Alternative Credit Scoring Models: Pros and Cons

by
Adam Rust

More people know their credit score than ever before. More people check their credit score regularly than ever before. More people do so because knowing your credit score is essential. It’s increasingly imperative.

Your credit score can affect how you live, not just how you borrow. In some employment sectors, it is more and more the norm that employers use your credit score when they make hiring decisions.

Your credit score used to be an amalgamation of five factors. Some credit scores continue to use those same constructs. The most predictive, according to industry experts, was data from credit card accounts. The benefits were numerous: for people with the right data inputs, underwriting algorithms were highly predictive, and the needed data was accessible at a meager cost.

A fundamental shortcoming of a system that uses existing credit records to assess qualifications for new extensions of credit is that it mostly keeps the door closed to new entrants. Not only did it harm some consumers, but it also curbed the volume of business that a lender could find.

However, in the future – which is here in some cases – your credit score will be built from hundreds of data points. That starts with new models that can pull payment data into the trove of data that goes into making your score. Some use income and asset data, too.

Your new data inform your credit score if and when a credit bureau gets access to your bank account. If you have allowed a company to import your transaction history, then it can be utilized for scoring. There is a fundamental shift occurring right now in terms of how a consumer’s profile is determined.

Picture of card
Picture of card

A company like UltraFICO – a product that only recently came into being - can incorporate the promise of ECOA. It makes the shoebox a plausible alternative. In the past, while bureaus were required to accept additional evidence from consumers, they often did nothing with that data because it had no place in their algorithms. A company like UltraFICO will utilize the data. Moreover, their system allows it to go to scale and with relatively little effort on the part of consumers. The proposition to consumers is straightforward: If you feel your score fails to assess your creditworthiness correctly, share your information with UltraFICO, and you may qualify for new credit opportunities.

“We ask for permission from consumers. Let us look at your banking behavior,” said Will Lansing, CEO of FICO at last year’s Money 20/20 conference. “Let us look at your average daily balance, let us look at how long you have had your DDA (a checking account) open, let us look if you have overdrawn and how frequently. With that additional behavioral information, we have seen that 70 percent of people wind up with a better score if they have good behavior against those dimensions.”  

Sharing is easy – it’s just a matter of granting a company access to your sign-on information.

“We all crave simplicity,” said Regis Hadiaris of Quicken Loans and Rocket Mortgage.

Of course, simplicity is only one aspect that matters. Privacy and control could also change.

Some new data points that can go into an alternative scoring model:

• Employment history

• Checking account data

• Assets and income

• Shopping history

• Transfers to savings and retirement accounts.

• Rent and utility payments

• Address history and general tenure.

• Various behavioral traits

There are others.

It takes software to make it happen. Companies in this space create application programming interface “API”) protocols that smooth the rails for the exchange of data from a consumer account into the bureau’s algorithms.

A company like Finicity creates the tools that are necessary to establish the linkages between companies and consumers. Plaid and Yodlee are other companies operating in this space.

To make that work, consumers have to consent to share their information. There is some latitude, as the new service bureaus are willing to accept more or less access, but the potential for benefit increases with each new decision to grant more access.

Advantages

1. More consumers will qualify for credit.

2. With APIs, sharing occurs at higher velocities. No longer is it necessary to mail paper copies of account statements. A consumer can share access to an account with a few taps of a smartphone.

3. Consumers will know more about the data they are giving to third parties.

4. With more understanding of consumer behavior, companies may be able to do a better job of designing appropriate products.

5. More data equals more consumers who can qualify for credit equals more demand equals more competition equals better pricing.

6. More people will qualify for credit. In other cases, job applicants who might otherwise have been turned down for work will now find employment.

Disadvantages

1. Debt collectors may be able to sharpen their tools to collect money. For example, if an agency can see when payments arrive on a consumer’s bank account, then it may attempt to debit the consumer’s account electronically as soon as possible.

2. Loss of privacy.

3. We are putting too much faith in the viability of new tech companies. Many Fintechs have relatively short lifespans. What happens when a company goes out of business? Will their knowledge of consumer behavior have value to other institutions? If so, will we have protections in place to make sure that consumers can prevent unauthorized sharing? If you close your account, does your payment history remain active?

4. Some aggregators will sell data to third parties.

The industry will say that there are only net positives here. The UltraFICO claim that most consumers improved their qualifications for credit also means that others did not. The implicit deal – give up your privacy to gain access to credit – didn’t pan out.

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