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Achieve Operational Excellence thanks to AI

We develop AI solutions to accelerate business processes such as new customer onboarding and fraud risk monitoring. Beyond the automation of manual tasks, our solutions increase the performance of your activities by enriching them with intelligent insights into customer knowledge.

Increase KYC compliance goals

The KYC process is a regulatory requirement that requires accurate screening throughout the customer lifecycle, from onboarding to the end of the relationship. Our solutions leverage various external data sources, such as the financial press, to increase the quality of the screening algorithms and detect additional risks affecting prospects and customers, whether they are companies or individuals. The risks integrated by these algorithms cover economic and financial issues and CSR policy and image.

Detecting fraud intelligently

Fraud is a complex risk to predict due to the low volume of cases observed, preventing the development of effective business rules. Our algorithms combine the business expertise of our financial services fraud consultants with machine learning methods specifically designed to highlight atypical cases synonymous with suspicion. Enhancing internal data with external sources such as partner e-reputation also improves the performance of these detection tools.

AI solutions for operational optimization

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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