Machine Learning Techniques for Corporate Governance

Even with much growth, development, evolution, advancement and contribution to the governance mechanisms studies on firm and market performances, there are no clear consensus on governance issues like CEO duality, board diversity, CSR impact and other parameters. A need is felt to harmonize various concepts, theories, models of corporate governance to meet the idiosyncratic needs of a firm. There is a need of new data sources, technologies, research methods as a customized approach to meet the gaps of existing literature and find better constructs to understand the intricacies of governance mechanisms and help find resolution of conflicting or unexplored results. One of such trajectories is machine learning techniques that can tailor the data collection, process and analyze various sources for decision-making processes. This chapter aims to provide creative integration of corporate governance mechanisms with machine learning techniques in order to achieve managerial powers resulting in competitive advantages. It looks at the areas wherein technology can provide the required core competencies by providing solutions to enhance accurate and effective managerial decision-making, reduce their opportunistic behaviour and thereby improve firm’s ability to handle different uncertainties in business. This move should be towards a more universal and holistic approach through synergistic intelligence to help shaping governance mechanisms and decision making in years to come.