News!: Opus Technologies Launches FinGeniusAI Solutions – An Open Innovation Platform for Building Future-Ready Solutions.. Know More
News!: Opus Technologies Launches FinGeniusAI Solutions – An Open Innovation Platform for Building Future-Ready Solutions.. Know More

CEO’s Corner

Can Community Banks and Credit Unions Leverage AI Like Bigger Banks?

Share :

CEO’s Corner Series: Unlocking Intelligent Banking: A Deep Dive into the Impact of AI on Banking and Payments

About this series:

In this exclusive series, we will explore the world of Artificial Intelligence (AI) within banking and payments. This series will be a deep dive into how AI is transforming financial experiences, from fraud prevention and hyper-personalization to streamlined transactions and intelligent financial planning.

This is the fourth post of the five-part blog series. In previous posts, I have talked about the significant impact of AI in revolutionizing the banking and payments industry. I’ve also discussed the challenges in AI adoption– the cost of implementation, identifying the right entry point, navigating a limited talent pool, and achieving faster turnaround times. In this blog, I’ve explored the reasons that push community banks and credit unions toward AI integration. The blog identifies key first steps that will make AI adoption easier for smaller FIs. The era of intelligent banking and payments is upon us. Join me and explore the strategies to make AI work for you.

As bigger banks, FinTechs, and other larger financial institutions race toward adopting AI across all business functions, community banks and credit unions continue to follow a “wait and watch” approach. This reminds me of the digital transformation era, where community banks and credit unions were among the laggards in adoption. Given the huge investment made by large financial institutions in testing and implementing AI for driving ROI and improving customer experience, it is understandable that small FIs are still far behind.

In the digitalization era, smaller financial institutions stayed competitive due to their ability to offer personalized products and services to their niche customers. This is one strategy that sets them apart from larger banks and FinTechs. It was nearly impossible for larger institutions to work with granular data and cater to the specific needs of a narrow market. However, with AI being used for market analysis, understanding customer demand, and making personalized product offerings, large banks and FinTechs have the power to customize their offer for each individual. Community banks and credit unions are on the brink of losing their competitive advantage.

Lack of budget and staff constraints are the key reasons cited by community banks and credit unions in relation to slow technology adoption. However, AI is penetrating the industry at a much faster pace, and it’s critical for community banks and credit unions to carefully analyze the impact it will have on their market share and work toward a full-fledged implementation plan sooner rather than later.

Why AI is Essential for Community Banks and Credit Unions

Customer Engagement Rate:  According to the latest data from the National Credit Union Administration, there are 4,604 federally insured credit unions with 139.3 million members as of December 2023.  We also know that there are 4,429 community banks active across all 50 states in the U.S. as of Q4 2023, based on the data shared by Federal Deposit Insurance Corporation (FDIC). These financial institutions have always enjoyed a high customer engagement rate due to their proximity to the customers and non-dependence on the principles that rule Wall Street. In a recent study by Gallup, a think tank that monitors the performance of credit unions, 73% of members who felt that their credit union cared about their financial well-being were actively engaged. This kind of engagement pays dividends as it significantly increases the lifetime value of a customer acquisition.

Source: Customer Engagement at Credit Unions Is Slipping: Here’s How to Reverse the Trend, The Financial Brand and Gallup

However, Gallup has identified that this trend has started to fade gradually. In 2014, credit unions had an engagement premium of over 21% and a NPS (Net Promoter Score) premium of 29% over larger banks. By 2021, the engagement premium was reduced to just over +11%, and the NPS premium dipped to around +17%.

Align Products and Services for GenZ: The demographic shift in the customer base is another critical factor that will force credit unions and community banks to consider AI. The overall median age in the US is 38.5. In the near future, millennials and GenZ will be the primary customer base for smaller financial institutions. Gallup research has shown that GenZ customers are least engaged with their credit unions as compared to other age groups. The younger generation expects better customer experience, faster access to services and innovative products.

Need for Cybersecurity: Cybersecurity is a major challenge for the financial services industry. Without the right investment in IT, the data available with smaller financial institutions is vulnerable to ransomware attacks and fraud. To stay customer-focused, credit unions and community banks will have to procure cutting-edge technology solutions and protect critical data in compliance with the latest regulations.

Can AI Level the Playing Field for Smaller FIs?

In a recent study to understand the priorities of credit unions, 60% of the institutions agreed that it’s extremely important to identify new revenue streams to stay competitive in the market. Artificial intelligence could be the lever to make that happen.

With the right implementation of AI tools, smaller FIs can get access to key customer information that is typically missing from a standard credit report. Once the machine learning models are well trained, these tools can share a wealth of quality data and insights, such as financial patterns, customer behavior and potential credit needs. These insights can be used to deepen the relationship with their customers and offer customized financial services.

Some of the new revenue streams that community banks and credit unions can explore with AI are:

  • Offer a new product or service to a customer based on prediction-based credit needs.
  • Use AI tools for digital lending through automated credit score assessment and faster loan application processing.
  • Provide personalized customer services and resolve issues with minimal intervention through AI chatbots.
  • Partner with FinTechs to provide differentiated offerings.

Source: State of the Credit Union Industry Report, Research and Outlook for 2023, by WIPFLI

How to Strategize for AI Implementation

As the AI ecosystem continuously expands, it is important to consider its implementation from a solution approach. Asking the right question is the key. Instead of “How should I implement AI?”, community banks and credit unions should ask, “What customer problems can I solve through AI?”.

It’s important to note that smaller FIs can draw from their digital transformation experience and build on that to navigate the challenges faced in AI adoption. This is particularly important for hiring and retaining skilled talent as well as managing cultural change within the organization to support AI implementation.

I suggest these four strategies to ease your entry into AI:

  1. Appoint a leader who can define and take ownership of the AI strategy for the entire organization. The leader will be responsible for defining the initial set of use cases where AI can be leveraged, managing stakeholders, and creating a collaborative environment for the technology shift.
  2. Carefully monitor the points of interaction for the customers and understand the nature and volume of data collected from each interaction. This will be the goldmine for training machine learning models for personalized customer offerings.
  3. Review data strategy and make necessary upgrades so that the data flows seamlessly across channels and functions. It’s equally important to review data flow from legacy systems and plan upgrades to support smooth data exchange between systems.
  4. Focus on compliance requirements and security while planning AI implementation. AI is an evolving field, and strict regulatory compliances are on the horizon. Invest in solutions that can be trained on processes and workflows to meet industry-wide regulatory compliances as they evolve.

It is not mandatory to revamp the whole IT infrastructure for implementing AI. What is essential is taking a strategic approach to identifying key business problems and connecting them to a solution that AI can deliver. To stay competitive, credit unions and community banks must take swift action and exploit their wealth of data to deliver better services.

Remember, you don’t have to do it all by yourself. Finding a technology and innovation partner is a critical step in your AI journey. Opus Technologies has developed an open innovation platform, FinGeniusAI, to support credit unions, community banks, and small-sized financial institutions to understand and adopt AI. The platform allows financial institutions to discuss AI-based solutions for their business use cases with our payment experts, create a proof-of-concept (POC), and formulate an actionable roadmap.

The next blog will conclude this series on the impact of AI in banking and payments. I will address the cost component of AI adoption and how to measure ROI from an initial stage in the final blog. Stay tuned for more!

Opus Official

Praveen TM is a highly accomplished global payments leader with over 20 years of experience. A veteran in the payments industry, Praveen has immense wealth of insights to share in payments innovations, emerging technologies, FinTech, and financial services.

Join our mailing list to be the first to know about industry news, Opus updates & upcoming events

    Please read our Privacy Notice to know how we protect personal data