AI coupled with an open banking framework provides better access to credit for consumers. 

The technology presents an opportunity for consumers with limited credit to obtain loans and make payments, Ben Soccorsy, head of data access and business development at Mastercard, said this week during the Finovate Fall event in New York City.

By combining AI and open banking, financial institutions can pull in additional, real-time data, including payroll information, to gain a better idea of a “consumer’s creditworthiness,” Soccorsy said. 

For more on open banking, register for the upcoming complimentary webinar presented by Bank Automation News: “The future of open banking: Payments meet data,” on Tuesday, Sept. 17 at 11 a.m. ET. Register for the webinar here.   

Nearly 21 million Americans are not eligible for traditional credit scoring mechanisms, but the use of alternative data can give lenders a clearer picture of their creditworthiness, according to a February report from credit bureau Experian. 

When data is shared with financial institutions via open banking, AI can be tapped to quickly look beyond a consumer’s credit score and into their transaction history, cash flow statements and other essential financial metrics before decisioning takes place, Michael Chung, senior product manager at nCino, told Bank Automation News. 

“Financial statements are, by default, a lagging indicator,” Chung said. 

Financial services technology provider Plaid uses real-time data to determine an applicant’s credit worthiness based on credit risk, cash flow data and financial stability, according to the company.  

Financial institutions are “starting to look at the potential of using transaction data and having transaction data as a leading indicator [of credit worthiness], because you have near time access to the actual cash flow situation, and you can see if there is cash flow surplus or if there’s a cash flow deficit,” Chung said.