# Credit Rating Model Forecast credit metrics and estimate debt ratings without waiting for agency decisions. Map your leverage, coverage, and liquidity ratios to published agency scales and stress-test your rating under different EBITDA and financing scenarios. - Canonical: https://finamodel.com/templates/credit-rating-model - Excel download: https://finamodel.com/templates/credit-rating.xlsx - Category: Banking - Model type: Sector planning - Difficulty: Advanced - Audiences: Credit & risk, Investors & analysts, Treasurers, Rating analysts, Lenders, Credit officers - Tags: Credit analysis, Rating, Leverage, Coverage ## Overview This credit rating model calculates leverage and coverage ratios from a three-statement projection and maps them to implied credit ratings (BBB, BB, B, etc.) using agency-published rating scales. It projects leverage (total debt / EBITDA), interest coverage (EBITDA / interest), DSCR (debt service coverage ratio), loan-to-value (LTV), and other metrics; then applies lookup tables benchmarking those metrics against Moody's or S&P rating thresholds to estimate what rating a debt issuance would likely receive. It includes rating outlook and rating triggers, flagging when performance deteriorates sufficiently to trigger a downgrade watch or negative outlook. The model includes an assumptions section with leverage and coverage thresholds for each rating category; a calculations section projecting the subject company's financial metrics across a 5-year period; a rating determination section that looks up the implied rating in each year based on leverage, coverage, and qualitative factors; and a sensitiv table showing how ratings change if key assumptions (EBITDA growth, leverage target, interest rate) shift. Outputs include a rating waterfall showing the path from entry to exit rating, and heat maps identifying periods of rating stress. This model is used by corporates managing their credit profile and capital structure to maintain or improve ratings; credit analysts evaluating issuers; lenders assessing credit risk for commercial loans; and investment committees evaluating fixed-income holdings. It provides forward-looking insight into credit trajectory without waiting for agencies to publish their ratings. ## What's included - Leverage ratios: Net Debt/EBITDA, Total Debt/EBITDA, Loan-to-Value - Coverage ratios: Interest Coverage, DSCR, EBITDA-to-capex - Liquidity: Days Cash on Hand and loan covenant cushion - Default probability from credit metrics using agency mappings - Rating outlook and rating triggers - Liquidity: Days Cash on Hand, Loan covenant cushion - Default probability from credit metrics (using agency mappings) ## How the Credit Rating Model Works: Drivers, Calculations and Practical Use This credit rating model helps you forecast credit metrics and estimate an indicative internal rating without waiting for agency decisions. It links a five-year financial forecast to debt repayment, scoring, recovery analysis and pricing. The underlying template shows how leverage, coverage and business risk combine, so you can evaluate the methodology before using it for scenario testing. ### Operating and Financing Drivers Behind the Forecast The model builds a five-year forecast for a sample industrial borrower, Apex Industrial Holdings, with separate industrial and consumer revenue streams. Revenue for each segment grows at its own input rate, and costs, capital expenditure and working capital are driven by ratios or days tied to revenue or costs. - Reported EBITDA is adjusted to credit-agreement EBITDA by adding back synergies, restructuring, stock compensation and other items. Debt repayment follows five tranches, each with an opening balance, coupon and tenor, amortising or repaying as a bullet. - Interest uses opening debt balances, while cash interest income applies a fixed rate to opening cash. The eight-sector input is not referenced by any formula, so the template remains a single industrial sample rather than switching between sector models. ### From Financials to Credit Metrics Operating and debt schedules feed the income statement, balance sheet and cash flow, which in turn populate the credit metrics. Four ratios—net leverage, FFO to debt, EBITDA to interest and FFO to interest—are each converted to scores using input thresholds. - For every displayed year, the scorecard uses the median of all five forecast years for each metric, then applies input weights to produce a financial risk score. Business risk combines industry, country and competitive-position scores. - The rounded business and financial scores locate a numeric anchor on a 6×6 matrix, and manual or peer modifiers adjust the numeric rating, bounded between 1 and 21. This structure means the annual scorecard repeats five-year medians rather than showing a distinct year-by-year migration path. ### Recovery Analysis, Expected Loss and Pricing Outputs The recovery waterfall values stressed Year 5 reported EBITDA at an input multiple, subtracts administrative costs and allocates the remaining value to secured, unsecured and subordinated debt. Recovery-based loss-given-default bands determine indicative instrument notches. - Expected loss is calculated as a hardcoded rating-to-probability-of-default lookup multiplied by claim-weighted LGD and Year 5 debt. Indicative yield to maturity adds a rating-based hardcoded spread to an input seven-year Treasury yield. - All thresholds, peer percentiles, probabilities and spreads are illustrative placeholders, not current verified agency or market data. The model does not issue an agency rating and uses Year 5 debt for recovery rather than a selectable default date. ### Practical Use and Documented Limitations You can use the template to relate operating assumptions to credit metrics and an indicative internal rating, and to see how stressed EBITDA and debt levels affect recovery and expected loss. The dashboard summarises the headline rating, outlook, risk profiles, instrument ratings and expected loss. - However, several boundaries are documented: the sector input does not change thresholds, one-off EBITDA addbacks recur every year, the scorecard repeats five-year medians, and the revolver has no liquidity-driven draws. Pricing is a spread and yield translator, not discounted bond cash-flow pricing. - Some checks enforce illustrative ranges, so a failed check may simply reflect a scenario outside those bands. The public download is a values-only preview, not a live calculation file, and the model does not establish compliance with agency methodologies. ## Rating scale mapping to agency benchmarks Use agency-published mappings from S&P, Moody, and Fitch to convert your calculated metrics into rating equivalents for pricing and covenant analysis. ## Stress and scenario rating analysis Model your implied rating under different EBITDA and leverage scenarios so you understand rating volatility before a deal or covenant test. ## Default probability calibration Translate calculated credit metrics into probability of default using historical default rates by rating category. ## Rating scale mapping to agency benchmarks Use agency-published mappings from S&P, Moody, and Fitch to convert your calculated metrics into rating equivalents for pricing and covenant analysis. ## Stress and scenario rating analysis Model your implied rating under different EBITDA and leverage scenarios so you understand rating volatility before a deal or covenant test. ## Default probability calibration Translate calculated credit metrics into probability of default using historical default rates by rating category. ## Features - **Rating scale mapping:** Use agency-published mappings (S&P, Moody's, Fitch) to convert your metrics into rating equivalents. - **Stress and scenario rating:** Model your rating under different EBITDA and leverage scenarios so you understand rating volatility. - **Default probability calibration:** Use historical default rates by rating to translate your calculated metrics into probability of default (PD). ## Use cases - **Debt issuance and pricing:** Use your estimated rating to benchmark pricing and terms versus actual market data for comparable debt. - **Covenant monitoring:** Track metrics quarterly and get early warning when you approach covenant breach or rating downgrade risk. - **M&A analysis:** Model the pro forma credit profile post-acquisition and ensure the financing structure maintains your target rating. ## Frequently asked questions ### What is a credit rating model? It is a model that calculates leverage, coverage, and liquidity metrics and maps them to agency rating scales to estimate an implied debt rating and probability of default. ### How accurate is a self-estimated credit rating? Agency ratings typically lag by 6 to 12 months and incorporate qualitative factors. A self-estimated model provides a quantitative floor and early warning of deterioration. ### What is a good interest coverage ratio? A ratio above 3.0x is generally strong and maps to BBB or better. Below 2.5x typically indicates high-yield or distressed credit. ### How do I model default probability? Use the Merton model leveraging equity volatility and firm value, or apply rating-to-PD lookup tables published by rating agencies. ### Who uses credit rating models? Treasurers, rating analysts, lenders, and credit officers use them for debt issuance pricing, covenant monitoring, and pro forma credit analysis in M&A transactions. ## Related templates - [Debt Schedule](https://finamodel.com/templates/debt-schedule) - [Credit Stress Testing Framework](https://finamodel.com/templates/stress-testing-model) - [Bank Loan Analysis Model](https://finamodel.com/templates/bank-loan-model)