Our Methodology

The Anti-IFF Policy Tracking Tool presents a comprehensive methodology for monitoring and evaluating the performance of tax-based anti-IFF policies across African countries. Our approach is designed to provide an objective, standardized, and data-driven assessment, enabling stakeholders to identify policy gaps, track progress, and understand effective reforms.

Policy Mapping & Gap Identification

Policy Mapping & Gap Identification

We compare existing tax-based anti-Illicit Financial Flows (IFFs) policies against a set of recommended indicators or good international practices. This comparison helps identify clear policy gaps in strategic efforts to curb IFFs both at the country and regional levels.

Good Practices & Success Stories

Good Practices & Success Stories

Our methodology provides a snapshot of a country's efforts, successes, and capacity challenges in implementing adopted recommendations to stem IFFs. It also enables consensus among stakeholders, assists in setting reform priorities, and monitors a country's progress in the continuing reform agenda.

Implementation Status & Progress

Implementation Status & Progress

Our methodology indicates the current status of policy implementation and the remaining gaps to be closed in a given country. It also allows for a comparison over time and across countries, providing insights into the degree of policy progress. 

Reform Insights & Advocacy

Reform Insights & Advocacy

Our methodology provides a snapshot of a country's efforts, successes, and capacity challenges in implementing adopted recommendations to stem IFFs. It also enables consensus among stakeholders, assists in setting reform priorities, and monitors a country's progress in the continuing reform agenda.

Scoring Methodology

Indicator-Based Scoring

We structure the policy tracker around four clusters of anti-IFF thematic areas, each associated with specific recommended indicators. For single-dimensional clusters, the indicator score is the cluster score. For clusters with two or more indicators, we assess each indicator separately, combining the scores by choosing the lowest score given for any dimension.

Weighted & Normalized Scoring

We assign a weight to each indicator, with the total weight of each cluster amounting to 100. The final score for each indicator is calculated by multiplying the weight by the chosen score. The total indicator scores are then divided by 300 to present the final cluster score within a standardized range, facilitating easier interpretation and comparison.

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