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Nature-risk PD/LGD/EAD bridge ​

bridge_pd_lgd_ead · v0.1.0-prior-dominated

Translates normalised nature-risk drivers into indicative credit-risk parameter uplifts using disclosed prior-dominated coefficients.

Inputs ​

  • baseline water stress, annualised tree-cover loss, biodiversity screening and transition-risk indicators;
  • operator-quality context, recovery horizon and tailings consequence class;
  • facility EAD, tenor, baseline credit spread and sustainability-linked KPI structure;
  • versioned coefficient set with confidence bounds.

Calculation ​

The method normalises ecological drivers against registered reference levels. Water, land, biodiversity, transition, operator and water–land interaction terms contribute to a non-negative PD uplift in basis points. Recovery horizon and tailings class contribute to LGD uplift. KPI step-down terms can adjust effective EAD. Expected loss is calculated from adjusted EAD, stressed PD and stressed LGD.

Outputs ​

  • PD uplift in basis points;
  • LGD uplift and adjusted EAD;
  • expected loss and nature-related expected-loss uplift;
  • component contributions, input snapshot, suggested KPIs and signed manifest.

Limitations ​

This version is explicitly prior dominated. It is an indicative translation layer for scenario and pricing discussion, not an empirically validated internal-ratings model or regulatory capital model. A lender must apply its own model governance, calibration, overrides and approval process. Missing inputs may use disclosed neutral defaults.

Versioned methodology documentation for Miombo Nature Risk Intelligence.