The Next Crisis will be in Consumer Credit Scores — and Alternative Data Will Be Essential

Chris Brummer is a Georgetown law professor and host of the Fintech Beat podcast, produced by CQ Roll Call. This Article was published in April 2020, prior to the $500 billion supplemental support package passed by Congress to bolster the economy.

One difficulty sure to come from the COVID-19 pandemic — after the foreclosures, bankruptcies and deaths — is a crisis in credit scores. With experts expecting unemployment rates to reach the mid teens, and institutions like the St. Louis Fed seeing the possibility of 32 percent unemployment, it’s not hard to imagine peoples’ credit standings cratering in a matter of months. Mortgages, car and student loans, as well as other consumer debts, will be due, and go unpaid if the country’s economic slide continues; and eventually, data of failed payments will make it into the credit terms of lenders.

The impact will be wide and unprecedented. Experts estimate that about 45 million U.S. consumers lack the credit history required to produce trustworthy credit scores, in addition to the millions who cannot access credit because of their low scores. The crisis will make things even worse, and in the absence of significant policy or market interventions, battered scores will weigh on people’s credit histories for years, even when the economy recovers.

It’s important to add that up to this point, policy responses have only indirectly, and partially, spoken to credit scores. Instead, the focus of federal action has targeted the immediate economic dislocations of the pandemic. For example, under the CARES Act — the congressional rescue package enacted last month — a servicer of federally backed mortgage loans may not initiate any judicial or nonjudicial foreclosure process, move for a foreclosure judgment, order a sale, or execute a foreclosure-related eviction or foreclosure sale.

Similarly, landlords are prohibited from filing to recover possession of properties from a tenant for nonpayment of rent or other fees or charges and may not charge fees, penalties or other charges to the tenant related to nonpayment of rent. Landlords also may not provide any notices to vacate — including for reasons unrelated to nonpayment — during a 120-day period.

Credit score impact

But even with these protections, credit scores for the unemployed could change dramatically.

Take for example, FICO scores. The Fair Isaac Corporation creates software used by the three major credit bureaus, Equifax, Experian and TransUnion. That software reportedly groups data into several categories of varying weights including payment history (35 percent), amounts owed (30 percent), length of credit history (15 percent), new credit (10 percent) and credit mix (10 percent). The credit bureaus then take borrower information reported by lenders, and plug the data into the FICO formula.

Given the configuration of data used in FICO scores, current reforms would offer limited relief for consumers in terms of their credit scores. Fortunately, mortgagees who actively seek forbearance or relief with their lender will not be negatively impacted. From what I understand, they will be marked as “paid as agreed” on any credit report which is the same as paying on time. But even with forbearance, the amount owed by a debtor during the forbearance period will only accumulate — and in the process tarnish one of the most important categories determining credit scores.

Alternative data will need an upgrade, too

Such limitations suggest one reason why the fintech sector could prove especially important in America’s post-COVID-19 economy. Dominant scoring methodologies, combined with limited federal relief, will provide only indirect assistance for debt-ridden, unemployed workers.

Alternative data, in particular, will be needed to design new kinds of credit modeling and scoring for individuals specifically impacted by coronavirus. Instead of an over-reliance on FICO, lenders will need to consider, where appropriate, data tools that investigate other factors like bank account statements, rental payments, asset ownership, and other customer-permissioned data. In doing so, they can harvest a wider range of information from which to determine a borrower’s eligibility. This might be especially helpful in an age where traditional metrics might be unnecessarily harsh for workers caught in the crosshairs of the pandemic, overestimating their credit risk.

My hunch, however, is that alternative data, too, will require more creativity than ever. It’s extremely likely that information gleaned from sources’ bank account and investment records will reflect diminished prospects and fortunes of borrowers, and thus provide only limited benefits for borrowers. For example, Bloomberg recently reported that due to the swelling ranks of the unemployed, just 69 percent of renters paid their rent by April 5, compared with 81 percent who paid by March 5. Consequently, payment records may not only disclose information about borrower habits that is overdetermined by the pandemic, but it might well also inadvertently reveal information — like missed rental payments — that FICO records under the CARES Act may not.

Instead, new metrics will still be needed. Other kinds of data, including behavioral and social media data, could come increasingly to the fore to develop new risk models. New scoring infrastructures will also be necessary, including more sophisticated digital identities, to allow individuals to more quickly establish creditworthiness by generating new data inputs needed for more and better scoring.

None of these changes are without risks. Some scholars have argued that alternative data, if poorly collected and interpreted, could introduce racial and gender bias instead of alleviating it. Similarly, some consumer advocates and scholars have identified instances where “bad” alternative data mistakenly enhanced income data, as well as exacerbated the challenge of capital access for historically marginalized groups.

In times of economic peace, such concerns are especially noteworthy. But in times like these, and those to come, the downside of no alternatives to traditional credit methodologies and scoring bureaus seems more dire than ever. Overall, alternative data has proven to be a lifeline for many women, minorities and small businesses, and has opened many more doors than it has closed. And if less punitive, but more accurate formulas prove compelling, Americans may quickly conclude that more innovation in credit scoring, rather than less, is needed to ensure that the economic opportunities arising from overcoming the pandemic are fairly shared.

Want to learn more? Listen to the podcast Fintech Beat, and a recent episode on Ethical Algorithms.

Chris Brummer is a Georgetown law professor, author, and lecturer.

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