Corporate governance disclosure among African firms: A text mining perspective

We examine corporate governance (CG) disclosures in Africa, examining the scope, pattern, trends, and extent of disclosures. We employ textual analysis of annual reports from 52 firms across various African countries and sectors, spanning nine years. Using Python-based text mining techniques, we identify disclosure patterns across seven corporate governance categories. Our findings reveal that Board Structure and Functioning and Audit and Risk Management are the most frequently disclosed categories. Conversely, disclosures in Ethics and Compliance and Compensation and Remuneration are significantly lower, reflecting a reluctance to disclose sensitive information in the absence of strict regulatory mandates. Sectoral variations were evident, with larger firms and those in heavily regulated industries, such as banking and telecommunications, exhibiting higher disclosure levels. The trend analysis shows a gradual increase in corporate governance disclosure over the period, particularly in Transparency and Disclosure and Shareholder Rights and Relations. The study highlights the potential of enhanced corporate governance disclosures to attract investment, improve stakeholder trust, and support sustainable business practices. However, the lower disclosure levels in Ethics and Compliance and Compensation and Remuneration highlight the need for more stringent regulatory frameworks and enforcement mechanisms in Africa.