RiskSpan, a leading provider of innovative trading, risk management and data analytics for loans, securities and private credit, has announced the release of its latest Non-QM Prepayment Model incorporating CoreLogic’s loan-level non-QM performance data. This update significantly enhances prepayment forecasting accuracy for non-QM loans and mortgage-backed securities by leveraging a robust, segmented modeling approach.
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RiskSpan’s new non-QM prepayment model introduces a two-component framework that improves the precision of prepayment predictions:
- The first component is a Unified Turnover Model, designed to capture base prepayment trends.
- The second component, a Refinance Model Categorized by Documentation Type, is capable of distinguishing among and modeling behavioral characteristics specific to bank statement, debt service coverage ratio/investor, full documentation, and other documentation types
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The model is built on loan performance data spanning and intelligently incorporates long-term prepayment behavior with conventional loans, addressing the challenge of limited non-QM data history. Key enhancements include:
- Sensitivity to SATO (Spread at Origination) and Burnout Effects, refining prepayment behavior projections.
- DSCR-Specific Adjustments, incorporating prepayment penalty terms and amounts to refine refinance calculations.
By integrating granular loan-level insights from CoreLogic, this release enhances market participants’ ability to accurately assess non-QM prepayment risk, optimize portfolio strategies, and improve secondary market pricing.
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“Our latest model delivers a more precise view of non-QM borrower behavior, equipping market participants with the insights needed to manage risk effectively,” said Divas Sanwal, Senior Managing Director and RiskSpan’s Head of Modeling. “By leveraging CoreLogic’s expansive dataset and an expansive GSE dataset, we’re enabling investors to better anticipate prepayment trends and make more informed decisions.”
The new model is now available for integration into RiskSpan’s Platform.
Source: Businesswire
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