Out of the Trenches in the Battle Over Bank Customer Data

Fintechs and banks have been at odds with one another over customer information since the first moment that someone somewhere decided “fintech” was an actual word. American Banker reports that the icy relationship may be thawing.

Fintechs have been arguing that they need to access bank customer account data to provide a variety of services, including online loans, personal financial management, and integrated savings apps. Understandably, Banks have been slow to provide such information and are unhappy with fintechs grabbing it by logging in with customers’ user names and passwords.

“Over the course of the past nine months in particular, the flywheel is starting to spin,” said Brett Pitts, who is head of digital for Wells Fargo virtual channels. “We’ve been talking about a lot of the mechanics, plumbing, and cross-industry dynamics that are important and we’ve made some progress. There’s a whole lot more progress to make.”

Recently, Wells signed data-sharing agreements with Intuit, Xero, and Finicity, and recently announced two more such agreements with Expensify and PointServ.

The Consumer Financial Protection Bureau’s data-sharing principles and increased communication among financial firms, aggregators, and fintechs have lead to legal agreements through which banks share customers’ account data, typically via an application programming interface, with details around data use, consumer consent, and liability largely settled by lawyers.

“We’ve come a long way over the past year or two, starting with the CFPB’s request for response in January,” said Becky Heironimus, vice president of enterprise digital products and data connections at Capital One. “The fact that we’re talking about it is a huge step forward. The fact that the CFPB published guardrails is a huge step forward. We’re going to need to keep the conversation going as technology changes.”

This move opens up improved data extraction of information from transactions which can feed data mining and predictive analytics applications, i.e. grabbing the payee on checks and using it for fraud or marketing.

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