Introduction
In 2025, managing credit risk between companies has become a strategic factor. Payment deadlines are lengthening, defaults are rising again, and financial departments need reliable tools more than ever to anticipate payment arrears.
B2B financial scoring addresses this need: it allows you to assess the creditworthiness of a client or prospect and make quick, rational decisions. In this guide, we detail the data sources, modeling methods, use cases, and best practices for successful deployment.
What is B2B Financial Scoring?
B2B financial scoring is a process of evaluating the probability that a company will honor its financial commitments (repayment, supplier payment, compliance with covenants). Unlike scoring for individuals, it relies on more heterogeneous and often less standardized data.
Main objectives:
The main data sources
Reliable scoring relies on the ability to aggregate multiple sources:
1. Banking data (Open Banking / PSD2)
- • Cash flow, average balances, outstanding amounts
- • Detection of payment incidents (NSF, rejections)
- • Volatility of cash inflows and outflows
2. Accounting and tax data
- • Balance sheets and income statements
- • Trends in margin, debt, equity
- • VAT returns, tax package
3. Legal and Public Data
- • Commercial registers, directors, beneficial owners
- • Insolvency proceedings, litigation, registration of liens
- • Company's history of creation and evolution
4. Behavioral Data
- • Payment history (delays, late payments)
- • Dispute rate, frequency of invoice challenges
- • Past commercial relationships (turnover, order regularity)
5. Relational (Graph) Data
- • Supplier/customer network
- • Detection of at-risk clusters (domino effect)
- • Sector analysis (fragility of an ecosystem)
👉 The strength of modern scoring lies in combining these streams to move from a simple static rating to a dynamic and predictive score.
Frequently Asked Questions
What is B2B financial scoring and why is it important?
B2B financial scoring is a process of quantitatively evaluating the solvency of client companies. It significantly reduces unpaid invoices by identifying risks before they materialize, accelerates credit granting decisions, and optimizes client portfolio management.
What data is used in a modern B2B scoring model?
Effective B2B scoring combines several sources: financial data (balance sheets, cash flow), banking information (payment history, incidents), behavioral data (payment delays, disputes), and legal information (proceedings, directors). This multi-data approach significantly improves predictive accuracy.
How do I integrate a financial scoring system into my company?
Integration is generally done via REST API in 3 steps: connection to existing systems (CRM, ERP), configuration of business rules, and team training. Take advantage of a 14-day free trial with credits included to test RocketFin in your environment.
What is the difference between traditional scoring and AI predictive scoring?
Traditional scoring is based on static financial ratios, while AI predictive scoring analyzes hundreds of variables in real-time, detects weak signals, and adapts to market changes. AI models offer superior accuracy compared to traditional methods.
How much does it cost to implement a B2B scoring system?
Costs vary depending on the size of the company and the volume of transactions. Modern solutions like RocketFin offer transparent pricing with no installation fees, with an ROI generally achieved quickly thanks to the reduction of unpaid invoices.
Is B2B financial scoring compliant with GDPR?
Yes, professional solutions comply with the GDPR by using only legitimate data (consent, legitimate interest), guaranteeing transparency of decisions, and allowing the exercise of the rights of the persons concerned. RocketFin is fully compliant with European regulations.
Can scoring models be customized according to our business sector?
Absolutely. Modern scoring models adapt to sector-specific characteristics (construction, commerce, services) and the business criteria of each company. This personalization improves the relevance of evaluations and reduces false positives.
Conclusion
B2B financial scoring is a strategic lever for any company wishing to reduce its unpaid invoices and secure its cash flow. Players who know how to combine multiple data sources, predictive models, transparency, and seamless integration will gain a head start on their competitors.