Project objectives

Building PE portfolios remains a real challenge for LP 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.

Viewing limited partnership as cash-flow assets and designing portfolio of funds depends on the ability to project cash-flows (see Cornelius, 2013) and score funds. In any case, 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 problems 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. Indeed, there is very limited experience with exceptional market situations such as the global financial crisis in 2008–2009 and the subsequent Great Recession. Here Artificial Intelligence can be therefore very convenient to come up with new strategies that help institutional investors in protecting the value of their portfolios of limited partnership funds and even flourish under such circumstances.

Consequently, this project will focus on the development of a new AI-assisted algorithm producing sustainable and trustworthy recommitment strategies to protect and enhance the value of LP funds’ portfolios.