Rent payments, cellphone bills, even social media history—some lenders are considering alternative data and processes to gain more insight into credit risk.
By Beth Mattson-Teig
The fundamentals of credit analysis remain firmly in place, but some institutional credit scoring methods may be due for an overhaul.
The debate on how to integrate alternative data, such as rent payments, utility and cellphone bills, into the credit scoring process has been raging for years. Now, initiatives by the Consumer Financial Protection Bureau (CFPB) and the Federal Housing Finance Agency (FHFA) are bringing credit scoring methodology to the forefront of their discussions. Both agencies have launched inquiries into ways to expand access to credit for consumers who are “credit invisible,” meaning they lack enough credit history to obtain a credit score. Lenders, too, recognize the need for alternative data sets and processes to reach the credit-invisible market. By some industry estimates, this segment of the US population includes millions of students, current and former members of the military, immigrants, and seniors and retirees who do not rely heavily on credit.
Mobile payment options like Google Wallet and Apple Pay are also driving the shift to alternative data. At the same time, powerful data-gathering and analytical tools now allow financial companies to create a more detailed profile that can be used not only to analyze credit risk but also to provide fraud protection, identity verification and even manage customer relationships.
“There is no denial that the microchip and the digitalization of banking is changing the face of banking and, in my opinion, changing underwriting,” says David Reiling, CEO of St. Paul, Minn.-based Sunrise Banks, which has assets of $800 million. “We are still trying to solve the basic five Cs of credit [character, capacity, capital, collateral, conditions] that have always been there, but we are doing it in much different ways.”
Credit where it’s due
Credit scores from FICO and VantageScore are standard fare in underwriting credit risk today. Those credit scores are embedded in the automated mortgage underwriting engines for both Fannie Mae and Freddie Mac. Many banks also use credit scoring models in evaluating other types of credit.
ICBA supports the FHFA and CFPB’s exploration of alternative scoring methods to qualify credit-invisible customers, notes Ron Haynie, senior vice president of mortgage finance policy for the association. The caveat: ensuring those alternative data tools are fully vetted before being put in place. (See sidebar, below.)
To some extent, the agencies’ push to expand the scope of alternative data used in evaluating credit risk is something many community banks are already doing. “We have always based our lending decisions not just on credit scores,” says Ann Seiss, vice president and retail lending officer at Frederick County Bank, a $400 million-asset community bank based in Frederick, Md. “We look at the whole picture and base our decision on common sense as best we can while staying within regulations.”
For example, a customer might come into the bank every Friday like clockwork to deposit a paycheck, or the bank may get a reference from a landlord that says an individual pays their rent on time every month. That information provides insight into the customer’s behavior, lifestyle and ability to pay.
“So community banks have always looked at some forms of alternative data,” Haynie says. “It just might not be the same forms of alternative data that people are advocating for in different credit models.”
But what exactly constitutes alternative data? The term has an increasingly broad interpretation, with a lengthy list of data sets ranging from debit card transactions to social media history. Payment and transaction-related data, such as a history of paying rent, utility and telecom bills, help illustrate trends and patterns. How does someone shop on the internet, what devices does that person use, what stores does he frequent? Other data sets focus on change of address, phone numbers and email addresses, as well as a person’s occupation or educational attainment, schools attended and jobs held. “All of those things may have some correlation with a person’s stability,” Reiling says.
Some view alternative data simply as a deeper dive into financial data in checking and savings accounts. “You are not just looking at a balance, but what comprises that balance,” says Terry McKeown, practice manager at Credit Analytics at Envestnet | Yodlee, a data aggregation and analytics platform for digital financial services. “What is the cash flow like? How are they spending? What is the frequency of their paycheck? Do they have other sources of nontraditional income, such as from Uber or Airbnb? That level of detail is not something that is typically captured by the credit bureaus. So it allows you to get a more complete picture of someone’s financial situation.”
The digitization of banking and fintech solutions is helping banks access a wider variety of financial data that is better, faster and cheaper. “You still need to make sure that you are lending money to an individual that has the ability to pay,” says McKeown. “But because people are using data and their financial tools differently, we need to be able to access more of that data in a different way.”
Beth Mattson-Teig is a writer in Minnesota.