We test the reasonableness of model data inputs, assumptions, and calculations by assessing how coefficients were selected, confirming that their selection is justified using developmental evidence, and reviewing all model documentation.
Our validators benchmark model outputs across a wide range of shock scenarios using RiskSpan’s suite of proprietary credit, prepayment, and valuation models. Whether coded in SAS, R, Excel, or Python, we ensure model consistency with critical documentation and best practices.
We tailor the statistical tests for back-testing to the specifics of each model under review and work with your team to develop thresholds and tolerance levels appropriate for each model, their respective outputs, and each use case. Recommendations are adapted to your needs when recalibration is required.
Get clear and comprehensive model validation reports that satisfy internal stakeholders and meet regulator requirements.
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