Investment objective: The investment objective of OSSIAM EUROPE ESG MACHINE LEARNING (the “Fund”) is to deliver the net total return of a selection of equities which are listed in Europe. The Fund is a actively managed and will only use its benchmark, the Solactive Europe 600 Index NTR (the “Benchmark”) for performance and carbon emission comparison purposes. The Fund’s portfolio composition is therefore not constrained by the Benchmark and may deviate significantly from the Benchmark’s constituents. Investment policy: In order to achieve its investment objective, the Fund can use total return swaps with the objective of delivering synthetically the performance of a portfolio of equities which are selected and weighted as detailed under the Investment Strategy. This method implies a counterparty risk as described in the below Risk and Reward Profile. The net asset value per share of the Fund will therefore increase (or decrease) according to the evolution of the portfolio of equities. The counterparty to the swaps will be a first-class financial institution that specialises in this type of transaction. The Fund may also enter into multiple swap agreements with multiple swap counterparties with the same characteristics as previously described. Alternatively, the Fund can invest directly in all or part of the equity securities which are selected by applying the Investment Strategy. In any case, the Fund will be invested in for a minimum of 75% in equities or rights issued by companies having their registered office in the European Economic Area, excluding Liechtenstein. In addition, and on an ancillary basis, the Fund may use other derivatives for hedging and investment purposes as described under “Use of Derivatives, Special Investment and Hedging Techniques” in the Prospectus. The Reference Currency of the Fund is the Euro. Investment strategy: The Management Company uses a quantitative model which implements a rule based approach that aims to assess large and mid-cap equities from developed markets based on financial data and ESG (Environment, Social, Governance) ratings. The model first applies an Ethical Filter (as defined in the Prospectus) to exclude securities that inter alia are in breach of the 10 principles of the UN Global Compact or have significant operations in coal industries. Securities which pass the Ethical Filter are then further screened by the Management Company’s model using both ESG and financial data. The Management Company then uses an optimisation procedure to determine the weights of the equities selected by the quantitative model, so that the portfolio complies with a number of constraints including a reduction by 40% of the total greenhouse gas emissions and the potential greenhouse emissions from reserves of the portfolio compared to the Benchmark and an ESG rating of the portfolio at least 10% higher than that of the Benchmark.