This article follows up on a previous piece where we discussed the upcoming DCC2 regulation on credit. Today, we are pleased to speak with Paul Peyré, co-founder and head of Risk and Data at Algoan, a fintech specializing in next-generation credit scoring based on Open Banking data.
Paul Peyré, co-founder and head of Risk and Data at Algoan
Paul, could you introduce yourself and share what led you to create Algoan?
In 2018, after several years at Fitch Ratings as Director of Structured Finance, I co-founded Algoan with Michaël Diguet, pioneering credit decision-making based on Open Banking data. We were convinced that advanced algorithms leveraging Open
Banking data would significantly outperform traditional credit issuance, which relies on sometimes unfair and inefficient socio-demographic criteria and involves lengthy, complicated processes.
Specifically, what is Algoan's business?
Algoan provides credit decision support tools for financial institutions. These tools are based on Open Banking data and are available in API format. We also offer a bank account aggregation product with a custom-built client interface for credit,
featuring “compliant by design” consent management. Finally, we provide a Data Dashboard, a visualization tool to facilitate the monitoring of client files and decision-making.
How do Open Banking API-based credit scores compare to traditional methods?
With Open Banking, recurring income and expenses are directly accessible from transactional banking data. These data allow lenders to ensure that borrowers can repay their credit. Additionally, banking data enables a clearer understanding of an individual’s
financial profile, including the balance between income and expenses or the identification of financial difficulties (such as missed payments, specific bank fees, excessive overdraft use, etc.). Compared to traditional scores, which in France
are mainly based on socio-demographic data, we have observed significant performance improvements, with up to a 40% increase in acceptance rate for the same level of risk and a 50% reduction in risk cost at the same level of acceptance.
Lenders
highly value these performance gains and the reliability of Open Banking data. Unlike the self-reported data used in traditional scores, Open Banking data is factual, up-to-date, and retrieved directly from the source. Consequently, as of 2024,
the majority of lenders, including the subsidiaries of French banking groups, are already using Open Banking scoring, with Algoan in particular. Besides improving risk management and financial inclusion, we reduce processing costs and enable fully
digital subscription processes with instant decision-making. As a result, we’re seeing strong growth in the adoption of these new methods.
How does artificial intelligence also contribute to strengthening these scoring models?
Scoring based on transactional data presents numerous challenges, especially when it comes to structuring and enhancing this data for decision-making systems. Bank data categorization, which is crucial for solvency analysis, is complex due to the
variety of transaction labels, banking terminology, and differing conventions across financial institutions. Using AI models such as Large Language Models (LLMs) helps improve transaction categorization by facilitating the annotation of large data volumes, error detection, and more. AI is, therefore, a powerful innovation driver for enhancing
our tools' performance.
The Second Consumer Credit Directive (DCC2), which will be implemented in French law by November 20, 2025, requires enhanced verification processes for income and expenses for all credits up to €100,000. What will be the impact of this directive?
DCC2 will strengthen solvency assessment requirements to better control borrowers' repayment capacity and thus prevent over-indebtedness. Solvency analysis will now need to be “based on relevant and accurate information on the consumer’s
income and expenses,” which may include “proof of income or other sources of repayment, information on financial assets and liabilities, or details of other financial commitments.”
Currently, the only security checks for
credit issuance are the National Register of Credit Payment Incidents (FICP) and the requirement to provide proof of identity, residency, and income for any loan above €3,000. The need to document decisions is therefore reinforced, focusing
not only on income but also on expenses. Today, Open Banking data is the only comprehensive and reliable data source that meets these needs: income and expenses, credit installments, bank fees, evidence of rejected payments, or other negative
credit risk indicators (such as account garnishments).
DCC2 will impact actors previously unaffected by credit regulations, such as BNPL providers. How will these players need to prepare for this new directive?
Indeed, DCC2 broadens the definition of consumer credit to all non-mortgage loans up to €100,000. Thus, DCC2 applies notably to:
- leasing operations with a purchase option (LOA),
- overdraft and credit line contracts, and
- deferred payment facilities.
This last area includes “Buy Now, Pay Later” (BNPL) services. BNPL providers will need to conduct a solvency assessment at the time of issuance, even though their main focus is to offer a smooth customer journey. Here again, Open Banking
appears to be the optimal solution. The customer simply needs to connect to their banking app and authorize the sharing of their banking data, which can then be automatically retrieved, analyzed, and used to generate a score within seconds.
What about the use of Open Banking scoring for other products or segments, such as real estate loans or business credit?
Open Banking is also very suitable for real estate loans. Instead of providing three months of bank statements, a borrower can use Open Banking to share their banking information, allowing for a quick assessment of debt levels and disposable income.
A preliminary agreement can then be granted within minutes by a credit analyst, and simple cases may even be processed automatically. Real estate brokers are the first to adopt these solutions.
For business credit, especially for small businesses or micro-enterprises, which traditional players have always struggled to serve due to a lack of relevant data, Open Banking offers a fresh approach. Accounting data is often inadequate due to its
outdated nature or lack of granularity, making it difficult to assess credit risk for these actors. In mid-2024, Algoan launched an extension of its service to accommodate this type of clientele.