Leveraging AI to go beyond the data
Data has always been foundational to the financial services industry. On a daily basis, credit unions have access to a myriad of data points and information—ranging from credit and debit card transactions to how members prefer to interact with their credit unions, among others. But are credit unions putting this data to its best use?
The richness of data comes to life when credit unions are able to take data insights and determine next steps that drive best-in-class member interactions. That said, the amount of data credit unions have access to can be overwhelming, and adding the layer of determining how to best use it—and doing that in the most efficient way possible—can add to that challenge.
As technology has advanced, data literacy across all levels of an organization has become more and more essential to efficiency, agility, responsiveness and member engagement. One way to help address data literacy and put data to use is by leveraging artificial intelligence (AI). With the help of AI, credit unions and their employees can not only analyze data effectively and efficiently, but they can also develop actionable insights to help create seamless and cutting-edge experiences across all of a credit union’s channels.
Making better use of AI
For many credit unions, the first step to harnessing the power of AI when it comes to data is helping your credit union and employees become more AI literate. There will be opportunities to save money, make money and mitigate risk using AI. First and foremost, however, is the possibility to reduce friction in all experiences, whether internal or member-facing.
Many day-to-day jobs can be tedious. If AI can help streamline mundane tasks, then resources can be focused on other things.
When considering generative AI, many people might first think of tools like ChatGPT that can be used to develop content ranging from text to audio, video, code and more. However, the use cases for this technology go far beyond just that. For example, a big area of opportunity is helping employees balance providing exceptional member experience with being efficient. There can be opportunities for operations enhancements or streamlining efficiencies in contact centers.
AI could be utilized to scan all calls coming into a credit union contact center and identify the top 10 reasons why people are calling. Then, solutions can be developed to address the problems for which members are calling—so they don’t have to call at all—thereby improving your members’ experience and allowing your employees to spend their time on other areas. AI also has tremendous potential to help with personalized services for your members. Another potential use case for AI is an application that helps your members identify how much money they spend on subscription services and asks them to consider canceling the services they don’t use, in order to save money and improve their finances.
Technology is about people
Looking ahead at the next five years, credit unions will continue to be faced with determining how to evolve their culture and processes to keep up with technology and member expectations. Based on many estimates, AI is likely to impact about 30% of the jobs in the financial services industry overall. While some jobs do have the potential to be eliminated, other jobs will almost certainly be created by this technology. When it comes down to it, AI and other tech advances are making the people in our industry more important. People are needed to leverage the full capabilities of the latest technology.
Creating a data culture
The journey to data literacy is a combination of technology, process and people. The people component can be the hardest part. It begins with getting key team members familiar and comfortable with data. A recent McKinsey study finds that 50% of employees avoid or find alternative solutions to data-related tasks—which is unsustainable in the age of AI.
Understandably, no one wants to be thrown into the deep end of data without knowing how to swim. Data literacy does not require technical skills or knowing how to program. The biggest shift must be in the data culture of your enterprise. It’s one thing to teach a process; it’s another to understand why you need that process.
Ultimately, the outcomes for credit unions are measurable, including metrics like value acceleration, time to close or time to resolution—in other words, efficiency and value generation. Used strategically, generative AI can serve as a force multiplier for a data-literate organization.
Embracing the power of AI
We are at an inflection point when it comes to embracing AI and its use cases. The opportunity—and responsibility—is to take a step back and visualize the credit union of the future. How do you want to serve your members? What is your forward-thinking strategy and how do you look at data technology as an enabler of that? What does it mean for your talent and organizational culture?
AI is going to disrupt the financial services industry significantly, but it comes with many opportunities—from data enablement to efficiencies. Better, more intelligent and more personalized service will improve member relationships in ways never possible before. Credit unions that proactively develop competency with generative AI and view it as an enhancement rather than a threat, are going to have a significant advantage over those that don’t. Let’s embrace that challenge and the benefits that can be released from AI.
