One of the more alarming trends banks face is their inability to win over young consumers, which more than any other generation look for alternatives to credit cards.

A startup, Petal, is using machine learning in its new card program to make the most of the scant financial data available from young consumers. It aims to create a more accurate view of credit this audience's credit, ultimately using this data to make better offers.

"We're looking at young people who are getting their first credit card, someone who's transferring from debit to credit, or someone from overseas that doesn't have large track record in the U.S.," said Jason Gross, CEO of Petal, which is targeting consumers generally between the ages of 18 and 29. This age group may have a poor relationship with banks and often looks to P-to-P apps or installment payment apps to move money or finance larger purchases.

Petal will rely on the limited savings account history of consumers who have checking accounts but not credit relationships; and other digital financial records from the consumer.

"We can use that information to gain a better understanding, and to lower interest rates and eliminate other fees," Gross said, contending machine learning can build a credit profile for a consumer years ahead of what traditional credit reporting allows. "It's not a creditworthiness issue for these consumers; it's a data problem."

Petal's analysis is in some way similar to how merchant lending services from companies like Square or PayPal operate. In these examples, the lender uses sales data gathered through their point of sale offerings to inform a decision on whether to extend capital to a small business.

"The analogy to Square Capital is apt here," Gross said. "Square uses cash flow to better understand their clients. Petal applies a similar model to consumers rather than small businesses, but the tech backbone is similar."

While Square has kicked the tires on consumer loans and PayPal has sought to deemphasize consumer credit, Gross said Petal's model is closer to the merchant lending products, in which an active balance sheet is analyzed for underwriting to build deeper financial services.

In that way, Petal will be also be similar to Moven or Simple, two ventures that use simple payment products such as prepaid accounts to build a predictable base for a deeper financial relationship in the future that may involve credit. Petal will a bank partner, that it has not announced yet, to issue the cards.

Other companies like Affirm and PayPal are using AI to promote online credit services that are designed to compete with credit cards, with millennials being among the largest users of alternative credit, according to Michael Moeser, who heads the payments practice at Javelin Strategy & Research. "These fintech startups and nonbanks are using AI to their advantage in promoting credit offers to consumers when they are most likely shopping or in the process of shopping."

AI can speed the gathering of noncredit data, Moeser said, noting Kabbage, SoFi and other online lenders use AI to qualify leads and assist in underwriting when using non-credit bureau data.

There are some complications with marketing credit cards to young people, Moeser said, noting the Credit CARD Act of 2009 which stipulates people under 21 can't get a credit card unless a parent cosigns or the applicant can prove independent income that supports a credit card.

"Further, since card marketing to college students was also banned, people getting ready to start their first job generally don't have a credit card," Moeser said.

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