Independent Systemic Risk Visibility
Next-generation risk models that give regulators independent analytical power over the raw data they already collect — replacing reliance on static reporting from supervised entities.
Currently, regulators often rely on static reporting from supervised entities themselves. This creates an information asymmetry where the institutions being supervised control the analytical narrative around their own risk exposure.
The Superintendency needs the capability to independently validate, challenge, and monitor the risk models and portfolio health of the institutions under its oversight.
Solution Overview
Caltec allows the Superintendency to run independent, next-generation risk models on the raw data you already collect. Rather than depending on self-reported metrics from private banks, our supervisory technology processes the underlying data directly — providing an unfiltered view of systemic risk.
Validation of Internal Models
We provide the tools to audit the Internal Ratings-Based (IRB) models used by private banks, ensuring capital requirements accurately reflect actual risk.
Independent audit capability over bank-submitted IRB models
Verification that reported capital requirements match actual portfolio risk
Alignment with Basel 3.1 IRB framework requirements (basic and advanced approaches)
Early Warning Capabilities
Our engine detects deterioration in specific loan portfolios before traditional indicators signal a default. The output is a Value at Risk (VAR) measurement — calculated using the publicly established VAR equation, enhanced with Caltec's proprietary models to ensure measurement precision.
How VAR Works for Supervisory Early Warning
The Value at Risk quantifies the maximum expected loss for a credit portfolio within a defined confidence interval over a given time horizon. Caltec applies proprietary predictive models to the standard VAR framework, delivering a more granular and forward-looking risk assessment than conventional approaches.
VAR-based quantification of expected loss across supervised portfolios
Proactive identification of portfolio stress before defaults cascade into systemic events
Granular visibility into specific loan segments — including consumer credit, commercial loans, and other portfolio categories
Proprietary model enhancements over the standard VAR methodology for greater measurement precision
Move from reactive oversight based on institution-submitted reports to proactive, independent systemic risk monitoring — powered by VAR analysis and proprietary models that deliver precision beyond standard market tools.