More and more investors wish to invest their money in companies that meet certain criteria for environmental, social and corporate governance (ESG). To this end, machine learning helps to evaluate the performance and sustainability of globally listed companies according to such ESG-defined criteria. Only high-performance shares of companies that can demonstrate certain standards regarding their environmental and social behavior as well as responsible corporate governance are then taken into account.
Together with Arabesque Asset Management Ltd, Fraunhofer SCAI is developing innovative mathematical methods for machine learning processes that can be used to determine complex ESG-compliant equities – and thus to assemble a high-performance portfolio. In addition, the procedures allow predictions about the future potential of the respective shares and assets. The results provide precise investment recommendations for institutional investors.