This article uses business language to discuss the modelling foundations for The Financial Health System. If you have not done so already, we recommend reading What is the FHR first.
Model Foundations
The FHR is a 0-100 score, expressed across five risk categories, and each FHR is associated with an Estimated Probability of Default (EPD). The FHR model uses a sophisticated industry-specific approach to benchmark financial characteristics against 40+ years of historical performance. We identify characteristics of strong companies in the best of times and weak companies in the worst of times to determine how rated companies compare. Do the financial characteristics resemble firms which default, firms which survive, or firms which thrive?
Key model features include:
- Financial Statements Only: Our models are based entirely on financial statement information. We exclude:
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- Analyst opinion which can lead to inconsistency across ratings
- Market level inputs that can cause arbitrary rating fluctuations
- Industry Specificity: We use 24 industry models to ensure each company is appropriately benchmarked, whereas most alternative services only use 4 or 5. This allows RapidRatings to take a more granular approach in assessing the financial viability of companies across industries.
Overview
Our competitive edge lies in our separation of analyses into three stages for a more dynamic and accurate measurement of Financial Health.
- Measure Core Health: Is the company’s operational performance sustainable? The Core Health Score (CHS) is an industry-specific measurement of a company’s efficiency and likelihood of remaining competitive through market fluctuations. Core Health is significantly influenced by profitability performance.
- Measure Resilience: Does the company have the financial capacity to meet its obligations? We assess three key elements: Leverage, Liquidity and Earnings Performance
- Measure Financial Health: What is the likelihood of default or bankruptcy over the coming 12 months? Financial Health captures a dynamic interaction between Core Health and Resilience
A company with strong Core Health is unlikely to experience distress and is afforded considerably more flexibility with leverage and liquidity requirements. As Core Health deteriorates, the importance of strong Resilience increases if the company is to survive. A company with poor Core Health and poor Resilience is at the highest risk of failure.
Core Health
The Core Health model measures a company’s efficiency and competitiveness, from both an operational and a structural perspective. Additionally, it provides an upstream and downstream scan of a company’s profitability.
Figure 1: Core Health Categories
Figure 2: Measuring The Core Health Score (CHS)
Resilience Indicators
The Resilience Indicators measure a company’s leverage, liquidity and earnings performance. They interact dynamically with Core Health to indicate lower or higher short-term risk. Strong Core Health makes a company less sensitive to the impact of its Resilience Indicators. However, as a firm’s Core Health deteriorates, its Resilience Indicators become increasingly important and will have a more significant impact on the final FHR. This dynamic interaction between Core Health and Resilience is a key pillar of the FHR’s predictive ability.
- Leverage is a solvency metric that depicts the extent to which a firm’s assets are dependent on debt as compared to equity.
- Liquidity measures the ability of the firm to survive any short-term crises that drain its asset reserves.
- Earnings Performance assesses the firm’s efficiency in managing internal constraints and internal opportunities to generate upstream and downstream profitability to permit the firm to meet internal obligations and external obligations.
Figure 3: Dynamic Interaction of Core Health and Resilience Indicators
FHR and EPD%
The analysis described produces the FHR, a 0-100 score expressed across five risk categories, and each FHR is associated with an Estimated Probability of Default (EPD).
Figure 4: The Risk Categories and EPD Ranges
FHRs have shown to be exceptionally accurate at predicting default risk. The chart below depicts more than 90% of defaulters have FHRs which are High or Very High Risk.
Figure 5: FHR Distribution at Default for 1500+ defaults
