Ai-powered investment decision

Discover our approach
Our approach

Our vision

Our vision

Can you predict how a multitude of drivers will impact financial markets?

Within a complex environment where humans cope with contradictory signals, it is crucial to identify relevant variables to rationalize investment decision.

Ai for Alpha has designed Artificial Intelligence solutions to help professionals build resilient portfolio allocations and understand key drivers of financial regimes.

Our proprietary approach “Explainable Ai 360” enables professionals to spot key market drivers and make unbiased investment decisions.

Our approach

Our approach

Ai for Alpha uses the most advanced Machine Learning techniques to deliver accurate anticipations about financial markets.

This process results in a dynamic asset allocation that adapts in real time to changing market conditions.


Our model is helping financial professionals build resilient portfolio allocations and understand key market drivers, in any market situation.
Our methodology is based on four distinct steps with a full screening of risks in order to provide a smart allocation.

Market features

Selecting relevant information among hundreds of variables and data

Regime prediction

Anticipating regimes shifts and financial cracks

Allocation decision

Providing the most relevant allocation based on the client’s constraints and risk profile

Ai 360 Explanation

Spotting key drivers to provide transparent and rational decisions (explainable AI)

Augmented Intelligence

Augmented Intelligence

Leveraging on Ai potential, investment decisions take on a more powerful dimension.

An Algorithm Trained Over Time

An Algorithm Trained Over Time

Our incremental model is continuously being trained and developed with the most recent market data.

Strategic Use of Data

Strategic Use of Data

Macroeconomics, interest rates, government decisions, inflation and company valuations: Ai for Alpha analyzes hundreds of drivers by testing their prediction power on specific markets.

Infer Daily Investment Decision / Allocation of Market Environment

Infer Daily Investment Decision / Allocation of Market Environment

Proprietary models find optimal allocations based on predictions derived from data.

Anticipating Market Risks

Anticipating Market Risks

Predicting asset returns with 100% accuracy will always be deceiving. Our proprietary models have identified common invariants to bull and bear market regimes in various asset classes. Our systems detect the most meaningful relationships between factors and market dynamics.

Explainable Data

Explainable Data

Our approach is fully transparent. We apply our “features importance” methodology to extract key drivers that impact portfolio allocation at any time.


Our clients are asset allocation decision makers.

Asset Managers

Investment Banks

Institutional Investors

Wealth Managers

You can choose to receive daily insights on “Ai 360 portfolios”, or customized recommendations.

Ai 360 Portfolios

We provide daily allocation signals on equity indices and multi-asset portfolios. We use the latest explainable Ai techniques to highlight the key drivers of allocation decisions.

All signals are transparent and can be explained by our AI 360 explainable approach.

  1. Daily updated and automated allocation
  2. Probability of crisis for each underlying factor
  3. Explanatory factors for each signal
Today Market regime
French Equities 3%
EU Equities 4%
UK Equities 3%
US Tech Equities 10%
Japan Equities 3%
China Equities 3%
US Large Cap Equities 13%
Brent 31%
Gold 21%
US 10-Year Bond 5%
EUR 10-Year Bond 4%
Total 100%
Suggested Allocation example

Customized Plan

Our tailored technology-based solutions adapt to the specific clients’ constraints. We leverage our technology to co-develop custom-made solutions with investment professionals based on their expertise in specific asset classes. Selection of factors can be adapted with the client to fit his management style.

Our offer then combines the business know-how brought by the customer and the scientific expertise of Ai For Alpha.


Our model filters a multitude of factors impacting financial markets in order to recommend the most relevant allocation.
Technical indicators
Market Breadth, Investors Positioning
Price Indicators
Risk adjusted returns, Volatilities, Momentum
Risk Perception
Implied Volatilities, Credit Spreads
Macroeconomic factors
Growth, Inflation, Interest Rates’ evolution, Central Banks monetary decisions
Financial Metrics
Earnings, Sales, Valuation Multiples

We stack a supervised learning approach based on Gradient Boosting Decision Trees with deep reinforcement learning. We leverage our expertise in interpretable machine learning techniques.

Features selection

Filtering & final features

Regime prediction


Portfolio construction

Deep Reinforcement learning

AI 360 Explanation

Features’ marginal contributions
Risk management is fully integrated into the process. We incorporate reinforcement learning techniques to dynamically control risks.

Clients & partners

Our clients are asset allocation decision makers.

Our partners

Ai For Alpha has received funding from the European Institute of Innovation and Technology (EIT).
This body of the European Union receives support from the European Union's Horizon 2020 research and innovation program.
Finance Innovation
Ai For Alpha has received the worldwide Finance Innovation label in 2020.



CEO & Board Member
Béatrice has more than 20 years of experience in financial markets. She worked in structuring departments of various investment banks (JP Morgan, Deutsche Bank, Société Générale). Béatrice graduated from the engineering schools Ecole Polytechnique and ENSAE. She holds two masters degrees, one in financial mathematics from LPSM (laboratoire de probabilités statistique & modélisation) and one in finance from the London School of Economics.

Scientific team

Scientific Advisor & Board Member

Eric Benhamou has worked at Goldman Sachs and Natixis, as the head of quants. He founded a start-up supplying financial derivatives independent valuation that was purchased by Thomson Reuters.

Eric Benhamou is ranked in the top 0.01% of researches on SSRN, the open Social Science Research Network, with a world wide ranking of 60 over 500 000 researchers. Eric published over 60 articles.

He is a Polytechnique, ENSAE and London School of Economics Alumni and obtained two PhDs one in Economics and one in Mathematics and a master in AI from Dauphine and ENS Ulm.

Scientific Advisor & Board Member

Jean-Jacques has twenty plus years of experience in asset management. He started his career as a quantitative investment engineer. He then founded a fintech company called Riskelia. He served as the CIO of Homa Capital and created several quantitative funds.

Jean-Jacques received the Lipper Award in 2019 for the best Managed Futures Fund over three years. He is a regular Financial TV broadcast Speaker.

Jean-Jacques is a CentraleSupélec Engineer School Alumni and is a CFA Charterholder.

Data scientist

David is finalizing a PhD in Reinforcement Learning within the machine learning laboratory specialised in signals and images (CNRS/LISIC). He was previously a consultant in actuarial sciences at Prim’Act and data scientist at the Institut Louis Bachelier Datalab.

David will be coheading with Eric Benhamou the Deep Reinforcement Learning course in the IASD Master programme in artificial intelligence in partnership between Dauphine, Ecole Normale Ulm and Mines Paristech.

David graduated from Dauphine University. He holds two masters degree in Actuarial Finance and Artificial Intelligence.


Business Angel and Senior Advisor in Fintech. Founder and Former Deputy CEO at Ossiam
Managing Director, Senior Advisor ESG
General Manager of EMEA at AptiviO, and serial entrepreneur in the digital field
Senior Advisor and Board Member. Managing Director of Impact Private Equity at Mirova and former General Partner at Rothschild & Co


Associate Partner at LBO France
Head Of Research at Lombard Odier Investment Managers