From the July - August 2010 issue: Measuring Secrecy

The Financial Secrecy Index (FSI), developed by the Tax Justice Network in 2008, ranks jurisdictions based on the opaqueness of their financial markets. Put more crudely, the FSI, designed to complement Transparency International’s Corruption Perceptions Index, ranks the world’s tax havens, or secrecy jurisdictions.

Developed in cooperation with government officials, researchers and civil society organizations from many countries, the FSI uses only publicly verifiable sources. It combines two measures—one qualitative, one quantitative. The qualitative measure is an Opacity Score based on existing laws, regulations and treaty information. The quantitative measure weighs each jurisdiction based on the scale of the offshore financial services it hosts. The Opacity Score is the more important of the two. Using an assessment of how aggressively a jurisdiction provides secrecy facilities, the score highlights specific features likely to attract illicit financial flows.

The degree of opacity is assessed using 12 indicators grouped into three themes: transparency of ownership information, transparency of corporate activity and engagement in international cooperation to combat harmful practices.

Once an individual jurisdiction assessment has been completed, the aggregated results are arithmetically squared to emphasize differences in transparency among jurisdictions. This emphasis is important, since even small differences in the secrecy on offer can facilitate significant volumes of illicit financial flows. Finally, the values are normalized by dividing through by 100, giving an Opacity Score between 0 (absolutely transparent) and 100 (absolutely opaque).

The quantitative data, weighting each secrecy jurisdiction according to the scope of its cross-border financial services activity, uses either IMF data on cross-border trade in financial services or, where that data is unavailable, estimates of holdings of foreign portfolio assets. The quantitative and qualitative datasets are combined arithmetically by simple multiplication.1

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See also: Catching up with Corruption by Raymond Baker, John Christensen & Nicholas Shaxson
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