ChatGPT for Credit Unions: Promises and Pitfalls of Large Language Models

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ChatGPT and Large Language Models are dominating the news cycle and seemingly taking control over the  future of tech. The opportunities are truly limitless. But, unlike others, we at Posh aren’t going to apply the technology without a robust understanding of its capabilities and proper guard rails in place. 

If you’ve used ChatGPT, you know its impressiveness. The vast knowledge it contains and spits out in an understandable piece of writing, code, recipes or poems can’t be understated. But it doesn’t come without pitfalls. 

“One of the strange things about these technologies [GPT-3, ChatGPT] is that they're impressive, and so you use them in a first demo, you have this, 'wow this is incredible and ready to go.' [But] you use them a hundred times and you see the weaknesses... There's a false impression of how good they are. However, that's all going to get better,” Sam Altman, CEO at OpenAI has been quoted saying

Posh was founded to democratize access to cutting edge AI technology for all financial institutions regardless of size or charter. Each should have the opportunity to foster the status quo-changing innovations happening in Fintech. 

While ChatGPT excels at:

  • Question-answering
  • Summarization
  • Content generation
  • Language translation 
  • Content editing 
  • Code completion / correction
  • Language style transfer
  • Entertainment / chit-chat. 

It’s not verticalized like Posh, which hosts a massive data set of financial institution specific information. Our team is navigating risk via clever mixing of understanding and constrained generation. 

The topic is vast, complex and interesting. While we don’t claim to have all the answers, we’re exploring the possibilities of how it will be applied to better understand and serve members. Posh is here to help navigate and partner in that journey. 

Want to learn more about ChatGPT and how Posh can partner with your institution? Get in touch at hello@posh.tech. 

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ChatGPT for Credit Unions: Promises and Pitfalls of Large Language Models

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March 17, 2023
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