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Detect the risks and ensure the legality of your actions

We identify anomalies and optimize their treatment using tracking and pattern detection algorithms. We continuously monitor legislative developments to highlight upcoming changes and ensure the compliance of your business.

Detecting irregular financial activities

With a Brazilian investment bank based in São Paulo, we are developing a solution that identifies fraudulent transactions based on detecting suspicious behavior patterns.

  How does it work?

  • Detection of habits and everything that constitutes a "behavior" thanks to our AI replacing the current system of rules.

  • Construction of a behavior analysis tool.

  • Development of a scoring model, taking into account the irregular potential of a behavior.

  • Development of an interface for the restitution of the algorithm's detection results.

Automate regulatory watch

We are helping a leading French bank and insurer automate its regulatory monitoring process. Our client's compliance experts use the Reg Review solution to identify new regulatory standards, summarize them, identify the people and departments impacted in the organization, inform them via a newsletter, and manage all compliance tasks. Previously time-consuming and performed manually, these tasks are now automated and optimized.

What does Reg Review do?

  • Scan the sources sharing new regulations.

  • Collect and analyze data from these sources.

  • Provide detailed reports and customized alerts. Manage tasks (Business Process Management function) in a value chain.

  • Share information from automated intelligence.

AI solutions for compliance

Our publications


Boosting search engine capabilities of RegReview:…

RegReview is an AI solution for compliance teams, to automate regulatory monitoring and processes, which brings together several tools, the most essential of which is a search engine operating on a compiled database of custom-built regulatory sources.

The database contains ~300k documents.


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Synthetic data or how to share sensitive data…

For a period of six months, 5 students from Centrale Supélec and ESSEC worked collaboratively with Sia Partners on building a Python library to create fake - which we'll call synthetic - data.
But what's the point of creating fake data? How could it help organizations?


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Introduction to OpenStreetMap: How to leverage…

In this article, we explore the use of OpenStreetMap for extracting geospatial data and implementing an approach to enhance the overall data quality. We delve into the key steps of data extraction including selecting the area of interest, data collection, cleaning, and preparing data for future use.


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