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Watchlist Screening: Understanding Effective AML Compliance

Watchlist Screening: Understanding Effective AML Compliance

The United Nations estimates that criminals worldwide launder between $800 billion and $2 trillion each year, representing anywhere from 2% to 5% of the world economy.[1] The money stems from, and funds, unspeakable crimes: terrorism, slavery, weapons trafficking, child exploitation, and the drug trade among them. Legislators believe that when the flow of money stops, instances of these crimes plummet — along with instances of fraud and tax evasion. That’s why nations worldwide have implemented stringent anti-money laundering (AML) laws.

Specific mandates vary from country to country, but for banks and other types of financial institutions (FIs), watchlist screening — or the act of comparing customer names against names appearing on watchlists and sanctions lists — is the most significant component of AML compliance.

The following FAQ provides an overview of watchlist screening: what it is, how it works, why it’s important, and the challenges FIs face in optimizing screening processes.

What is watchlist screening in AML compliance?

Watchlist screening in AML compliance is the act of comparing a customer’s name and identity against government-issued, internal, and commercial lists of prohibited or high-risk entities. Watchlist screening is undertaken by FIs to comply with AML mandates: to ensure they reject business from sanctioned individuals, corporations, or nations. They must also take special care when working with “restricted” or “at risk” entities. 

Watchlist screening is a significant part of broader customer onboarding processes that include identity verification and risk scoring.

What risks does watchlist screening help prevent?

Watchlist screening solutions help prevent money laundering, which in turn minimizes the risk of crimes such as terrorism, slavery, weapons trafficking, child exploitation, and the drug trade.

How does watchlist screening protect against sanctions violations?

Sanctions screening is a part of watchlist screening. Sanctions violations occur when an FI does business with a person, corporation, or nation appearing on applicable sanctions lists. Optimized watchlist and sanctions screening help protect FIs from the fines and potential criminal charges that can result from the failure to meet AML mandates.

What is the difference between sanctions screening and watchlist screening?

Sanctions screening is a critical component of watchlist screening. Sanctions screening compares customers to government-issued lists of persons, organizations, and nations with whom banks are legally prohibited from doing business. Watchlist screening is a broader process that screens customers against other lists and databases naming entities that may present a risk of money laundering or other financial crime. These lists include Politically Exposed Persons (PEP) lists, bank-internal lists of previously terminated clients, suspicious activity reports (SARs), adverse media databases, and fraud/crime databases. While banks are not prohibited from doing business with entities appearing on these watchlists, the relationship typically requires enhanced due diligence. (See How does watchlist screening support enhanced due diligence?)

How does watchlist screening reduce financial crime risk?

Watchlist screening helps reduce the risk of financial crimes by keeping those likely to launder money out of nations’ financial systems.

When should watchlist screening be performed?

At customer onboarding and periodically thereafter.

Is watchlist screening part of KYC or AML?

“AML” or “anti-money laundering” is a phrase used to describe a broad array of laws worldwide with which financial institutions must comply. “KYC” or “Know Your Customer” is an umbrella term used for the processes undertaken by FIs to comply with AML laws. Watchlist screening is therefore a part of KYC.

Who needs watchlist screening and why?

Almost universally, AML mandates require watchlist screening by banks, other financial institutions, and gambling operations. Watchlist screening is required of other industries on a country-by-country or region-by-region basis.

What industries are most affected by watchlist screening requirements?

Among the industries most affected by watchlist screening requirements are financial services (including cryptocurrency and digital assets), travel and transportation, energy and utilities, mining, telecom, trade and supply chain, government and defense, legal and professional services, healthcare and life sciences, and ecommerce.

Why do these industries need to screen against watchlists?

Typically, governments impose screening requirements on businesses and industries whose operations affect financial systems, national infrastructures, or public health and safety. The goal is to prevent wrongdoers from accessing these systems.

Why is watchlist screening required for regulated businesses?

Watchlist screening is required for regulated businesses because, beyond money laundering, there are a host of ways for wrongdoers to harm financial systems, national infrastructures, or public health and safety. Watchlist screening is sometimes required in the shipping industry, for example, because governments fear that criminals may use freight forwarding services for the cross-border movement of weapons, drugs, and the type of chemicals that can be used in acts of terrorism. Telecom industries, meanwhile, are often charged with installing the intercept systems needed for the lawful monitoring of certain communications. A malicious vendor working with a telecom company could potentially breach these systems and use them for espionage.

What types of watchlists are used for screening?

Sanctions lists are the most significant AML watchlists. Prominent sanctions lists include the U.S. Office of Foreign Assets Control’s Specially Designated Nationals and Blocked Persons (SDN) List, the European Union’s Consolidated Financial Sanctions List, the United Nations Security Council’s Sanctions Committee lists, as well as national and regional lists in Asia and elsewhere. Regulatory agencies worldwide also expect banks to scan against adverse media databases and PEP lists. PEP lists, available from third-party vendors, name persons who hold the type of prominent public positions that put them at a greater risk of bribery, corruption, or other financial crimes. Their close associates and family members are also often listed.

How does watchlist screening work?

Processes vary across FIs and countries. Broadly speaking, AML investigators and other bank personnel use name-match and entity-resolution technology to compare customer names against the lists discussed in What types of watchlists are used for screening? These screenings are conducted at customer onboarding, and periodically thereafter throughout the life of the relationship.

Why do banks find watchlist screening procedures so challenging?

Older, fragmented AML compliance software used by many FIs make screenings difficult and labor intensive. Challenges include finding insight in siloed data sources. AML/KYC systems pull from multiple sanctions list and watchlists. Data among these lists may be inconsistent, outdated, or duplicated — a situation that leads to both missed matches and the need for manual investigation.

Fragmentation continues among watchlist screening technologies themselves. These systems may not talk to each other, a state that obscures insight — notably in the field of corporate ultimate beneficial ownership. Many existing technologies are also too slow to process huge volumes of names, delaying both customer onboarding and cross-border payments.

Name matching is among the most challenging aspects of watchlist screening.

What is name matching? Why is it so hard?

Name matching is the process of comparing customer names against names appearing on sanctions lists and other watchlists and databases. Ideally, name matching should be an automated, speedy, and accurate process.

However, difficulties arise because of the preponderance of similar names appearing across a broad array of languages and scripts. There are more than 8 billion people on the planet. A lot of them are named John Smith. Is the John Andrew Smith, self-identified teacher opening a checking account at your bank, the same person as John A. Smith, suspected terrorist? Or as Smith, John A., known drug runner? Without additional identifiers (home address, date of birth, social security number and more) determinations are hard to make.

Complications deepen when you consider that name variations occur across scripts and languages. Is “your” John Andrew Smith the same person as a suspected Yakuza member John Andrew Smith, whose name is rendered in phonetic Kanji as 譲恩 安土琉 寿美須? Or is he a member of Italy’s racketeering syndicate 'Ndrangheta, going by the Italian translation of John Andrew Smith: Giovanni Andrea Ferraro?

Existing technologies miss many of these matches. Far more often, they return false positives — linking every John Andrew Smith to a hypothetical John Andrew Smith appearing on the SDN list or other watchlist. And each time a system suspects a match, it alerts AML analysts. Those analysts must then spend investigative time resolving that alert.

How often do these mismatches occur?

A lot. Industry estimates put the false positive alert rate at more than 90%.[2]

What is a false positive in watchlist screening?

A false positive is a mismatch of a client name to the same or similar name appearing on a watchlist.

How should compliance teams handle watchlist screening alerts?

Compliance teams must manually investigate each alert to see if it is a true match or a false positive.

What happens if a business fails watchlist screening requirements?

Banks that fail to comply with watchlist screening requirements violate AML laws, risking heavy fines and even criminal prosecution of bank leadership. For example, in late 2025 The Department of the Treasury’s Financial Crimes Enforcement Network (FinCEN) assessed a $3.5 million penalty against Paxful, Inc., a peer-to-peer cryptocurrency exchange. The fine was levied after FinCen found that Paxful’s transfers involved sanctioned countries and companies.[3] At around the same time, a federal grand jury indicted the former president and CEO of an Oklahoma bank for both fraud and failure to implement an adequate AML program.[4]

How does watchlist screening support AML and KYC compliance?

Watchlist screening is a key component of AML/KYC compliance.

How does watchlist screening support enhanced due diligence?

“Watchlist screening” is a fundamental component of KYC processes for both “customer due diligence” (CDD) and “enhanced due diligence” (EDD).

CDD screenings apply to every customer at onboarding and periodically thereafter.

But FIs recognize that some clients present more of a risk than others. A non-sanctioned individual may be the daughter of a PEP. A corporate client may have an opaque ownership structure. These types of clients require EDD. EDD enhances CDD with additional watch list screenings and, typically, adverse media monitoring. Clients requiring EDD are also typically subject to more frequent transaction monitoring and shorter client-review cycles.

Why Babel Street?

Babel Street is a global leader in mission-grade risk intelligence. The Babel Street Risk Intelligence Platform helps FIs worldwide more easily and cost effectively comply with regulatory mandates. In the field of name matching, our AI-powered AML compliance software dramatically reduces false positives and the concurrent need for manual investigation while speeding customer onboarding and easing cross-border transfers. It enables automated, accurate, multilingual name matching across 25 languages and a variety of scripts — including Arabic, Russian, Chinese ideographs, and Japanese Kanji.

Similar efficiencies are obtained through our entity resolution and adverse media screening capabilities. To resolve entities, Babel Street finds records in different data sets that refer to the same entity, then links these pieces of data to each other and to real-world people, places, and organizations. This capability automates previously manual processes, improving insight and saving significant investigative time.

For customers requiring adverse media monitoring, Babel Street queries reputable news sources around the globe (along with government records and social media) for negative mentions of clients or prospects. Our always-on monitoring covers data sources published in more than 200 languages, quickly surfacing adverse information and translating results into your language of choice.

Finally, the nature of money laundering means that it is typically a multi-person crime. Babel Street can help rapidly map key relationships within social media networks, uncovering previously unknown or hidden relationships, and precisely identifying those who wield the most influence. Once influencers are identified, Babel Street empowers FIs to delve deeper into those influencers’ online profiles and activities — providing valuable AML/KYC insight

Endnotes

1. United Nations, “Improving regional investigations on money laundering and asset recovery,” accessed March 2026, https://www.unodc.org/roca/en/NEWS/news_2024/november/improving-regional-investigations-on-money-laundering-and-asset-recovery.html

2. Thompson Reuters, “False positives and false negatives: How best to leverage adverse media searches in the battle against financial crime,” accessed March 2026, https://legal.thomsonreuters.com/en/insights/white-papers/white-paper-false-positives-and-false-negatives

3. United States of America Financial Crimes Enforcement Network/Department of the Treasury, “FinCen Paxful Consent Order,” accessed March 2026, https://www.fincen.gov/system/files/2025-12/PaxfulConsentOrder.pdf

4. U.S. Department of Justice, “Former President of File Oklahoma Bank Indicted for Bank Fraud,” December 2025, https://www.justice.gov/opa/pr/former-president-failed-oklahoma-bank-indicted-bank

Disclaimer

All names, companies, and incidents portrayed in this document are fictitious. No identification with actual persons (living or deceased), places, companies, and products are intended or should be inferred.