Optimization of the Credit Portfolio and Methodology for Evaluating a Public Support Policy: The Case of the Support Fund for Large Ivorian Enterprises (FSGE)

The article employs a logistic regression model to predict defaults and optimize credit portfolios for enterprises receiving support, showcasing a rigorous methodological approach. It relies on empirical data to ensure the relevance of its findings and utilizes the Evidence-Based Policy Making (EBPM) method, incorporating propensity score matching techniques to correct for selection biases, thereby ensuring accurate evaluations. Additionally, the work adheres to international standards set by the INTOSAI Guide 9020, enhancing its academic credibility. Ultimately, the proposed solutions contribute to both financial theory and public management practices, illustrating the author's ability to harmonize theoretical frameworks with practical applications.