In an ideal world, all your documents (legal, marketing, commercial...) should provide the same level of information about your financial products. In reality, these documents often contain discrepancies that can have serious consequences for your business.
The cross-document consistency check consists of analysing and comparing the contents of several documents to identify and correct potential discrepancies.
Once tedious and time-consuming, this task can now be automated thanks to artificial intelligence... under certain conditions.
Documentary consistency control is primarily a regulatory issue. The European Directive MiFID II requires financial services firms to provide clear, accurate and non-misleading information to their clients. In France, AMF doctrine also requires consistency between advertising communications and product regulatory documents.
Your teams juggle thousands of documents, dozens of versions and languages. The workload is immense and requires your full attention. The risk? Inconsistencies slipping through the cracks.
"This level of risk is increased in the context of the AI bubble. When it bursts, clients who have lost money will look for the slightest documentary error to hold financial institutions accountable."
Traditionally, consistency control is based on human review and Excel checklists of points to control. More recently, generalist LLMs have also been used (often in secret) to read or compare texts. Here's why these methods fail:
With the constant increase in the volume of documents to be examined, the workload of the collaborators who carry out the reviews becomes unsustainable. Teams spend hours checking information that should be identical.
The content to be reviewed is often several pages long, with a complex language combining financial and legal terms. Subtle deviations can be difficult to spot. Furthermore, human fatigue caused by re-reading increases the risk of error.
Large generalist models still suffer strongly from hallucinations, i.e. false but convincingly formulated responses. They are not trained to understand financial language and not designed to apply strict and reproducible business rules.
The majority of general LLMs are not sovereign solutions. Platforms like Chat GPT or Gemini are exposed to legislation such as the Cloud Act and the Patriot Act, which jeopardises the confidentiality of your sensitive information.
A sovereign AI specialised in finance, whose model is trained to finely understand the semantic subtleties of financial language. The solution is ready for use, without any complex training or setting.
You upload the documents to be compared (KID, contracts, sales brochures, marketing leaflets, etc.).
The model compares documents based on a defined table of key indicators (more than 150 consistency points). It compares the values from one document to another and detects discrepancies, even when the formulations are not identical. The solution is also able to compare information even when it is not in the same format, like a table and a product sheet.
The tool generates a structured report that is easy to read in order to rapidly review any identified discrepancies.
The era of tedious and time-consuming checklists is over.