I recently participated in the Fintech Panel on Practical AI Use Cases at the 2018 Symitar Educational Conference (SEC). It was great to see that there's a lot of excitement about AI and how it's being used by credit unions and other consumer finance organizations.
On top of that, Jack Henry did an amazing job of organizing the panel, providing valuable insights to attendees in varying stages of AI adoption by bringing together participants from companies operating in very different areas of the field.
- Infosys consults on large-scale AI projects, helping credit unions and banks develop complex, in-house capabilities to be applied across numerous business functions.
- Clinc specializes in advanced conversational AI, helping banks develop, train, and deploy superior conversational AI solutions.
- Faraday, yours truly, specializes in AI-powered customer lifecycle optimization, helping credit unions, banks, and fintech platforms better understand their consumers, personalize experiences, and improve member interactions from acquisition to retention.
The big takeaway
We covered a lot, but the biggest concern in the room was how credit unions with little to no experience with AI can operationalize the right solutions quickly.
There are seemingly endless ways AI is being used by innovative consumer finance organizations. Every day, we're hearing about new, creative ways organizations are applying data science and machine learning to extract more value from their data. Frankly, it can become overwhelming for credit unions that are just getting started.
You're not going to transform every process with AI overnight (or even over the next year). Start with one or two solutions that are relatively easy to implement and will yield significant results in the short term.
If you're considering using AI to draw deeper member insights, personalize experiences, and optimize outreach, Faraday can get you up and running in 6-8 weeks. Here are a few ways to get started:
