Can Alternative Data Move The Dial For Financial Inclusion?

28. May 2018.








In the early 1950s, an engineer named William Fair encountered a mathematician Earl Isaac who together decided to work out an automated credit scoring system for banks. In 1954, they came-up with the first version of the Fair Isaac credit score — or the FICO.

It was a huge flop.

Banks didn’t trust that an automated system could do nearly as good a job as personal bankers when it came to evaluating customers and their likelihood to repay.

But the two continued to work and refine the system using ever-improving computer technology — and by 1958, they started to see buy-in from banks in the U.S. and around the world. The system got a major boost in the 1970s with the passage of The Fair Credit Reporting Act, which officially regulated what information would be collected as well as created rules that made credit reports something consumers had a legal right to both see and dispute.

FICO was an ideal fit for the FCRA world, and has been the dominant credit scoring model in the United States for over four-and-a-half decades as a result. Without a reasonable FICO score, home buying (with mortgages) auto-loans, credit cards and even simple checking accounts all become out of reach for consumers.

But is FICO keeping pace with modern financial services? And if not, does it need to be supplemented — or perhaps supplanted — by other data streams? That is the question posed by Experian’s first ever The State of Alternative Credit Data report.

Because while the standard model of the past is doing well by about half of American consumers, it’s having a hard time getting a full enough picture when it comes to capturing financial activity of lots of consumers in the present.

“What we’ve seen is that when additional fields of data become visible to a lender, suddenly a much more comprehensive consumer profile is formed. In some instances, this helps them offer consumers new credit opportunities, and in other cases it might illuminate risk,” noted Paul DeSaulniers, Experian’s senior director of Risk Scoring and Trended/Alternative Data and Attributes.

And, Experian’s report notes, both consumers and lenders are getting increasingly interested in “those much more comprehensive profiles” becoming a standard part of the underwriting process.

Alternative Data Streams Good (And Not So Good)

The basic elements of standard consumer credit scoring are well-known: tradeline information like loan balances or credit limits, debt repayment history, and account statuses, as well as information from public records relating to bankruptcies and small claims. Traditional scoring also generally factors in data like income and length of employment.

“Alternative credit data can take the shape of alternative finance data, rental, utility and telecom payments, and various other data sources,” Experian’s DeSaulniers explained.

The data, the report notes, can be derived from any place that a consumer is regularly interacting with a bill, because they all offer the same information to a lender — the customer will pay on a debt as agreed.

The data must, however, fall within the FCRA guidelines — which means alternative credit data sources must be displayable, disputable and correctable.

Which is why, the report notes, social media data as an alternative data stream for consumer underwriting decisions is probably a big no-no for lenders, even though it is a possibility that is often buzzed about.

The FCRA, the report notes, bars lenders from considering race, religion, gender, marital status, age and other personal characteristics as criteria for underwriting a loan.

“A quick scan of any Facebook profile can reveal these things and more. Credit applications do not ask for these specific details for this very reason,” the report notes. “Lenders’ primary goal is to assess a consumer’s stability, ability and willingness to pay. Today, social media can’t address those needs. This is not to say that social media data can’t be used in the future, but financial institutions are still grappling with how it can be predictive of credit behavior over time.”

Moreover, the report notes, there are already many underutilized streams of data that are more attuned to assessing willingness to pay.

“Social media can be gamed. On the flip side, a consumer can’t manipulate their payment history,” the report noted.

Finding More Good (And Shutting Out More Bad)

Of the 247 million Americans over the age of 18 — who are thus eligible for credit — 57 percent are thick credit file consumers — with five or more active tradelines for the FICO score to dig into. They are roughly equivalent to the “No Worries” persona PYMNTS/Unifund wrote in about in the last edition of its Financial Invisibles Report.

On the whole, this group of consumers can fully participate in the financial system, and on average tend to be older, more affluent and more likely to have multiple credit cards and lines of credit — and tend to have credit scores north of 700.

By and large, both Experian and PYMNTS data concludes, they are well served by traditional credit scoring mechanisms and services.

The other 47 percent — or about 106 million people — are not nearly as well served because they aren’t nearly as well seen, according to Experian data. This data, incidentally, is backed by the PYMNTS Unifund findings: as one slides further down the financially invisible scale, one becomes more likely to live paycheck to paycheck and less likely to have access to a credit card.

Experian’s report argues that layering in alternative finance data could allow lenders to identify the consumers they would like to target, as well as suppress those that are higher risk.

“Additional data fields prove to deliver a more complete view of today’s credit consumer,” said DeSaulniers. “For the credit invisible, the data can show lenders should take a chance on them. They may suddenly see a steady payment behavior that indicates they are worthy of expanded credit opportunities.”

It also, the report notes, clues lenders into borrowers that appear stronger on paper than they are because they have a series of short term loans out, or a long history of maximally overdrafting their checking account, that lenders using traditional data streams might not see.

While most alternative borrowers are subprime, the report notes, about 20 percent have prime credit scores. A fuller look at data, said DeSaulniers, gives underwriters a cleaner picture of how prime that score really is.

What’s Next

According to Experian’s report, the demand curve among consumers and lenders is shifting toward more credit scoring models that include a wide swath of data. Nearly 80 percent of lenders surveyed noted that they used a traditional FICO score plus at least one alternative data stream in underwriting decisions; while 16 percent noted they either use, or plan to use, rental payment or utility payment data in their underwriting choices.

Moreover, the report notes, lenders believe alternative data streams could help them both make better decisions risk wise, and also “expand their lending universe.”

Consumers, notably, believe they will do better in an underwriting context. About 60 percent of consumers note they do not think their credit score accurately portrays their credit worthiness, and 47 percent believing they are actually better borrowers than their score indicates.

And, DeSaulniers noted, consumers should not be locked out of credit because the system cannot build a file on them — because it is a lost opportunity for both the lender and the consumer.

“An ‘unscoreable’ individual is not necessarily a high credit risk — rather, they are an unknown credit risk. Many of these individuals pay rent on time and in full each month and could be great candidates for traditional credit. They just don’t have a credit history yet.”

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