandonment rates, increased call wait times, low-resolution rates and overall, a poor member experience.

Let us take a more in-depth look at support and call center operations in credit unions to understand the root causes of these issues. For this study, we have aggregated call center data across 300 credit unions, and below are the findings:

  • Today, 50-60% of total calls pertain to questions on basic information on products or accounts.
  • Another 10 – 20% of the total calls handled are to help members perform transactions such as transferring funds, bill pay, etc.

To summarize, most member support functions spend up to 80% of their time [4] answering basic questions or processing simple requests for members that are meant to be addressed swiftly. By spending such large amounts of time on such inquiries, the staff at credit unions lack the bandwidth and cannot tend to members who need financial advice.

The ‘people helping people’ philosophy was built on supporting members in need, offering them sound financial advice, helping them on the path to financial wellness, and not just helping them complete simple tasks such as providing details of accounts or answering FAQs.

For credit unions to stay true to their philosophy, they need to ensure their staff has sufficient bandwidth to support all members. In today’s world, where issues with traditional member support operations persist, and resources for credit unions are constrained, the only way credit unions can efficiently support each member in a prompt & timely manner is by leveraging Artificial Intelligence (AI).

How can AI help credit unions continue to operate by their core philosophy in today’s times?

With AI, credit unions can automatically handle high-frequency questions from members, thus freeing up the support staff to engage members in need. Credit unions can offer instant support to members 24×7 and manage increased call volumes without hiring additional staff, thereby bringing call abandonment rates and wait times to zero. It can bring down the cost per call from over $1.50 per minute to less than $0.20 per minute enabling thousands of dollars in savings [5]. It also engages members through financial insights and drives revenues through up-sell and cross-sell.

With AI, CUs can extend their support to all members and not just a fraction of the membership. Instead of responding only to many straightforward inquiries, staff will be able to spend more time providing sound financial advice to members in need and helping them achieve financial wellness.

AI will enable CUs to operate efficiently even during testing circumstances and allow them to stay true to their philosophy of ‘People Helping People.’

 


  1. The provided numbers have been taken from National Credit Union Administration -Quarterly Credit Union Data Summary 2022 Q1
  2. The provided numbers have been taken from National Credit Union Administration -Quarterly Credit Union Data Summary 2022 Q1
  3. The provided numbers have been taken from the article ‘How Banks Can Grow Like Bank Of America, Chase, And Wells Fargo: The Reacquisition Imperative’
  4. As per a study conducted by interface.ai team involving over 300 Credit Unions
  5. These are actual results experienced by 70+ interface.ai customers such as University Credit Union, Dover FCU, Neighborhood CU, Security Service Federal Credit Unions and many more.
Srinivas Njay

Srinivas Njay

Srinivas Njay is the founder and CEO of interface.ai. interface.ai provides an award-winning out-of-the-box Intelligent Virtual Assistant that acts as a “personal banking teller” to help customers 24/... Web: interface.ai Details

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