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Sophisticated risk management with AI

We combine state-of-the-art machine learning algorithms with our detailed knowledge of natural and human risks to better predict and mitigate these risks.

Defining climate scenarios

We use our Weather & Climate solution, dedicated to the acquisition and processing of large volumes of meteorological data, to define climate scenarios over different horizons. In conjunction with our actuarial experts, we integrate these scenarios into the risk models of our banking clients so that they can fine-tune their provisions and risk management strategy.

Modeling systemic economic crises

We mobilize various external data sources, such as corporate financials, to simulate crises that would spread throughout the global economy. These models allow us to provide estimates of these systemic risks to feed the catastrophe models of insurers and reinsurers, in particular on corporate liability.

AI solutions for rish management and modeling

Our publications


French energy companies and digital transformation

Big Data, Smart Factory, Cloud... the advent of new digital technologies is perceived by companies as a source of competitive advantages, especially in sectors requiring operational asset management such as energy.


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Ano detection

Detection and interpretation of outliers thanks…

Anomaly detection is the process of identifying irregular patterns in data. Its use is widespread, from fraud detection to predictive maintenance or churn detection. As a result, a whole branch of machine learning algorithms has been developed around these topics.


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Anomaly Detection in Time Series

Anomaly Detection is becoming ubiquitous throughout all industries as one of the most important data science use cases to address.
An anomaly, or outlier, can be defined as a point that does not fit the pattern of the rest of the data or expected results. While there are many different origins to an


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