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The Global Sanctions & Watchlists (2020–2025) dataset focuses on sanctions-related information about individuals, companies, vessels, and cryptocurrency wallets. The available dataset description indicates coverage of more than 62,000 entries, making it a potential resource for studying sanctions data and compliance screening.

Sanctions lists help organizations identify individuals and entities that may be subject to legal or regulatory restrictions. Therefore, structured sanctions data can support research into compliance workflows, entity matching, and risk assessment. However, users should verify the source and status of individual records before drawing conclusions.

Key Features

• Historical Coverage: Focuses on sanctions and watchlist information associated with the 2020–2025 period.

• Multiple Entity Types: The available description identifies individuals, companies, vessels, and cryptocurrency wallets.

• Compliance Research: Supports the study of sanctions screening and regulatory compliance processes.

• Data Analysis: Provides a starting point for examining records and identifying data quality issues.

• Entity Matching: Can support research into name matching and record comparison, depending on the available fields.

Review the original dataset files to confirm the exact record count, source authorities, columns, and historical coverage.

Applications of the Dataset

1. Sanctions Screening Research

Researchers can examine how sanctions information supports screening workflows. For example, they can explore methods for comparing names and identifying possible matches. However, a potential match requires further verification before any decision is made.

2. Compliance and Risk Analysis

Compliance teams and students can study how organizations organize sanctions information for review. In addition, the dataset can support educational exercises involving regulatory data and risk-screening processes.

3. Entity Matching and Data Quality

Sanctions records may contain different spellings, aliases, or similar names. Consequently, analysts can explore data cleaning, duplicate detection, and entity resolution techniques to improve record matching.

4. Cryptocurrency and Financial Crime Research

The dataset’s stated coverage of cryptocurrency wallets may support research into sanctions-related digital asset monitoring. Nevertheless, a wallet entry alone does not establish ownership, activity, or a legal violation.

5. Data Analytics and Machine Learning

Students and researchers can investigate record classification, text matching, and data visualization. The suitability of these tasks depends on the dataset’s actual fields and available labels.

Why Use This Dataset?

The Global Sanctions & Watchlists (2020–2025) dataset provides a starting point for exploring historical sanctions information and compliance-related data analysis. Moreover, its stated coverage of several entity types creates opportunities to study record matching and structured data processing.

However, sanctions information can change over time. A historical record may not reflect an entity’s current status. Therefore, users should consult relevant official sources before making legal, financial, or compliance decisions.

Conclusion

The Global Sanctions & Watchlists (2020–2025) dataset can support research into sanctions screening, entity matching, compliance workflows, and data analytics. It may be useful for students, researchers, and analysts studying regulatory data.

This dataset is sourced from from Kaggle.