How Wells Fargo uses AI

Wells Fargo deployed a retrieval augmented tool for branch bankers that finds the relevant policies and procedures during customer interactions. Google Cloud reports that it reduced the workflow for query resolution by about 20%, without saying whether that means time, steps or effort. The bank uses reusable APIs on Apigee to scale generative AI across teams.

No outcome disclosed.

Wells Fargo's Fargo virtual assistant, built into the Wells Fargo mobile app since 2023, helps customers send money with Zelle, pay bills, locate routing numbers and gain insights into their spending and account balances. The bank reported that Fargo has now supported customers through more than 1 billion interactions, reached in under three years since launch, and that more than 3 million Spanish speaking customers have used it, engaging with the assistant over 160 million times.

• Interactions handled: at least 1 billion, since Fargo's 2023 launch, reached in under three years

  "Fargo has now supported customers through more than 1 billion interactions – achieved in less than three years since its launch."

  Claimed by: organization

Wells Fargo Bank patented a computer based credit evaluation system that pairs a machine learning credit risk model with an adverse action methodology: when the model denies an applicant, the system compares the applicant's characteristic values against anchor values taken from a top scoring population, calculates a replacement score for each characteristic, and ranks the characteristics to identify the principal adverse action factors for the denial. The United States Patent and Trademark Office granted the patent in October 2022 on an application Wells Fargo filed in October 2019. Separately, the trade publication Risk.net reported in August 2021 that a team of Wells Fargo researchers had begun deploying an explainability technique for its deep learning credit models, and a paper by six Wells Fargo model risk researchers proposed a related Shapley decomposition method for explaining adverse credit decisions. No outcome metric or notice volume is disclosed by any source.

No outcome disclosed.