Modeling Default And Recovery Analysis

Builds default probability and recovery rate models incorporating structural credit analysis, industry default statistics, and loss-given-default (LGD) estimation for leveraged lending, direct lending, and broad credit market portfolios.

When To Use

• Underwriting a new leveraged loan or direct lending facility and need to size expected credit losses
• Constructing or updating a portfolio-level reserve model (CECL, IFRS 9, or internal economic capital)
• Stress-testing a credit book under adverse macro scenarios (recession, sector dislocation)
• Evaluating recovery assumptions for a restructuring, workout, or distressed debt investment
• Pricing credit risk on a single-name or portfolio basis for CLO warehousing or syndication

Inputs To Gather

• Obligor financials: Latest and trailing 3-year income statement, balance sheet, cash flow statement; management projections if available
• Capital structure detail: Secured/unsecured tranches, lien priority, intercreditor terms, guarantor coverage, collateral descriptions and appraisals
• Industry default data: Moody's, S&P, or Fitch trailing default and recovery rate studies for the relevant sector and rating cohort [VERIFY available vintage]
• Macro scenario parameters: GDP growth, unemployment, interest rate path, sector-specific stress drivers (e.g., commodity prices for E&P)
• Collateral valuations: Appraisals, liquidation analyses, or orderly-sale estimates for tangible and intangible assets
• Loan documentation: Credit agreement covenants, waterfall mechanics, cure rights, and any subordination or turnover provisions