Can A.I. Marketing Help Both Customers and Companies?
A panel of experts from academia and industry discusses how marketers can use A.I. responsibly.
Can A.I. Marketing Help Both Customers and Companies?In the European Union, open banking is transforming finance. Regulations are enabling consumers to control their banking data and share them, if they wish, with third parties such as fintech companies. The aim is for this to promote competition and allow innovation to flourish—moving us more quickly toward lower-fee banking and perhaps even a cashless society.
But the idea has critics, among them Mick McAteer of the United Kingdom’s Financial Inclusion Centre. In 2017, he called it a “daft idea” and told the BBC News it could lead to consumers being exploited. And research by Chicago Booth’s Zhiguo He, Booth postdoctoral principal researcher Jing Huang, and Yale’s Jidong Zhou outlines how consumers could indeed be worse off with open banking.
Traditional banks serve as gatekeepers for a lot of customer data. Allowing data to circulate more easily would promote more competition between banks and fintech companies, the latter of which have pushed innovation and automation in everything from lending and trading to advising and digital currencies.
Giving customers the ability to share their data more widely could net them better deals. It would make banking data portable, lower prices, and potentially unleash yet more innovation. EU regulation is pushing banks hard in this direction, having mandated them to change their back-end infrastructure to allow for data sharing.
The researchers worked through the potential theoretical outcomes of loans, and offer some notes of caution. On the surface, open banking may be good for customers by forcing big banks to open up and allow competition from young upstarts—but the costs rise as those young upstarts mature.
The first potential problem He, Huang, and Zhou identify involves an information externality: a consumer who chooses to share data may hurt other consumers. Say one banking customer voluntarily shares her data with a bank and a fintech lender, choosing to reveal her own banking history in hopes of qualifying for a lower rate. But while the fintech lender learns about her spending history, it also infers things about customers who are less willing to reveal their information. In the short term, what’s good for one open-banking customer has costs to others.
The second risk is what’s called the winner’s curse. Take the banking customer who shares her data. If she’s coming to the fintech lender for a loan, it’s presumably because she doesn’t like the rate her bank is offering. The fintech will do its own assessment, just as the bank had done. Say the fintech lender beats out the bank. It may be because the bank identified some risk factor and figured it into its calculations. The fintech has fallen prey to the winner’s curse: it got the customer, but it’s also taking on risk that it didn’t detect but the bank did.
A panel of experts from academia and industry discusses how marketers can use A.I. responsibly.
Can A.I. Marketing Help Both Customers and Companies?Much of the growth is due to regulations that have pushed banks out of traditional lending businesses.
What’s Driving the Growth in ‘Shadow Banking’The winner’s curse is rooted in information asymmetry, the balance of which is likely to shift as fintech lenders grow. Right now, many fintechs are essentially software startups, some of which have powerful abilities to analyze data of all kinds, such as social media postings. Open banking gives them access to far more data. Eventually, when they offer a rate to a consumer, it could be one that’s really precise. A traditional bank would be outmatched, loathe to underbid such a competitor because doing so would mean it would have failed to spot something that the fintech’s powerful models had identified. “It’s a much bigger winner’s curse situation,” says He.
Importantly, the existence of both risks—the information externality and the winner’s curse—means that all parties can be worse off in equilibrium, even if everyone who owns data is able to voluntarily opt out and refuses to share those data. Open banking would allow a fintech to analyze so much information that it could come up with a precise rate and scare away other competition. But if a banking customer anticipates this and decides not to share his data, so long as others are willing to share, the fintech can still infer information about him.
The researchers identify yet a third risk: precision marketing. Companies are learning to market to consumers in real time—for example, by texting a coupon to a shopper whom they know to be in a store. Fintech lenders could act similarly if, for instance, they know a banking customer is traveling and needs cash quickly, and could factor this information into their offered rates.
“As the global discussion unfolds, many practitioners and policy makers expect ‘open banking’ to represent perhaps the most transformative trend in the banking industry in the coming decade,” write He, Huang, and Zhou. But it’s a trend that may look better when fintechs are small—and less so when big banks start competing with big tech.
Zhiguo He, Jing Huang, and Jidong Zhou, “Open Banking: Credit Market Competition When Borrowers Own the Data,” Working paper, November 2020.
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