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Toward A.I. Recommitment Strategies for ESG integration in Private Equity

Financement: European Investment Bank > STAges de REcherche BEI-EIB research internships
Date de début: 1 janvier 2021
Date de fin: 31 août 2021

Description

The rise of Environmental, Social, and Governance (ESG) factors has been one of the major changes for private equity partners. ESG considerations have redesigned the standards of due diligence and add new objectives on top of financial statements and growth plans. Building private equity portfolios remains a real challenge for limited partners investors with heavy consequences on ESG/Sustainable investments. This lack of guidance is certainly the main barrier to overcome in order to give confidence to investors and encourage investing in innovative and sustainable technologies. Policy makers have tasked institutional investors such as the European Investment Bank (EIB) to invest in a sustainable future for all. Nevertheless, the different objectives, levels of risk aversion, ESG exposure and time-horizons are subject to complex constraints and trade-offs. Under such circumstances, there is a real need to design guidance mechanisms to leverage private equity responsible investments.

Achieving and maintaining high allocation to private equity and keeping allocations at the targeted level through recommitment strategies is a complex task and needs to be balanced against the risk of becoming a defaulting investor. When looking at recommitments we are quickly faced with a combinatorial explosion of the solution space, rendering explicit enumeration impossible. The multi-objective nature of the recommitment problem creates numerous alternatives that can be difficult to apprehend for investors.

For this reason, investors need guidance and decision aid algorithms producing reliable and robust sustainable and trustworthy recommitment strategies. By trustworthy, we mean intelligible rules for investors and domain experts. Using an optimised AI-assisted system in normal market conditions, strategies are likely to provide more guidance and flexibility while becoming a testbed for extraordinary market conditions. In this project, we propose an innovative approach to generate sustainable and trustworthy recommitment strategies with the aid of AI-based algorithms. Our main attempt is not only to develop an algorithm replacing human strategies but also to design a Sustainable and Trustworthy AI Recommitment System (STAIRS) guiding dynamically the search of recommitment strategies in order to build portfolios of responsible investments. To support all the development and tests, this project will strongly rely on High Performance Computing (HPC) to cope with the computing power requested by such an AI-based system. The use of HPC hardware-accelerated code (e.g. GPU, FPGA, TPU) will be decisive to push back the frontiers of achievable while reducing tremendously the time needed to provide satisfying solutions.

The STAIRS research project will be conducted at the FSTM by Dr. Emmanuel Kieffer, research Scientist in the HPC group, under the supervision of Prof. Dr Pascal Bouvry from the University of Luxembourg and Dr. Hakan Lucius from The European Investment Bank.

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