Five of The Best: Top AI Guides and Case Studies for 2024

Artificial intelligence is a tricky space to navigate in the banking industry, making it a hot topic in our coverage at The Financial Brand. Here are our top five stories covering artificial intelligence and generative AI that no banker can miss.

1. A Banker’s Guide to Digital and AI Transformation Success

Author: Jim Marous (The Financial Brand)

Date: July 5, 2023

Executive summary: Inside his new book, “Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI,” Eric Lamarre and his co-author took a deep dive into the digital transformation and AI imperatives that every banker should be keeping an eye on.

Jim Marous interviewed Lamarre on the Banking Transformed podcast in mid-2023 to talk about the book, which found that long-term success comes when leaders are willing to embrace changes related to talent, their operating model, technology and data capabilities. Check out Jim’s conversation with Lamarre.

A key takeaway: Across all industries, 87% of firms have pursued some form of digital transformation in the past two years, but have captured only 31% of the revenue lift they expected, according to a McKinsey & Company global survey.

2. How to Get Comfortable with Generative AI in Your Marketing Strategy

Author: Kevin Farley (United Heritage Credit Union)

Date: June 14, 2023

Executive summary: There are a million and one articles boosting generative AI and its importance to certain industries. Very few experts provide a strategic approach to generative AI for banks and credit unions. That’s why we recruited Kevin Farley for this piece, who provides a crawl-walk-run process for trying out GenAI.

Quotable: “There’s no doubt that artificial intelligence, particularly generative artificial intelligence, has enormous potential to revolutionize the way financial institutions approach marketing. But nobody is suggesting a reckless or uninformed embrace of this technology. Like any powerful tool, it requires careful and strategic implementation, starting with small experiments and progressing to full integration.”

3. Lessons from Ally’s Experiment with GenAI Marketing: Commit, But Carefully

Author: Steve Cocheo (The Financial Brand)

Date: December 4, 2023

Executive summary: How many banks and credit unions do you know of that have actually started experimenting with generative AI in a deep way? Look no further than Ally Financial, whose marketing efforts are spearheaded by Andrea Brimmer. Brimmer and her marketing staff spent the second half of 2023 experimenting with OpenAI’s ChatGPT. What has Brimmer learned so far?

Quotable: “You’ll only get 30 days to prove out the value. If you don’t, then you have to leave the Ally.ai platform. You’re out of the sandbox. You’ll have to come up with a different use case.” — Sathish Muthukrishnan, Ally Financial

4. ChatGPT Will Become ‘ChatOMG!’ in 2024, Forrester Predicts

Author: Steve Cocheo (The Financial Brand)

Date: November 1, 2023

Executive summary: ChatGPT is just one in a heaping pile of new large language models (LLMs) that are developing in the artificial intelligence field. Even though the technology is gaining traction in banking, Forrester predicts the industry will see mishaps in 2024 as GenAI usage accelerates. Find out why.

Quotable: “Large language models are pretty darn opaque, and banks know that. So they’re designing their compliance and regulatory efforts to try to avoid any exposure. But there’s going to be slip-ups.” — Peter Wannemacher, Forrester

5. Unleashing the Power of Generative AI: Three Use Cases for Payments

Author: Safwan Zaheer (HundredX)

Date: September 21, 2023

Executive summary: Artificial intelligence isn’t only penetrating traditional banking  — it’s also infiltrating payments. Fintechs like Stripe and Klarna are already dominating the payments game with the help of advanced artificial intelligence technology. Should your bank or credit union delve further into AI?

A key takeaway: To get started with generative AI, payment companies should follow these actionable steps:

1. Develop generative AI literacy: Educate teams throughout the organization on the technology, use cases and potential implications. Bringing in experts for training will foster a positive culture of responsible adoption.

2. Build a North Star for generative AI: Formulate a practical strategy and roadmap, aiming for a generative AI “North Star.” Identify areas within the business that can benefit from GenAI and determine desirable use cases while keeping the associated risks in mind. Check out the three other steps.

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