In the post, Predicting the Timing of HELOC Payment Shock, we outlined that millions of home equity lines of credit will be hitting the end of draw (EOD) period over the next few years, which may cause some borrowers to default on their HELOCs due to the payment shock of full amortization (interest plus principal payments). Lenders with and without HELOC portfolios have billions of dollars exposed to borrowers who may be unprepared for this payment shock.
Motivated to discern the timing of HELOC reset risk, TU Financial Services analysts conducted a study. In today’s post we will examine the metrics around the second of three dimensions of risk at the consumer level, the capacity to absorb payment shock.
Part 3 of 5
After constructing an allocation model that correctly predicts the EOD point 81% of the time, and developing metrics to assess credit risk of the consumer, our Financial Services analysts turned their focus on the ability of the consumer to absorb a payment shock. Perhaps the biggest challenge for lenders is the lack of metrics to help identify which consumers present an elevated risk from an impending EOD payment shock. Many borrowers have the means to absorb the incremental debt service; the trick is to determine who belongs to which group, so appropriate strategies can be set at the customer level.
Although some might consider income to be a good metric for measuring HELOC risk along this dimension, accurate income data is hard to obtain and most sources of the data lack sufficient population coverage. Even when income data is available and current, there is still the question of the consumer’s debt service and other financial obligations, and how good the consumer is at meeting those obligations given income and lifestyle.
To fill these blanks, we used a metric developed in previous analyses called Aggregate Excess Payment (AEP), the difference between actual payments made on credit cards in any given period and the minimum payments due on those cards in the same period. The theory behind using AEP is the measure of disposable income that could be reallocated to cover a payment shock, with the logic that consumers with large AEPs have already paid for regular expenses and still have disposable income to direct toward paying off card balances. Moreover, it is a conservative metric in that it does not account for funds deposited in any savings or investment accounts – so it acts as a lower-bound measure of a consumer’s liquidity, which makes it a strong candidate for effective measurement along this dimension of HELOC risk.
Table 2 shows that AEP is an excellent estimator of HELOC risk. While it is not as strong as credit scores in this regard, we find that AEP provides remarkable separating power, with a factor of 45x between delinquency in the highest AEP tier and that in the lowest tier. The determination of what constitutes elevated risk is a matter of personal preference for the lender. For our study, we chose an AEP of $500 or higher as the delineation of lower risk. Given the size of most HELOC balances (58% are over $100,000) we felt that having less than $500 in AEP represented limited discretionary income, as well as elevated exposure to HELOC EOD payment-shock risk. Given this cutoff, we find that about 43% of HELOCs present an elevated risk due to a lack of ability to absorb payment shocks, or to a lack of data available to calculate that ability – a material improvement over having to worry about all HELOCs yet to reach EOD.
Stay tuned for part 4 of the HELOC Reset Risk series, addressing the third dimension of risk in our study – the presence of a viable strategy for exiting the debt obligation.
For more on this topic and the study, download the full article Understanding HELOCS: Facts versus Fear, recently featured in the RMA Journal May 2015 edition.
Next steps for mitigating HELOC EOD risk:
- Initiate a portfolio review to understand extent of exposure, how many HELOCS are going to hit end of draw, and individual consumer ability to absorb shock
- Identify and analyze lender risk, pricing, credit limits and metrics around loan to value
- Determine how you move forward with prospective customers
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- For our most recent study on the consumer payment hierarchy, see “Take Heed of Consumers’ Changing Payment Hierarchy” in the December 2013 / January 2014 issue of The RMA Journal.
- For an in-depth discussion of AEP and the related metric, total payment ratio, see “The Almighty Payment: Why It’s Important to Study Debt Service Behaviors” in the March 2014 issue of The RMA Journal.
- Data Source: TransUnion consumer credit database.