Americans carry large amounts of consumer debt.  They are directly affected by credit scores, because the scores affect the interest rates they pay, and the amount of credit they are offered.  One late payment of a bill:  a 60- to 110-point score reduction.  Simply hitting the limit on a credit card:  a 10- to 45-point reduction.  A foreclosure:  an 85 to 160 point reduction.  And the grand finale, a medical bankruptcy: a 130- to 240- point reduction. 

When new coverage standards are implemented under the Patient Protection and Affordable Care Act (PPACA), the resulting “creditable” coverage will place caps on consumer cost sharing.  This can dramatically reduce medical bankruptcies, helping both consumers and their lenders.  Because of this, credit scores can potentially act as a private tax that augments the PPACA penalty for failure to obtain coverage.  Over half of all bankruptcies are now triggered by medical costs.

Imagine a world in which the credit-scoring industry knows exactly who has creditable coverage and (by implication) who does not.  Imagine that two otherwise-identical consumers, one insured and the other not, experience a 50-point differential on their credit scores.  Some interesting things happen.   

Today, a consumer’s insured status has no direct effect on his or her credit score, because the needed data streams are not in place.  Today, health plan sponsors (insurers, self-insured employers, and governments) have no compelling reason to produce uniform data that show which consumers have creditable coverage, except in Massachusetts. 

Credit Scores In The New World Of Health Reform

This will now change.  Health plan sponsors will be required to send a new 1099-like notification to the IRS for a variety of purposes, including enforcement of the new penalty.  For a tiny incremental cost, health plan sponsors could trade identical data files with private credit scorers, in return for various commercially-valuable services.  Existing laws such as FCRA (fair credit reporting) and GINA (genetic anti-discrimination) probably do not prohibit this sort of data exchange.  No medical data are involved. 

Imagine that PPACA’s $695 annual penalty is augmented by $400 in extra interest expense.  Imagine that every credit card issuer shrinks his median credit-limit offer by $2500 if the consumer is uninsured.  These are realistic effects of a 50-point differential in credit scores. 

Suddenly, the anemic PPACA penalties are substantially more robust.  The relative affordability of creditable coverage is enhanced.  The take-up rate for creditable coverage increases.  Best of all, because fewer relatively younger and healthier people find it advantageous to go uncovered, the new exchanges are less susceptible to death spirals, and their risks are easier to manage.  These are highly-desirable outcomes for policymakers.  Death spirals should be anathema to everyone, regardless of political persuasion. 

Should policymakers aid and abet a private piece of infrastructure, knowing that it will strengthen the individual mandate?  Does this raise moral or ethical issues?  These are complex questions, but consider that the infrastructure will probably be built eventually anyway, because lenders will realize that creditable coverage data enhance their algorithms’ predictive power, and thus reduce their lending risks. However, if policymakers resist it, the process will be weaker, messier, and (worst of all) later than it needs to be.