DefaultRiskIndex.com Shows Risk in Student Lending Hitting All-time Low as Bankcard Lending Risk Category Continues to Rise
VantageScore Solutions, LLC, developer of the VantageScore® credit scoring models, today announced an update to its Default Risk Index™ (DRI), an online tool that identifies lender risk appetite in major loan categories, using new loan origination data from the third quarter of 2018. After five years of data collection, the most recent update reveals risk in student lending trending downward, this quarter marking its lowest DRI since the inception of the DRI in 2013. Relative to other loan categories, the overall risk in student lending remains high though the trend downwards signals improvement.
The DRI compares the volume and weighted-average risk profile of quarterly originations within each major loan category. The following table measures changes in index values for these loan categories between the third quarter of 2018, the second quarter of 2018, and the third quarter of 2017.
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
Default Risk Index Insights
Originations: Mortgage originations slowed 7% relative to last year, while auto and credit card originations showed little change. Student loan originations more than doubled in the third quarter, consistent with seasonal expectations.
DRI: Despite the surge in volumes, student loan originations looked less risky both relative to the previous quarter (-18%) and to the third quarter in the prior year (-7%). This is the lowest student loan DRI observed since the beginning of the series.
Snapshot: The Default Risk Index began five years ago with a starting value of 100 in each lending category. In the third quarter of 2018, the student category reached its lowest value ever (“lower” indicating less risk) while the credit card category showed its second highest yet (the highest was in the second quarter, same year). The auto category is closest to where it started, at a DRI of 94, while the mortgage DRI of 88 reflects relative tightening (the latest value is in the bottom, or lowest risk, quartile of DRI values observed so far).
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 provided 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.
Each risk profile for the DRI 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).
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 is 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 securitized pools of consumer 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 leading a well-intentioned analyst to the wrong conclusions.