What is a sanction check? Complete guide for compliance teams

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A sanction check is the process of screening individuals, companies, or countries against official sanctions lists to ensure an organisation does not conduct business with prohibited parties. These checks play a critical role in preventing financial institutions, insurers, fintechs, and corporates from engaging with sanctioned entities reducing legal, financial, and reputational risk.

This guide explains what sanction checks are, why they matter, how they work, including common challenges and the role of technology.

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A sanction check (or sanctions screening) compares customer or transaction data against sanctions lists maintained by governments or international bodies. The goal is to detect, prevent, and manage sanctions risk by identifying sanctioned persons, organisations, vessels, and countries before any financial activity takes place.

Main sanctions list providers

Some of the main sanctions list providers across the globe include:

• United Nations (UN): The UN Security Council issues sanctions lists to maintain global peace and security, targeting individuals, organisations, and countries involved in terrorism, nuclear proliferation, or threats to international stability.

• Office of Foreign Assets Control (OFAC, US):  OFAC, part of the U.S. Department of the Treasury, enforces economic and trade sanctions. Its Specially Designated Nationals (SDN) list is one of the most widely used sanctions databases worldwide.

• European Union (EU): The EU publishes a consolidated list of persons, groups, and entities subject to restrictive measures, often reflecting international priorities while also implementing sanctions aligned with EU foreign and security policy.

• United Kingdom HM Treasury (HMT): Following Brexit, the UK maintains its own sanctions regime through the Office of Financial Sanctions Implementation (OFSI), publishing the UK sanctions list under the Sanctions and Anti-Money Laundering Act 2018.

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Sanction checks are not optional; they are a legal obligation under global anti-money laundering regulations. In today’s globalised economy, where money moves across borders in seconds, failing to spot a sanctioned entity in time can expose an organisation to risks that extend far beyond financial loss.

• Legal compliance: Avoid breaches of laws such as US, UK, and EU sanctions regimes.

• Reputational protection: Associations with sanctioned entities can cause reputational harm.

• Financial penalties: Non-compliance can lead to multi-million-dollar fines from regulators.

Sanctions screening is also a key element of AML regulations, ensuring institutions do not facilitate terrorist financing, proliferation financing, or money laundering.

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Sanctions checks are performed in the following ways:

1. Data collection: Gather names, dates of birth, addresses, and transaction details.

2. Screening: Compare against multiple sanctions lists using exact and fuzzy matching algorithms.

3. Match review: Investigate alerts to confirm or dismiss potential matches.

Manual vs. automated approaches

• Manual screening usually involves compliance staff checking names and other identifiers against sanctions lists directly on regulator websites or through spreadsheets. This approach may be suitable for very small firms with limited exposure, such as a boutique advisory firm with a handful of clients.  

However, it comes with significant drawbacks: it is time-consuming, prone to human error, and not scalable when customer or transaction volumes grow. Moreover, manual checks cannot provide real-time protection, which increases the risk of missing urgent sanctions designations.

• Automated screening by contrast, uses purpose-built software or APIs to compare customer and transaction data against multiple sanctions lists instantly. Advanced solutions apply fuzzy matching, transliteration support, and AI-driven analytics to reduce false positives and improve accuracy.  

Automated approaches are essential for banks, insurers, and fintech platforms that handle large transaction volumes and onboard customers at scale. They also offer an audit trail of every decision, ensuring regulatory expectations around governance and accountability are met.

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Sanctions risk is not static; it evolves as customers change behaviour, new lists are published, and global events reshape regulatory priorities. For this reason, sanction checks should not be a one-time activity but an ongoing control.

Institutions are expected to conduct checks at multiple stages of the customer and transaction lifecycle:

• At onboarding – Screening all new customers, counterparties, and vendors.

• Periodically – Rescreening existing relationships as lists update.

• On behavioural triggers – New payments to high-risk jurisdictions, new counterparties, or unusual transaction patterns. For example, a long-term corporate client begins sending funds to a high-risk region, prompting a fresh check.

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While sanction checks are essential, they are far from straightforward. Compliance teams often struggle with false positives (alerts that suggest a match but turn out to be incorrect). These can overwhelm teams, slow down decision-making, and increase operational costs.

False positives occur for several reasons:

• Name similarities (e.g., Amy Hawkenberry vs Aimee Hockenbury or Mohammed vs Muhammad)

• Spelling variations, translations, or use of aliases (For example, The name
  ‘Michaela’ has 135 different variations of spelling. Common other variations of the name include ‘Miceala’, ‘Mikeala’, and ‘Mikayla’, to name a few)

• Outdated or incomplete data, such as updated addresses, name changes, etc.

Strategies to reduce false positives include refining match algorithms, improving data quality, and using machine learning models to distinguish risk signals. For example, a compliance analyst can dismiss a false alert caused by a common name, after confirming the secondary scoring insights provided by the solution such as the individual’s birthdate and location not matching the sanctioned person.

5 ways to reduce false positives in screening

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Technology has transformed sanctions compliance from a slow, manual process into real-time, data-driven screening.  

• AI and machine learning: Detects complex evasion tactics, such as hidden ownership structures or trade-based sanctions circumvention.

• Automated list updates: Ensure screening tools reflect the latest designations immediately.

• Advanced analytics: Prioritises true risks, reducing noise and false positives.

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To stay compliant and reduce risk exposure, organisations must adopt a structured and proactive approach to sanctions screening. Best practices are not just about having the right technology but also about governance, training, and operational discipline.

• Regular list updates: Daily or near-real-time syncing with official sources, to ensure no sanctioned entities are missed.

• Multiple list sources: Covering UN, OFAC, EU, HMT, and jurisdiction-specific lists where applicable.

• Documented reviews: Maintain audit trails of every decision

• Staff training: Ensure teams understand sanctions obligations and escalation procedures

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