Definition
Alternative credit scoring assesses a borrower's creditworthiness without relying solely (or in addition) on traditional bureau scores — FICP in France, Schufa in Germany, FICO in the US.
It combines alternative data: AIS bank flows, BNPL payment history, digital behaviour, telecom data, company records, invoices. Enabled by PSD2 (which opened access to flows via AISPs), it can assess in a few seconds profiles that bureaus cover poorly.
The limits of traditional bureau scoring
In France, unlike the US or the UK, there is no positive score (FICO-style). The tools are negative: FICP (repayment incidents, over-indebtedness), FCC (cheque and card incidents) and each bank's own internal scoring. As a result, first-time borrowers, freelancers, newcomers and young people without a long history are invisible or penalised. Alternative scoring fills this gap.
The data used
- Bank flows (AIS): recurring income, fixed charges, average balances, savings rate, overdrafts, committed share of spending — the number-one source.
- BNPL / payment history: on-time repayments at Alma, Klarna, FLOA.
- Telecom data: payment regularity (mostly in Africa, rarer in Europe for GDPR reasons).
- Behavioural data: account age, number of banks, geographic stability.
- Self-declared: contract type, seniority, family situation.
- Company data (B2B): SIREN, age, sector, invoices, outstandings (Pappers, Heron Data).
The methodology: supervised ML
A model is typically a gradient boosting one (XGBoost, LightGBM), sometimes a neural network, trained on default history ("did the customer default at 12 months?"). It produces a score or probability of default, yielding a binary decision (threshold) or multi-tier one (rate by score). Explainability is mandatory for consumer credit (SHAP values, refusal reasons), under the right to explanation in Article 22 of the GDPR.
Major use cases
- BNPL (Klarna, Alma, FLOA, Younited Pay): instant scoring at checkout for fee-free 3x/4x instalments.
- Instant consumer credit: Younited, FLOA, Cetelem decide in 3 to 5 minutes, versus 3 to 5 days at a bank.
- SME / freelance business credit: Karmen, Defacto, October qualify unstable income via flows and invoices.
- Earned wage access (EWA): Stairwage, Rosaly estimate the employee's available cash.
- Embedded finance: scoring built into a merchant's checkout via API.
What alternative scoring is not
- Not a replacement for FICP: checking the FICP remains mandatory for consumer credit (Lagarde law); scoring complements it.
- Not FICO-style "positive scoring": France has refused a national positive register for 30 years; each player has its own proprietary model.
- Not exempt from the right to explanation: Article 22 of the GDPR requires explaining automated decisions and allowing human intervention.
- Not magic: the best models gain +5 to +15 Gini points over the traditional bureau — useful, not miraculous.
Quality criteria
- Gini / AUC: ability to separate good and bad payers (target Gini > 60% for solid consumer credit).
- Approval rate: share of accepted applicants, to be weighed against the default rate.
- Default rate: defaults at 12 months among the accepted (2 to 8% on BNPL).
- Latency: < 2 seconds for a checkout integration.
- Stability: resistance to drift over time (otherwise retraining).
In the PSD2 ecosystem
PSD2 was the catalyst for alternative scoring in Europe: before, only banks had the flows; with AIS, any lender can (with consent) retrieve 12 to 24 months of history. If FIDA is adopted, outstanding credits, savings and insurance will be added, for an even more accurate score.
Concrete examples
- B2C players: Algoan (a scoring building block sold to banks and fintechs), FLOA (BNP), Younited Credit, and the in-house models of Klarna and Alma.
- Younited: built its business on alternative scoring (AIS flows + self-declared data); a credit institution authorised by the ACPR since 2011, listed on Euronext Paris.
- Algoan: an SDK/API plugged into an AISP (Bridge, Tink) that returns a score and its reasons, sold to BNP, Cofidis and neobanks.
- Heron Data: B2B focus (US and UK SMEs), qualifying flows for credit, factoring and leasing.
- EWA: Rosaly and Stairwage score the employee on their salary flows to advance part of the net pay.
- GDPR / ethics limit: the use of behavioural data (geolocation, social networks) is highly contested in Europe; serious players stick to AIS, self-declared data and the bureau, explicitly consented.
- Evolution: use of LLMs for transaction context, models that are transparent by design, and pressure from the AI Act (2026), which classifies credit scoring as high-risk AI.