Escaping battered credit: a proposal for repairing credit reports damaged by domestic violence.

• Author: Littwin, Angela
• Position: III. Blocking Coerced Debt through Conclusion, with footnotes, p. 408-429

3. BLOCKING COERCED DEBT

This Part addresses the legal effects of the coerced debt certification proposed in Part II. Because my proposal alters only the reporting of coerced debt, not the consumer's liability for it, I have separated my reforms into two sub-proposals: one for debt that is already no longer legally binding and one for debt that is still outstanding. Creditors have different reasons for valuing information about these two types of debt. Data on past debt are useful only for their predictive power, while data about outstanding debt also provide creditors with information about a consumer's current and future available funds. The "predictive interest" can be preserved when blocking coerced debt from a credit report, but the "current liabilities" interest cannot.

There is a crucial difference between the FCRA's identity-theft blocking mechanism and my proposal: the treatment of liability. The FCRA is supplemented by other federal statutes that alter legal responsibility for fraudulent debt. While a consumer is seeking to block a fraudulent debt under the FCRA, she may also be seeking to discharge her liability for it under another federal statute. The Truth in Lending Act (TILA) and the Electronic Fund Transfer Act (EFTA) limit the amount for which consumers can be held liable for fraudulent use of their credit and debit cards. (278) Policymakers appear to expect consumers to simultaneously seek protection under the FCRA and these unauthorized use provisions. For example, the FTC provides a single identity theft affidavit that solicits information consumers need to meet the requirements for both statutory regimes. (279)

This overlap means that a debt blocked under the FCRA is also likely to be invalidated under the TILA or the EFTA, which is important for future potential creditors of consumers. Otherwise, a consumer's legal liability could exceed the liabilities listed on her credit report, which would compromise the current liabilities interest of potential creditors. Even under the current system, there is some risk of this problem. A consumer might not pursue or attain the unauthorized use remedies in addition to the FCRA block. But the risk is significantly greater when there is no liability relief provision available. Thus, I propose a complete coerced debt block on past liabilities but a narrower block for debts a consumer still owes.

1. The Predictive Power of Past Debt

   The first effect of submitting a certification of coerced debt to the CRAs would be to block from the consumer's credit report all coerced debts she no longer owed. These debts present a relatively easy case. Blocking them does not mislead creditors about the extent of a consumer's current indebtedness, and the coerced nature of the debts means that their initial accumulation does not accurately reflect a consumer's risk profile.

   Records of past obligations are important for their predictive power. The idea is that consumers maintain consistent approaches to debt payment such that payment history will be relevant to future payment behavior. (280) These data enable creditors to answer questions about consumer behavioral tendencies--such as promptness and willingness to make payments under a variety of financial circumstances--that would be otherwise difficult to determine. But when a debt is incurred involuntarily, a consumer's payment history is less likely to be representative. This is especially true when the consumer was not even aware of the debt's existence.

   1. Treatment of Past Debt Under My Proposal

      In many cases, by the time a victim learns of a coerced debt, it may have been paid off already or rendered uncollectable for other reasons, such as bankruptcy or the expiration of the statute of limitations. But if such a debt were ever delinquent, it would still have a significant negative impact on the victim's credit rating. Although the CRAs do not release the precise details of their credit scoring algorithms, (281) FICO, which claims to promulgare the most commonly used formula, (282) publishes a list of the factors it considers. Under the FICO model, payment history is the most important variable, counting for 35% of a score. (283) Payment history is even weighted more heavily than a consumer's current amount owed, which comprises 30% of the score. (284) So blocking past coerced debt could significantly improve victims' credit scores.

      Excluding coerced debt that is no longer outstanding should not have a major negative effect on future creditors, because the purpose of including past debt on a credit report is predictive. (285) The usefulness of one's payment history is predicated on the belief that consumers' track records are predictive of their future payment behavior. (286) But in the case of a victim of coerced debt who has divorced her abuser, this inference may no longer be justified. A court of law will have determined that the victim did not voluntarily create the debt, so its existence should have less predictive value. The payment history on coerced debts may very well reflect the abuser's willingness and ability to make prompt payments, not the victim's.

      The exact relationship between past coerced debt and victims' future payment tendencies is an empirical question that will require further research, (287) but it is still useful to think through some of the plausible scenarios now. In situations in which the victim was not aware of the coerced debt, the payment history (or lack thereof) will be entirely attributable to the abuser. In circumstances in which the victim knew of the debt but incurred it under duress, her ability to make payments could easily be compromised anal thus not reflect her payment tendencies under noncoercive conditions. Even when the victim is able to make payments without interference, one can imagine that she might prioritize "her" debts over those generated by the abuser.

      The above points examine the predictive potential of past coerced debt on the payment of future voluntary debt, but my proposal also implicates questions about the effect of past coerced debt on the likelihood of future coerced debt, generated either by the current abuser or a future abusive partner. In the case of the current abuser, the primary argument would be that victims of domestic violence may return to the abuser multiple times before leaving for good. (288) This would give the abuser additional opportunities to incur coerced debt in the victim's name. However, in order to access the coerced debt-blocking remedy, a victim must be in the process of divorcing her abuser, a step that is indicative of a permanent break in the relationship. There are never any guarantees that a given relationship-abusive or not--is fully terminated, but divorce is a generally accepted end point. In addition, a divorce may represent a victim's best chance of establishing herself as an independent financial unit. (289) Though there may be plausible concerns that even a former abusive partner could generate coerced debt, for example, by applying pressure via stalking or by using personal identification information acquired during marriage, the policy considerations discussed below still militate in favor of blocking coerced debt.

      With respect to concerns about potential future abusive partners, the vast majority of DV survivors are not repeat victims. The most recent, major national survey of domestic violence found that, among female respondents who had experienced domestic violente, 70.8% had had only one abusive partner over the course of their lifetimes. (290) Thus, fewer than 30% of DV survivors are victimized by future partners. In comparison, the same study found that 35.6% of females in the general U.S. population had experienced domestic violence at some point during their lives. (291) Therefore, past domestic violence does not appear to be correlated with future domestic violence by new partners, and because my definition of coerced debt depends on a finding of domestic violence, past victims of coerced debt are equally unlikely to be future victims of coerced debt at the hands of a new partner.

      Finally, even if there are some situations in which past coerced debt predicts future coerced debt, that does not necessarily mean that creditors should have access to this information. Federal law already prohibits credit discrimination on the basis of several classifications that would probably improve the predictive power of credit-scoring formulas, and DV status is a particularly important classification to protect. The ECOA prohibits many forms of credit discrimination. It was originally passed in 1974 to address an issue related to the topic of this Article, lending discrimination on the basis of gender and marital status. (292) The statute and its regulations have since been broadened to cover additional classifications such as race, religion, and age. (293)

      Many of these characteristics are statistically significant in predicting creditworthiness. The regulations promulgated by the Federal Reserve state that even statistically sound formulas cannot be used if they negatively impact certain groups. For example, creditors may not include age as a variable if a credit-scoring formula has a negative impact on elderly consumers, but may use it if senior citizens are affected positively. (294) The regulations also specifically prohibit using aggregate statistics about child bearing in evaluating creditworthiness. (295) The modern reader may be startled to learn that questions regarding birth control were common on pre-ECOA loan applications, (296) but Dom a statistical perspective, this practice may have been surprisingly sound. Empirical bankruptcy research since that time has suggested that there may be a correlation between supporting children and financial distress. (297)

      Even the very classification that motivated the original passage of the ECOA is not exempt. A contemporary study analyzed data Dom...