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Risk engine

B2B credit risk scoring: decisions in under 2 seconds

Our credit scoring engine combines artificial intelligence, machine learning and hundreds of real-time data sources to assess the risk of every B2B buyer with precision that traditional methods cannot match.

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847 LOW RISK
+200
Variables analysed
24/7
Continuous monitoring
+40
Data sources
The problem

Deciding blind is the most expensive luxury in B2B

Without robust scoring, every credit sale is a gamble. And B2B gambles are paid with defaults, cash tension and good clients you reject for lack of information.

🎲

You approve clients by intuition

Without enough data, credit decisions rely on the sales rep's gut feeling, a quick internet search or "they seem reliable". That works until it doesn't.

🚫

You reject good clients

Without precise scoring, you apply overly conservative criteria and reject solvent companies that would have paid without issue. Every good client you reject is a sale you lose.

⏱️

Days to evaluate, seconds to lose the sale

Requesting credit reports, manually checking bureaus, waiting for the insurer's response. Meanwhile, your client buys from the competition. In digital B2B, those who hesitate lose.

📉

Static models that age badly

A credit report from 6 months ago doesn't reflect a company's current situation. Static models don't detect early deterioration signals. By the time you find out, the default has already happened.

Data sources

We do not assess with one source. We cross-check dozens in real time.

Every query triggers a cross-verification process combining financial, corporate, behavioural and sector data from multiple providers simultaneously.

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Company registries

Corporate data, directors, share capital, company age and legal structure across Europe.

📊

Credit bureaus

Solvency reports, external scoring, payment history and risk alerts from leading providers.

🏛️

Official public data

Official gazettes, default registries, insolvency proceedings, liens, sanctions and compliance lists.

🔐

Open Banking (PSD2)

Consented access to buyer bank data: balances, transactions, spending patterns and real payment capacity.

🧾

Tax and VAT data

Intra-community VAT/tax ID verification, active fiscal status and declared information consistency.

📈

Sector data

Industry benchmarks, sector default rates, payment cycles and macroeconomic trends.

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Behavioural signals

Purchase patterns, frequency, volume, seasonality and buyer behaviour evolution on the platform.

🛡️

Credit insurers

Complementary scoring from leading European insurers. Dual validation that reinforces engine accuracy.

How it works

Three intelligence layers that reinforce each other

Our engine is not static scoring. It is a system that learns, adapts and improves with every transaction it processes.

Data collection and cross-referencing

In milliseconds, the engine simultaneously queries dozens of external and internal sources. It cross-references financial, corporate, tax and behavioural data to build a 360° buyer profile. It does not depend on a single source: redundancy is what generates precision.

Predictive AI/ML models

Machine learning algorithms trained on thousands of real B2B transactions analyse patterns that a human analyst would never detect. Gradient boosting, neural networks and ensemble models work in parallel to calculate default probability with surgical precision.

Continuous learning

Every transaction the engine processes — approved, rejected, paid or defaulted — feeds back into the models. The system recalibrates automatically, improving accuracy over time. It is not a static model: it is a living organism that evolves with your portfolio.

// Engine response in under 2 seconds
{
  "buyer_id": "ES-B12345678",
  "score": 847,
  "risk_level": "low",
  "credit_limit": 75000,
  "confidence": 0.94,
  "sources_checked": 43,
  "decision": "approved",
  "processing_time_ms": 1847
}
Differentiators

Why our scoring is unlike anything you have seen

🧠

Multi-layer ensemble models

We do not use a single model. We run multiple algorithms in parallel and combine their predictions with ensemble learning techniques. The result: more robust decisions than any individual model, with less bias and greater scenario coverage.

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Automatic recalibration

Static models lose accuracy over time. Ours recalibrates automatically with every new transaction, detecting changes in market behaviour, new risk patterns and early deterioration signals before they become defaults.

🌍

International coverage

We have built a mosaic of data sources with a special focus on Europe, where we cover all markets with native sources. We also provide coverage outside the EU, adapting available sources in each country. The engine adjusts automatically to the buyer geography.

👥

Specialist team behind it

Behind the engine is a team of data scientists, risk analysts and B2B credit experts who supervise, tune and improve the models continuously. The technology is powerful, but human intelligence is what makes it exceptional.

Independent and modular

You can contract scoring alone

You do not need the full BNPL. If you already have your own financing or credit insurance, you can integrate our scoring engine via API and use it to evaluate your buyers in real time. You decide what to do with the response.

🔌
API REST
One call, one response in under 2 seconds. Full documentation and sandbox.
🧩
Modular
Scoring only, or scoring + KYB, or scoring + insurance. You combine the modules you need.
📊
Dashboard
Monitor decisions, model performance and portfolio evolution in real time.
FAQ

About the scoring engine

What data do you need from the buyer?
Just the tax ID number. With that, our engine automatically queries all available sources and builds the complete profile in seconds. If the buyer authorises Open Banking, accuracy improves further.
How long does the decision take?
Under 2 seconds for 95% of queries. In cases requiring additional verification (new companies, inconsistent data), the engine may take up to 30 seconds while consulting complementary sources.
What if the engine rejects a buyer I know is good?
Scoring is a recommendation, not an imposition. You can set custom thresholds and business rules. If you decide to approve a transaction the engine rejects, you can do so by assuming the risk or requesting manual review.
Can I use scoring alone without other modules?
Yes. Scoring is an independent module with its own API. Many companies integrate it into their existing operations to improve credit decisions without changing the rest of their infrastructure.
Do the AI models comply with European regulation?
Yes. Our models comply with GDPR, PSD2 and EU AI Act guidelines for high-risk systems. We offer decision explainability (why approved or rejected) and full traceability of data used.
Does scoring improve over time?
Yes. The engine recalibrates automatically with every transaction. The more transactions it processes, the more data it has to refine predictions. It is a system that learns and improves continuously.

Want to learn more?

Request a personalised demo and discover how FutureBNPL can transform your B2B operations.

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