The Challenge
Investors hold large numbers of private infrastructure debt positions. Unlike listed bonds, these instruments lack public credit ratings from S&P, Moody's or Fitch, a liquid secondary market for price discovery, standardised peer benchmarks for comparison, and transparent deal-level spread and performance data.
Risk teams fall back on manual, case-by-case assessments — slow, inconsistent, and impossible to scale across the portfolio.
What a solution must deliver
The Solution
A reduced-form credit risk model turns the company-level data investors already hold into a per-company credit view — probability of default, shadow credit grade, peer comparables, and sensitivity to input changes.
Why the model works
Validated against public ratings
87% alignment with rating agencies over five years when classifying the same issuer as Investment Grade vs. Non-Investment Grade.
Model average PD ranges closely match observed default rates across corporate, project and utility segments (S&P 2022 study).
How It Works
Every risk driver in the model is observable from financial statements and deal terms investors already collect. No proprietary data required.
| Risk Driver | Applies To | Direction of Effect on Credit Risk |
|---|---|---|
| Interest Coverage Ratio | Corporate | Higher coverage → lower default risk |
| Leverage / Debt-to-Asset Ratio | Corporate & Project | Higher leverage → higher default risk |
| Cash Flow Available for Debt Service | Project | Stronger DSCR → lower default risk |
| Cash & Quick Ratio (liquidity) | Corporate & Project | More liquidity → lower default risk |
| Return on Assets | Project | Higher profitability → lower default risk |
| Firm Size & Age | Corporate | Larger / older firms → more resilient |
| TICCS® Business Model | Corporate & Project | Captures cash flow stability |
| Economic Region & Risk-Free Rate | Corporate & Project | Local macro & cost-of-capital effects |
All variables are observable from financial statements and deal terms investors already collect. No proprietary data required.
Worked Example
UK renewable energy project loan · XXX-00417
Drop in a firm's key parameters — country, sector, structure, latest financial ratios, age and credit event history — and the model returns a full credit view instantly.
| Loan ID | XXX-00417 |
|---|---|
| Value Date | 31/12/2025 |
| Country | United Kingdom |
| TICCS Sector | Renewables |
| Structure | Project finance |
| Firm age (years) | 11 |
| DSCR (CFADS) | 1.45 |
| Leverage ratio | 0.68 |
| Cash ratio | 0.22 |
| Quick ratio | 0.95 |
Scaling Up
The same model runs across an entire loan book at each point in time, and reconstructs a full credit history for any single firm — giving investors a single, consistent view of credit risk across every exposure.
A single, consistent view of credit risk across every exposure in the book — sectors, countries and structures side by side, run from one spreadsheet or API call.
Credit transition tracking, early-warning signals and refinancing-risk analysis — the story of how a loan's risk has evolved, one firm rated every year it reported financials.
| Value Date | Company ID | Country | Sector | Structure | Age (yrs) | Shadow PD | Market-Eq. Grade | Bucket |
|---|---|---|---|---|---|---|---|---|
| 31/12/2025 | XXX-00417 | Germany | Renewables | Project | 12 | 1.62% | Non-Investment Grade | Medium |
| 31/12/2025 | XXX-00418 | Singapore | Transport | Project | 28 | 0.84% | Investment Grade | Low |
| 31/12/2025 | XXX-00419 | UK | Network Utilities | Corporate | 41 | 0.19% | Investment Grade | Low |
| 31/12/2025 | XXX-00420 | Australia | Energy & Water | Corporate | 15 | 1.91% | Non-Investment Grade | Medium |
| 31/12/2025 | XXX-00421 | Italy | Social | Project | 6 | 1.44% | Non-Investment Grade | Medium |
Each row is a different infrastructure firm — countries, sectors, structures and ages vary across the book, same value date, same model, one run. 315 more rows not shown.
What Investors Get
Every loan carries a comparable PD and grade. The credit view of the book is no longer dependent on which loans happen to be rated.
Run thousands of instruments in seconds. Free up analyst time for judgement calls rather than spreadsheet mechanics.
Outputs usable under Solvency II, PRIIPs and similar frameworks that expect PD / LGD-style metrics for unrated exposures.
Flex any input — leverage, DSCR, country, rate environment — and see the portfolio's PD response immediately.
Anchor an internal view to observed behaviour across 700+ infrastructure firms globally, not a handful of public comparables.
Every rating decomposes into its input drivers, making conversations with auditors, boards and regulators straightforward.
