📘 Qualitative Overlay Guide for PD Modeling

1. What is a Qualitative Overlay?

A qualitative overlay (sometimes called a model adjustment, post-model adjustment, or post-management adjustment) is when you add judgment on top of a purely quantitative model’s output.

2. When to Apply an Overlay

You don’t apply overlays casually; they’re used in specific situations where the model is known to have blind spots. Common cases:

  1. Data Gaps or Limitations
    • Example: A new loan product has no historical defaults, so the PD model may underestimate risk.
    • Overlay: Add a conservative buffer until data matures.
  2. Macroeconomic or Sector Shocks
    • Example: Oil & gas companies in 2020 suddenly faced huge default risk not reflected in prior data.
    • Overlay: Increase PDs for energy sector loans.
  3. Forward-Looking Risk Factors
    • Example: A corporate borrower’s management is under investigation, which is not in historical financial ratios.
    • Overlay: Increase PD to reflect governance risk.
  4. Model Weaknesses Identified
    • Example: The logistic regression model underpredicts defaults for very small firms.
    • Overlay: Apply a higher PD floor for small-firm exposures.

3. How to Apply an Overlay

There are structured ways to apply overlays so they’re defensible, documented, and consistent:

  1. Define the Trigger / Rationale
    • Document why the overlay is needed (e.g., “COVID-19 impact on hospitality sector”).
  2. Determine the Method

    Several approaches can be used:

    • Additive Adjustment: +X% to predicted PD.
    • Multiplicative Adjustment: Scale PD by a factor (e.g., ×1.5).
    • Floor / Cap: Set minimum PD (e.g., no corporate loan can have PD < 0.5%).
    • Segment-Specific Adjustment: Apply overlays to certain industries, geographies, or product types.
  3. Calibrate the Size of the Overlay
    • Use external data, expert panels, stress scenarios, or regulator guidance.
    • Example: If sector default rates rose from 2% → 4%, apply a 2% absolute overlay.
  4. Governance and Review
    • Every overlay should be approved, documented, and backtested.
    • Regulators expect overlays to be temporary, not permanent substitutes for poor models.

4. Example: PD Overlay in a Loan Portfolio

Key Takeaway:

A qualitative overlay is a controlled, documented adjustment to a quantitative model’s outputs, used when the model cannot fully capture new risks, data limitations, or forward-looking conditions. Overlays ensure the model remains fit-for-purpose without replacing the model itself.

Qualitative Overlay Checklist – Example

1. Overlay Identification

2. Rationale for Overlay

3. Overlay Methodology

4. Overlay Size & Calibration

5. Governance

6. Review & Monitoring

Result:

The overlay ensured the bank’s PD estimates reflected real-world heightened risk, avoided underestimation of capital needs, and stayed defensible to regulators by being documented, calibrated, and temporary.

Perfect — let’s extend the example into a portfolio-level overlay framework, where multiple overlays can be applied in a structured, transparent way. Think of it as a layered adjustment process on top of your quantitative PD model.

Portfolio-Level Overlay Framework

1. Organizing Overlays

Banks usually categorize overlays into types, then apply them at the portfolio, segment, or borrower level.

Common categories:

  1. Macroeconomic overlays (forward-looking shocks)
  2. Sector / Industry overlays (sector-specific risks)
  3. Borrower-level overlays (idiosyncratic risks)
  4. Data / Model limitation overlays (new products, thin data, structural weaknesses)

2. Example: Portfolio-Level PD Overlays

A. Macroeconomic Overlay

B. Sector Overlay (Hospitality Sector)

C. Borrower-Level Overlay

D. New Product Overlay

3. Governance Structure

4. Example Portfolio Impact Table

Overlay Type Segment Affected Method Avg PD Before Avg PD After Impact on Portfolio EL*
Macroeconomic Entire portfolio +0.5% additive 2.1% 2.6% +\$15M
Sector (Hospitality) Hotels & Restaurants ×3 multiplier 1.5% 4.5% +\$22M
Borrower-Level Borrower XYZ Corp. Direct override 1.2% 5.0% +\$3M
New Product SME lending program 2% PD floor 0.8% 2.0% +\$7M

*EL = Expected Loss

Key Takeaway:

A portfolio-level overlay framework: