SME/VSE Solvency: Assessing and Anticipating Risk

SMEs and VSEs represent the majority of the economic fabric in Europe, but also one of the most vulnerable categories to defaults. Assessing their solvency is a major challenge: sometimes incomplete data, simplified balance sheets, strong dependence on a few customers. However, an adapted scoring system can significantly reduce payment defaults and secure commercial relationships.

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Why is SME/VSE solvency a specific issue?

Fragile lifecycle

High mortality rate within the first 5 years

Limited access to financing

Fewer guarantees, banking dependence

Customer concentration

One or two strategic clients can represent > 50% of revenue

Simplified accounting

Fewer details in the balance sheets

👉 Consequence:

A "classic" scoring system based solely on financial ratios is often insufficient.

Essential data to collect

1. Bank Flows

Regular receipts?
Cash flow peaks or chronic tensions?
Dependence on 1 or 2 large payers?

2. Accounting

Recurring or volatile net results?
Positive or negative equity?
Revenue evolution

3. Payment history

Average payment terms
Past disputes
Reputation within the sector

4. Public data

Recently registered?
Experienced or novice managers?
Past insolvency proceedings

5. Transactional behavior

Order frequency

Average transaction size

Complaint rate

Build a score tailored to SMEs

Liquidity score

Based on bank flows to assess immediate ability to pay

Structural score

Analysis of the simplified balance sheet (debt, equity)

Behavioral score

Payment habits and consistency of commercial relationships

Sector score

Sector exposure (Construction, catering, commerce)

👉 The aggregation of these partial scores

provides a more refined view than a simple financial ratio.

Concrete use cases

Rapid onboarding

Automate credit decisioning for new SME clients

Continuous Monitoring

Trigger an alert in the event of a sudden drop in cash for outstanding VSEs

Intelligent Recovery

Prioritize collection efforts towards the riskiest small businesses.

Credit insurance

Supplement internal analysis with predictive scoring.

Limitations and best practices

Beware of false negatives.

A solid VSE can appear fragile if only financial ratios are considered.

Frequent updates

Implement monthly or quarterly updates.

Quantitative and qualitative data

An experienced manager or customer diversification can compensate for an average balance sheet.

Explainability

Make the score readable for sales representatives who manage the customer relationship.

FAQ

Is it possible to score a company with limited data?

Yes, by starting with public data and bank feeds, then enriching over time.

Is SME/VSE scoring reliable?

With multi-source data, a very good level of prediction is achieved (> 80% accuracy over 12 months).

Should a specific model be used for VSEs?

Yes, because their financial structure differs from that of a mid-sized company or a key account: little capitalization, dependence on immediate cash flow.

Conclusion

SMEs/VSEs are essential but fragile. An adapted scoring model, combining banking, accounting and behavioral data, reduces the risk of default and builds more sustainable business relationships. With modern tools like RocketFin, it becomes possible to automate this assessment and make fast, transparent and reliable decisions.