Global Sanctions Index

Castellum.AI built the first ever Global Sanctions Index (GSI) to assess the accuracy and completeness of data contained in sanctions lists, how easy lists are to access, and the level of guidance provided by the issuing authorities. The GSI’s purpose is to help governments, businesses, international organizations and the public better understand the risk of sanctions violations and financial crimes in every country. A strong sanctions regime, or lack thereof, is a clear indicator of how well a country fights financial crime. The more developed a country’s sanctions list, the better its ability to fight financial crime.

Rating Global Sanctions

Each sanctions list is rated against 20 distinct criteria within three categories: Data Integrity, Data Delivery, and Guidance. Each criteria is weighted according to its impact on sanctions compliance. For example, Data Integrity has a higher weight than Guidance because obtaining the data itself is the first and most important step in compliance. If you don’t know who is on a list, guidance around it is largely useless. The final weighted score goes from 0-100% and ranks sanctions lists across languages, data formats, and size.

Castellum.AI reviewed 198 countries as well as supranational sanctions lists issued by the United Nations and European Union.

• Best
  80-100% indicates that the sanctions list is easy to find and use, the sanctions data is clean and well-structured and that the list supports compliance efforts.

• Helpful
  60-79% indicates that a sanctions list supports compliance efforts despite needing improvements in data quality, guidance and data delivery.

• Afterthought
  1-59% indicates that the government behind the sanctions list published it without considering data structure, guidance and how to effectively communicate sanctions to the private sector and the public. These lists are difficult to find, difficult to use and difficult to understand. They generally lack identifiers, create a higher than average amount of false positives and, in some cases, are actually detrimental to compliance.

• No list
  0% means that a country does not have a publicly available autonomous sanctions list. That a list be public is crucial, because if information is not accessible, it cannot help compliance.

See the Methodology section for more information on the criteria used in the GSI and how sanctions lists are scored.

Global Sanctions: A Summary

78% of countries globally do not have their own sanctions list, instead implementing sanctions agreed to by supranational organizations like the United Nations (UN) and European Union (EU). The UN and EU lists require broad international agreement, which is increasingly hard to find in the global policy community.

Meanwhile, 22% of countries have their own autonomous sanctions list, which are usually geared towards the issuing country’s national security concerns and are independent from global or regional sanctions lists. Having an autonomous sanctions lists enables governments to quickly react to changing national security concerns without relying on supranational organizations.

However, the quality of autonomous sanctions lists vary widely across countries. Among those with autonomous sanctions lists, scores ranged from 21% to 93%.  

How Common are Sanctions Across Regions?

At 40%, APAC has the most countries with autonomous sanctions lists. 26% of countries in Europe have autonomous sanctions in addition to enforcing European Union and/or United Nations sanctions. 16% of countries in MENA and Africa have autonomous sanctions lists. Half of the MENA countries have their own lists, but only one country does in Sub-Saharan Africa: South Africa. The Americas contain the fewest autonomous sanctions lists, with only 9% of countries publishing autonomous sanctions.

Sanctions Quality by Region

The average rating for sanctions lists globally is 60%, indicating that only half of these lists are helpful, and outlining the huge challenge for regulators and compliance professionals in enforcing sanctions. The quality of sanctions lists differs greatly across global regions with a 39% difference between the highest average regional score of the Americas and the lowest average regional score belonging to MENA and Africa. 

Regional reports, linked below, provide our detailed findings on sanctions trends and link to a page for every single country globally, stating if it has an autonomous sanctions list or not, and if it does, what is the quality of the list.

North & South America

The Americas scored highest for autonomous sanctions lists at 79%, meaning that most lists are easy to use for sanctions screening. While there are 35 countries in the Americas, only three have autonomous sanctions: Argentina, Canada, and the United States. Notably, the US Office of Foreign Assets Control Specially Designated Nationals and Blocked Persons List (OFAC SDN) received the highest score globally with 93%, lifting the regional average in the Americas.

Europe

Europe has the second-highest regional score at 71%. Autonomous sanctions lists scores varied greatly across the region with France’s Registre Des Gels receiving a score of 90% and Russia’s Rosfinmonitoring List of Terrorists and Extremists receiving the lowest score at 51%. All 27 European Union members adhere to the EU consolidated sanctions list, which scored 88%.

APAC

APAC sanctions lists are difficult to use, lack clear data schema and provide little guidance, resulting in a regional score of 56%. Despite being the world’s second largest economy, China’s Ministry of Foreign Affairs (MFA) sanctions received the lowest score globally at 21%. Nearly four fifths of APAC countries received scores lower than 75%, with most of the lists having poor data quality, lacking explanations for why sanctions were imposed, and not communicating data effectively to the private sector and the public.

MENA and Africa

The MENA and Africa region has the lowest average score for autonomous sanctions with 53%. The MENA/Africa region’s score is primarily driven by new sanctions lists which do not have the advantage of decades of improvements as in the Americas or Europe. These lists generally lack a strong data schema and are difficult to find and use, but have also shown rapid improvement in a short period of time.

GSI Standouts

The best-scoring sanctions list is the US OFAC SDN list with 93%, followed by France’s Tresor Registre Des Gels and Qatar’s Unified Record of Designated Persons and Entities. These three lists share similarities due to their structured and detailed data presentation, including unique identifiers for all entries. Unlike many lists scoring under 75%, such as the Indonesian DTTOT list and Belgian FPSF list, the lists from the US, France, and Qatar also include watchlist search tools and publicly available guidance, contributing to their accessibility and usability. 

China’s Ministry of Foreign Affairs sanctions received the lowest score globally with 21%. The Chinese Ministry of Foreign Affairs publicizes new designations through press releases, does not maintain a consolidated autonomous sanctions list and also removes the press releases after short periods of time. The lack of a consolidated list is the largest factor that resulted in such a poor score. Saudi Arabia’s List of Designated Individuals and Entities and Palestine’s Freezing List both received poor scores due to a lack of a data schema, lack of guidance, lack of data delivery and the lack of recent updates.

Explore GSI Rankings

Methodology

How did Castellum.AI assess autonomous sanctions lists? We developed a comprehensive model built around a central question: how easy is it to comply with a sanctions list, based on the structure, availability, and clarity of the data in the list? The practical application of how compliance is achieved allows for a detailed and objective approach to assessing sanctions lists across different formats, structures, languages, and, of course, content.

Our model is structured using frameworks that have been honed by country risk rating firms and experts for decades. We created a set of 20 criteria which are essential to sanctions compliance to objectively measure which lists are the easiest to comply with, and which are the hardest. Each criteria is weighted based on its impact on compliance. The criteria are then scored on a scale of one through five. Once scored and weighted, the results are compiled to arrive at a final weighted score that can be compared against other sanctions lists.

These criteria are grouped into three categories, detailed below.

1. Data Integrity     

Data integrity measures the quality and structure of data on each sanctions list. Castellum.AI divided this category into ten criteria that include the existence or lack thereof of a data schema, the detail of the schema, the freshness of the list, and the likely resultant false positive rate (a sanctions list that does not provide dates of birth will lead to a high false positives rate). Since the US OFAC SDN list provides unique identifiers for almost every entry (such as IDs, dates of birth and place of birth), the US list scored the maximum in the unique identifier component of the data integrity category. 

2. Data Delivery

There are seven criteria under the data delivery category, which includes the existence and functionality of a watchlist search tool, availability of automated notifications for sanctions list updates, the availability of multiple sanctions file formats, and the overall accessibility and ease of use. This category also covers how easy it is to find and access the sanctions list itself: is it buried on an obscure government authority’s website or is it easy to find?

3. Guidance

This category has three criteria which pertain to whether explanations are readily available as to why an entry is listed and whether guidance is available on the sanctions list’s web page. It also concerns whether justifications are directly linked to an entry. France’s Tresor Registre Des Gels includes a public guide regarding the searching of the watchlist and also includes detailed explanations for each entry for why they were sanctioned, resulting in a perfect score under the guidance category of the ranking sheet. 

About Castellum.AI

Castellum.AI obtains global sanctions information from primary sources, and then proceeds to standardize, clean and enrich the data, extracting key information like IDs and addresses from text blobs. Castellum.AI enriches as many as fifteen separate items per entry. This analysis is based on the enriched primary source data that populates our database. The database consists of over 1,000 watchlists, covering over 200 countries and eight different categories (sanctions, export control, law enforcement most wanted, contract debarment, politically exposed persons, regulatory enforcement, delisted, and elevated risk). Castellum.AI checks for watchlist updates every five minutes directly from issuing authorities.