To get bigger partners, fintechs must see past consumer fear
Fintech developers are trying to monetize data without scaring away privacy-conscious consumers — and, increasingly, to make sure bigger financial companies don't overstep the same boundaries.
In the wake of deals such as Mastercard and Google’s reported data collaboration, and Facebook’s attempt to pry more customer info from banks and collaborate with merchants to boost Messenger, fintechs are finding new ways to participate in the big data economy.
To be successful, fintechs will have to produce technology that allows banks, merchant acquirers, digital payment gateways and processors to credibly claim that the data that is being shared, crunched and analyzed is not being exploited or dangerously exposed to unwanted parties.
And there is an appetite for this technology. Capgemini on Friday published research that found 87 percent of banks plan to use customer data to crate “smoother customer journeys,” and 75 percent plan to develop relationship based pricing. Also, 58 percent plan to personalize incentive marketing. More importantly, three quarters of banks plans to collaborate with “big tech” or fintech providers to do this.
“If you’re using AI, then let’s join my data with your data. The next frontier collaborating with data, let’s get a higher level of utilization,” said Alon Kaufman, CEO and co-founder of Duality Technologies, a Cambridge-based startup. “When you do this, you are exposing data and opening up to the algorithms of the companies that you want to collaborate with.”
As these big data deals start to become the norm, expect to hear more about double blind encryption. The term came up in Google’s defense that it issued when the Mastercard collaboration became public, saying it prevents Google and its partners from viewing personal information, or accessing personal information from credit cards.
“Imagine you put the data into a black box and manipulate the data that’s in the box,” Kaufman said. “We never see the data and the third party never sees it, but it can be applied for analysis while it’s in the black box.”
Duality contends homomorphic encryption, or using code and programming to protect data identified as sensitive while allowing data of computational value to be shared, can power analysis while shielding privacy. Duality has found traction in the health care and automotive industries for the technology, but is focusing on the payment and financial services industries as data analysis increases for marketing and digital commerce.
“A bank offering a new payments product could use this to improve risk scoring or a marketing mechanism without either side on a collaboration seeing all of the data, or without a third party accessing data,” Kaufman said.
Another startup, Clarity Money, has several products in its pipeline to enhance its data management technology.
Venture capitalist Adam Dell founded Clarity in 2017 to use machine learning and advanced computing to do a deeper dive into product strategy. For example, it uses its internal engine to recommend steps such as canceling unused subscriptions, matching card options to a user’s payment tendencies and negotiating terms for recurring bills and savings accounts.
The fears around data and privacy security are less about the innovation and more about a sense of control, according to Colin Kennedy, chief operating and revenue officer for the New York-based Clarity Money.
Data sharing among large institutions in some ways works against the decentralized nature of consumer data. But there is a chance to use AI and related innovation to earn user trust by delivering better service and a more personalized experience, according to Kennedy.
“What gets misunderstood is consumers want to be able to share data with partners they choose,” Kennedy said. “Consumers will engage with multiple companies or sources of insight as long as there is a sense of trust.”
Another challenge comes from acting too quickly or placing the technology's capabilities ahead of the use case — Zafin’s Don Halliwell contends the ample benefits of improved data sharing and analysis could also raise the ire of regulators.
A Toronto-based startup, Zafin sells technology that helps banks take advantage of data sharing by tying activities such as e-commerce payments at a small business to broader financial services.
The new technology merges two types of data—financial information and spending habits, Halliwell said. When this information is combined, advertisers can make offers more relevant or the dots can be connected between loans and related financial services.
This power should be as public and transparent as possible, Halliwell said, adding consumers should be aware of how the technology is being used as a way to assuage fear and keep regulators at bay.
“If you collaborate too much you can accelerate regulations that may not be beneficial,” Halliwell said.