What is a solvency score? Definition, calculation and B2B use
A solvency score is a composite numerical indicator — typically expressed on a 0 to 100 scale — that summarises a company's ability to meet its financial obligations. It is used by leasing companies, banks, and B2B financing teams as a rapid decision-support tool.
In brief: a solvency score aggregates multiple financial and non-financial signals — balance sheet ratios, bank flow regularity, legal signals, payment behaviour — into a single composite indicator. Unlike a credit bureau report (which relies primarily on historical payment data), a modern solvency score uses fresh data updated continuously. A score of 0-100 allows teams to prioritise risks without reading a full analyst report.
Definition: what a solvency score measures
Solvency, in financial terms, refers to a company's long-term capacity to honour its debts and commitments. A solvency score translates this multi-dimensional concept into a single number by weighting indicators across four data categories:
Balance sheet ratios: debt/equity, financial autonomy, net debt/EBITDA. Derived from published annual accounts.
Cash flow regularity, average balance, absence of incidents. Collected via Open Banking (consent) or OCR of physical statements.
Insolvency proceedings (safeguard, administration, liquidation), late filings, director changes. From official public registries.
Payment behaviour (DSO), sector risk, company age, growth trajectory. Contextual signals that complement financial data.
The engine assigns a weight to each category and produces a final score between 0 (very high risk) and 100 (very low risk). For detailed ratio definitions, see our guide to key solvency ratios.
How a solvency score is calculated
Modern scoring engines use a hybrid approach — statistical models (regression, gradient boosting) combined with rule-based expert logic — to produce explainable scores. The key steps are:
- 1Data collection
The engine queries multiple data sources simultaneously — accounting filings, Open Banking flows, official registries — for the target company identified by its registration number.
- 2Normalisation
Each raw indicator is normalised against a reference population (sector, company size, age) to produce comparable sub-scores.
- 3Weighting and aggregation
Sub-scores are combined according to a weighting model calibrated on historical default data. Weights can differ by sector (e.g. banking data carries more weight for service companies than for manufacturers).
- 4Score output and explainability
The final 0-100 score is produced alongside the key factors that drove it — both positively and negatively. This explainability layer is required by the EU AI Act for high-risk AI systems used in financial decisions.
How to interpret a solvency score in practice
Standard credit conditions can be applied. Monitor annually.
Review in detail. Consider additional guarantees or shorter contract terms.
Require security deposits or guarantors. Increase monitoring frequency.
Default risk is significant. Refuse credit or apply maximum security conditions.
Frequently asked questions
What is the difference between a solvency score and a credit rating?
A credit rating (from agencies like Moody's or S&P) is designed for large listed companies and assessed by analysts. A solvency score is an automated, algorithmic indicator applicable to any B2B company — including SMEs and young structures. It is calculated in real time from fresh financial data, not from a periodic analytical review.
What score is considered acceptable for a B2B credit decision?
Score interpretation depends on the scoring provider and the risk appetite of the organisation. As a general benchmark: scores above 70/100 typically represent low to moderate risk; between 40 and 70, moderate risk requiring additional analysis; below 40, elevated risk requiring specific conditions or collateral. These thresholds must be calibrated to your portfolio.
Can a solvency score be wrong?
Any scoring model carries a margin of uncertainty. Key risk factors are data quality (outdated filings, incomplete information) and timing (a company can deteriorate rapidly between two assessments). This is why scores should be updated frequently and combined with human judgement for large exposures.
Is a solvency score compliant with EU AI Act requirements?
Decision-support scoring systems used in financial contexts fall under the EU AI Act's high-risk category. Compliant systems must provide explainability (each score factor is justified), auditability (a complete trail of data inputs and model logic), and human oversight capability. RocketFin's scoring engine is designed to meet these requirements natively.
Get a solvency score in 30 seconds
RocketFin delivers a 0-100 solvency score on any B2B company in under 30 seconds, from +100 data points. Explainable, auditable, EU AI Act compliant.