PT  - JOURNAL ARTICLE
AU  - Yini Yang
AU  - Joy Zhang
AU  - Jiawei “David” Zhang
TI  - Auto ABS Loan-Level Data: Improved Risk Analysis
AID  - 10.3905/jsf.2022.1.130
DP  - 2022 Jan 31
TA  - The Journal of Structured Finance
PG  - 31--42
VI  - 27
IP  - 4
4099  - https://pm-research.com/content/27/4/31.short
4100  - https://pm-research.com/content/27/4/31.full
AB  - In 2014, the US Securities and Exchange Commission’s Regulation AB mandated loan-level data disclosure for public auto loan asset-backed securities (ABS). As a result, the loan level data from 2017 to 2021 display a rich set of loan-level variables that shed light on collateral performance patterns and improve risk analysis, especially for credit risk. Statistical predictive models that incorporate these loan-level drivers substantially improve the accuracy and granularity of default forecasts for auto ABS loans, and can provide benefits for investors and risk managers who use them.