The third quarter update to the Default Risk Index (DRI) demonstrates a sustained trend across asset classes in which origination volumes generally increased while the risk profile of those originations became more conservative. In the third quarter, for example, student lenders originated the highest quarterly volume of loans since the DRI initiated, while the average default risk of those new originations was only 72 percent of the risk taken during the same quarter in 2013.
The VantageScore DRI tracks the amount of default risk assumed by lenders in four U.S. consumer-loan categories: mortgage, bankcard, auto loans, and student loans. The latest update is located in interactive infographics at DefaultRiskIndex.com and in a spreadsheet containing the full data series, which is available for download at the site.
Changes to specific index values are summarized below:
| CATEGORY | TOTAL ORIGINATIONS | TOTAL ORIGINATIONS VS. LAST QUARTER |
TOTAL ORIGINATIONS VS. SAME QUARTER LAST YEAR |
PROBABILITY OF DEFAULT (WEIGHTED) |
DEFAULT RISK INDEX | DRI VS. LAST QUARTER |
DRI VS. SAME QUARTER LAST YEAR |
| Auto | 160,979,112,224 | 1.2% | – 1.5% | 3.87 | 87.8 | – 3.7% | -3.6% |
| Bankcard | 88,117,522,011 | 3.2% | – 9.20% | 2.74 | 97.6 | – 3.5% | -2.9% |
| Mortgage | 424,323,804,842 | 3.4% | – 6% | 1.08 | 93.5 | 2.3% | 1.3% |
| Student | 49,334,949,179 | 108.4% | 2% | 14.92 | 72.1 | – 19% | -2.1% |
INDEX
Since Q3 2013, the risk profile of each asset class has generally tightened. Student lending was the tightest category in 2017 with a record-low DRI of 72.1.*
SNAPSHOT
The risk profile of new auto loans and bankcards tightened very slightly as compared to last quarter. Student loans tightened from 90 to 72.1 while volumes more than doubled, continuing a seasonal theme that plays out each year in the third quarter. Only mortgage loans showed both a slight increase in risk and a slight increase in originations.
ORIGINATIONS
Student loan origination volumes increased dramatically in the third quarter, more than doubling from the previous quarter to $49 million. Although an increase in student lending is typical in the third quarter of every year, this particular third quarter represented the highest quarterly volume since the DRI initiated. All other major loan categories (auto, bankcard, mortgage), saw a slight increase in loan originations from the last quarter.
*Each risk profile is indexed to the beginning of the series, where the third quarter of 2013 equals 100. DRI profiles that are close to 100 show an equivalent risk activity to the 2013 benchmark, whereas DRI profiles that fall further from 100 distinguish risk activity that is either higher or lower than the benchmark (depending on the results).
About the Default Risk Index
The VantageScore Default Risk Index (DRI) and its website, DefaultRiskIndex.com, permit users to monitor the shifting quarterly risk profiles of loan originations in the mortgage, credit card, auto, and student loan categories. The DRI is derived using credit file data from TransUnion and VantageScore odds charts—tables furnished to VantageScore users that match values on the 300-850 VantageScore scale range with their corresponding probability of default (PD) values.
The Default Risk Index is a measure of relative changes in risk level, benchmarked against the third quarter of 2013, the first period for which data were compiled. Interactive tools at DefaultRiskIndex.com allow users to view trends for each loan category and freely download the data behind the charts.
The VantageScore Default Risk Index is provided as a free resource to institutional and individual investors, professionals in the securitization field, academics, and all others interested in systemic lending risk. It will be updated quarterly, with data reflecting loans issued in the preceding quarter.
VantageScore Solutions and TransUnion developed the DRI to highlight limitations in the traditional ways credit scores are used to evaluate risk for categories or pools of loans. Today’s common practices—using “weighted average” or “distribution by score band” to summarize risk—are mathematically flawed. Reliance on those metrics can result in a miscalculation regarding the true credit quality of a loan pool as well as obscuring meaningful trends and lead a well-intentioned analyst to the wrong conclusions
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