Financial inclusion: between good intentions and real impact

1.4 billion adults in the world do not have access to a bank account. In France, the problem is different but just as real: access to credit is lacking. Self-employed people, young people with no credit history, and people in precarious situations regularly encounter refusal, even when their real financial situation would allow it.

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Credit is a powerful tool for economic inclusion. But it's also a double-edged sword.

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Credit and inclusion: a fine border

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Giving access to credit to populations that were excluded from it is a real advance. But if improperly calibrated, this same credit can worsen a fragile situation. The BNPL (Buy Now Pay Later), for example, has opened access to finance to millions of people. It has also generated situations of over-indebtedness among profiles who should not have been granted these facilities.

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Responsible financial inclusion is not measured by entry. It is measured by the way out: were the people to whom we granted a loan able to repay it without ending up in a debt spiral?

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The traditional scoring problem

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Classic scoring models were designed at a time when professional stability was the norm. They don't read atypical profiles well:

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• Variable incomes (independent, intermittent, seasonal)
• No credit history (young people, newcomers)
• Transitional situations (resuming business after a difficult period)

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The result: rejections that do not reflect the real risk. And people who are turning to more expensive, less protective alternatives.

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What Open Banking is changing

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THE Open Banking allows access, with the customer's consent, to real banking data: income flows, recurring charges, account management behavior. It is a revolution for solvency analysis.

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Where traditional scoring sees “independent = high risk”, a model based on Open Banking sees regular income, a remains to live comfortable, and zero payment incidents over 12 months. They are two fundamentally different interpretations of the same situation.

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But Open Banking alone is not enough. The models that exploit it still need to be designed to detect these nuances, not just to reproduce the logic of classical scoring with richer data.

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To go further on banking data and their use in scoring, see our article: When the algorithm decides: AI and responsible financing

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What B Corp requires: measuring real impact

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That's where the certification B Corp Change something. It does not ask to show intentions. It requires the measurement of results.

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For a financing player, this means in concrete terms:

• Follow the gearing clients financed over time
• Measuring the acceptance rate on profiles that have been historically excluded
• Document where the model allowed for inclusion without creating additional risk

It's not communication. It's responsibility.

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Meelo's commitment

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At Meelo, financial inclusion is not a marketing argument. It is an objective of the company with a mission : increase the acceptance rate of applications with limited risk, by giving funding organizations the tools to distinguish real risk from perceived risk.

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Our solvency analysis platform combines open banking, behavioral and documentary data to give a more accurate picture of each situation. Not to accept just anyone. So as not to turn away the wrong people.

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See how our customers are using these tools: Meelo customer cases

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