Sanctions, Watchlists and Name Screening

Introduction and context

Sanctions, watchlists and name-screening controls are central components of a bank’s financial-crime risk-management framework. They help prevent the institution from providing services to prohibited persons, entities, vessels, aircraft, governments and territories; identify politically exposed persons (PEPs); and detect customers or transactions associated with corruption, terrorism, organised crime or other serious misconduct.

These activities are closely related to anti-money laundering (AML) and counter-terrorist financing (CTF), but they are not identical. AML primarily addresses the prevention, detection and reporting of the concealment or movement of illicit proceeds. Sanctions compliance addresses restrictions imposed by states or international bodies for foreign-policy, national-security, human-rights, counter-terrorism or other public-policy purposes. A transaction may breach sanctions even when no money laundering is involved; conversely, suspicious activity may require an AML response even when no sanctions match exists.

Effective screening is therefore not simply a software exercise. It requires legally accurate list governance, reliable customer and payment data, risk-based rules, investigation expertise, documented decisions, escalation channels and senior accountability.

Learning objectives

By the end of this chapter, the reader should be able to:

• distinguish sanctions, PEP, adverse-media and AML screening;
• explain the role of United Nations, national and regional sanctions regimes;
• apply ownership and control principles when determining whether restrictions extend to an entity;
• evaluate name-screening alerts, aliases, transliteration and false positives;
• explain customer, payment and real-time screening processes;
• resolve alerts consistently and escalate potential true matches;
• assess the governance, ethical and technological risks of screening;
• design practical controls that are proportionate to institutional risk.

1. The architecture of screening controls

1.1 Sanctions

A sanction is a restrictive measure imposed by a competent authority. Measures may target:

• named individuals or legal entities;
• governments, ministries or state-owned enterprises;
• countries or territories;
• sectors such as finance, energy, defence or shipping;
• specified goods, services, technologies or activities;
• vessels and aircraft;
• funds, economic resources or transactions.

Sanctions may be comprehensive, restricting most dealings with a territory, or targeted, restricting dealings with identified persons or specified activities. They may prohibit asset dealings, financing, trade, investment, travel, export or import, or the provision of particular services. Their legal effect depends on the issuing jurisdiction, the institution’s location, the transaction’s nexus to that jurisdiction, and the precise wording of the measure.

A bank must not assume that a single global list captures every applicable obligation. Its legal and compliance functions must identify the regimes that apply to the bank, its branches, subsidiaries, correspondent relationships, currencies, payment systems, employees and customers.

1.2 Watchlists

“Watchlist” is a broad operational term. It can include:

1. Legal or regulatory sanctions lists, such as lists issued under United Nations or national authority.
2. Law-enforcement and lawfully shared intelligence lists, subject to applicable confidentiality and privacy rules.
3. PEP databases, which identify persons entrusted with prominent public functions and, in some systems, their family members and close associates.
4. Adverse-media databases, which collect credible reporting concerning allegations or findings of criminality, corruption, terrorism financing, fraud, trafficking or other serious misconduct.
5. Internal risk lists, such as persons subject to a prior exit decision or heightened monitoring.

These categories have different legal consequences. A sanctions hit may require immediate transaction blocking or rejection. A PEP result normally triggers enhanced due diligence rather than an automatic refusal. Adverse media is an investigative risk indicator, not proof of criminal conduct. Treating all watchlist results as legally equivalent creates both compliance and fairness risks.

1.3 Name screening

Name screening compares identifying data held by the bank with records in relevant lists. It may occur during:

• customer and beneficial-owner onboarding;
• periodic or event-driven review;
• account and product opening;
• payment initiation and processing;
• trade-finance, securities and custody transactions;
• changes to sanctions or PEP data;
• mergers, acquisitions and portfolio transfers.

Screening is a matching process, not a final legal conclusion. A system-generated similarity is an alert. A trained investigator must determine whether the available identifiers establish a plausible match, a false positive or an unresolved case requiring escalation.

2. Legal and institutional framework

The United Nations Security Council adopts measures under the UN Charter, including targeted financial sanctions associated with terrorism, proliferation and threats to international peace and security. Member states implement these measures through domestic law. National authorities may also impose autonomous sanctions that go beyond UN requirements. Regional regimes, such as those of the European Union, can create additional obligations for institutions within their jurisdiction.

A bank’s sanctions framework should therefore begin with a legal applicability analysis. The relevant questions include:

• Which laws bind the parent, branch and subsidiary?
• Does the bank process a currency or use a clearing system connected with another jurisdiction?
• Are employees, agents or service providers subject to additional rules?
• Does a correspondent bank impose contractual restrictions broader than local law?
• Are licences, exemptions or general authorisations available?
• What reporting, recordkeeping and blocking requirements apply?

The Financial Action Task Force (FATF) develops international standards for AML, CTF and proliferation-financing controls. FATF standards are not themselves a universal sanctions code, but they strongly influence customer due diligence, beneficial-ownership transparency, targeted financial sanctions implementation and risk-based supervision.

The Wolfsberg Group’s guidance is also influential in correspondent banking, payment transparency and sanctions-screening practice, although it is not legislation. Institutions should distinguish binding legal obligations from supervisory expectations, industry guidance and internal risk appetite.

3. Ownership, control and the extension of sanctions

3.1 Why ownership analysis matters

Screening only the customer’s registered name is inadequate. A non-listed company may be owned or controlled by a listed person and may therefore present a sanctions risk. Ownership can be direct or indirect, dispersed or concentrated, formal or practical.

A useful ownership model follows the chain from the customer to every natural or legal person with a relevant interest. The investigator should examine:

• direct shareholding and voting rights;
• indirect ownership through intermediate companies;
• agreements governing voting or appointment rights;
• nominee and trustee arrangements;
• board appointment or removal powers;
• contractual or financing control;
• influence over management or operations;
• joint ownership and coordinated action;
• changes made shortly before a transaction.

3.2 The “50 percent rule” and jurisdictional variation

Some sanctions authorities apply a rule under which an entity owned, directly or indirectly, 50% or more in aggregate by one or more blocked persons is treated as blocked even if the entity is not separately named. The calculation may aggregate ownership by multiple blocked persons. For example, if Person A owns 30% and Person B owns 25%, and both are blocked, their combined 55% may cause the entity to be treated as blocked under the applicable rule.

This is not a universal legal rule. Thresholds, attribution principles and concepts of control vary by jurisdiction and sanctions programme. A bank must apply the rule relevant to the transaction and document the legal basis used.

Ownership percentage alone may also be insufficient where the applicable law covers control. A person with 20% ownership might control an entity through voting agreements, board rights or practical dominance. Conversely, a large economic interest may not confer control in a particular legal structure. Screening teams must avoid mechanically applying a percentage without analysing the relevant legal test.

3.3 Beneficial ownership versus sanctions ownership

AML beneficial ownership and sanctions ownership are related but distinct inquiries. AML rules generally seek the natural person who ultimately owns or controls a customer for customer due diligence. Sanctions analysis asks whether a listed person owns or controls the customer in a way that triggers a restriction. The definitions, thresholds and evidential standards may differ.

A reliable case file should state separately:

• the AML beneficial owner identified under applicable law;
• the persons with sanctions-relevant ownership or control;
• the source of ownership information;
• the date on which it was verified;
• the legal rule applied;
• any unresolved ownership uncertainty.

4. Screening data and matching challenges

4.1 Data quality

Screening performance depends heavily on the quality of customer and payment data. Important fields include full legal name, aliases, former names, date and place of birth, nationality, address, registration number, tax identifier, passport or national identity number, vessel identifiers and ownership information.

Data should be collected in original form where possible, while retaining transliterations and standardised search forms. Missing dates of birth, abbreviated names, incomplete addresses and inconsistent corporate identifiers increase both false positives and false negatives.

4.2 Names, aliases and transliteration

Name matching is difficult because of:

• different word order conventions;
• family-name and patronymic systems;
• married and former names;
• initials and abbreviations;
• spelling variations;
• transliteration between alphabets;
• diacritics and punctuation;
• typographical errors;
• local naming conventions;
• deliberate concealment or identity fraud.

A screening engine may normalise case, punctuation and diacritics, and use phonetic or fuzzy matching. Such techniques improve recall—the ability to identify genuine matches—but may reduce precision by creating more alerts. No algorithm can replace reliable identifiers and human analysis.

4.3 False positives and false negatives

A false positive occurs when a system generates an alert for a person or entity that is not the listed subject. A false negative occurs when a genuine listed subject is not detected. The two errors have different consequences: excessive false positives create delay, cost and unfair customer treatment, while false negatives may expose the bank to legal, financial and reputational harm.

An institution should not evaluate a screening system solely by the number of alerts closed. It should examine the quality of matching, the reasons for closure, missed-match testing, data completeness, time to disposition, escalation quality and outcomes from internal audit or regulatory review.

5. Alert investigation and disposition

A disciplined investigation follows a documented sequence.

Step 1: Preserve the alert context

Record the customer or transaction, list record, screening date, data fields matched, system rule, analyst, timestamps and any action taken. The original alert should remain reconstructable after later changes.

Step 2: Compare identifiers

Compare full name, aliases, date of birth, nationality, address, registration number, passport details, industry, ownership and known associates. A name-only similarity is usually insufficient for a positive determination.

Step 3: Establish the legal and risk context

Determine whether the list is legally binding, advisory or internally generated. Identify the applicable jurisdiction and whether the activity involves a blocked currency, correspondent, territory, sector or service. Check for exemptions, licences or authorised dealings.

Step 4: Obtain reliable evidence

Use authoritative corporate records, government identification, customer documents, reputable commercial databases and credible open-source information. Evidence should be proportionate to the risk and sufficiently reliable to support the decision.

Step 5: Decide or escalate

Possible outcomes include:

• false positive: identifiers demonstrate that the subject is different;
• possible match: evidence is incomplete and further investigation is required;
• true match or prohibited activity: the bank applies the required hold, block, reject, freeze, exit or report action;
• no-match but elevated risk: no sanctions match exists, but PEP, adverse-media or AML concerns require enhanced due diligence;
• unresolved: the matter is escalated to sanctions legal counsel, the MLRO, a sanctions officer or senior management under the escalation policy.

The analyst must not close an alert merely because the customer is important, the payment is urgent or the relationship manager provides an unsupported verbal assurance.

Step 6: Communicate and document

Operational teams need clear instructions: whether to release, hold, reject, block or seek further information. The rationale, evidence, decision-maker and review date should be recorded. Where law requires, reports must be made to the competent authority, and tipping-off restrictions must be respected.

6. Customer, payment and transaction screening

6.1 Customer screening

Customer screening is usually performed at onboarding and refreshed when lists change or customer information changes. It should cover the customer, beneficial owners, directors, authorised signatories, trustees, settlors, protectors, beneficiaries, guarantors and relevant counterparties.

Risk-based refresh frequencies may be supplemented by event-driven review, such as a change in ownership, unusual activity, adverse media, a new country exposure or a regulatory designation.

6.2 Payment screening

Payment screening may examine the ordering customer, beneficiary, banks, intermediaries, originator and beneficiary information, free-text fields, vessel or aircraft details, goods and locations. Screening can occur at initiation, before release, during clearing or at post-transaction review, depending on the payment architecture and risk.

A payment alert requires careful handling because unnecessary repair or rejection can disrupt legitimate commerce, while release of a prohibited payment can create serious liability. The bank should have documented service-level expectations, authority to place a payment on hold, procedures for repairing incomplete data, and a clear escalation route.

Payment transparency is also important. Removing or altering information to avoid a screening result is a serious control failure and may itself indicate evasion. Screening teams should distinguish a genuine data correction from deliberate stripping or manipulation.

6.3 Trade and securities screening

Trade finance requires attention to goods, vessels, ports, shipping parties, insurers, banks, end users and documents. Securities and custody activities may involve issuers, issuers’ owners, funds, brokers, exchanges, securities identifiers and corporate actions. Screening must be designed for the product rather than copied from retail customer screening.

7. PEP and adverse-media screening

7.1 Politically exposed persons

A PEP is an individual who is or has been entrusted with a prominent public function. Examples may include senior politicians, senior government officials, judges, military leaders, senior executives of state-owned enterprises and senior officials of international organisations, depending on applicable law.

PEP status is not evidence of criminality. It indicates higher exposure to bribery, corruption and misuse of public position. Controls may include senior-management approval, establishing source of wealth and source of funds, enhanced transaction monitoring and enhanced ongoing review. Family members and close associates may also require treatment under local law.

PEP classification should be time-sensitive and proportionate. A former official may remain relevant after leaving office, but automatic permanent treatment without risk analysis is poor practice. The bank should record the basis for classification and the rationale for continuation or removal.

7.2 Adverse media

Adverse-media screening should assess the credibility, recency, specificity and relevance of information. A credible court judgment differs from an unverified online allegation. Relevant questions include:

• Is the source identifiable and reputable?
• Does the report concern the same person or entity?
• Is the conduct relevant to financial-crime risk?
• Was there a charge, conviction, regulatory finding or only an allegation?
• Is the information current, disputed or demonstrably false?
• What is the customer’s explanation and supporting evidence?

The bank must balance risk management with privacy, reputation and procedural fairness. It should not deny services solely because of sensational or unreliable reporting.

8. Governance, technology and artificial intelligence

A sound screening framework has clear ownership. The board approves risk appetite; senior management provides resources; the compliance function sets policy; operations execute controls; technology manages systems; internal audit independently tests effectiveness; and legal advisers interpret applicable restrictions.

Important governance controls include:

• an inventory of applicable lists and data providers;
• documented list-ingestion and quality checks;
• version control and change management;
• calibrated matching thresholds;
• role-based access and segregation of duties;
• analyst training and quality assurance;
• management information and key-risk indicators;
• independent testing and scenario-based validation;
• business-continuity and manual fallback arrangements;
• retention of evidence and decision records.

Artificial intelligence and machine learning can assist with entity resolution, alert prioritisation, adverse-media classification and analyst workflow. However, models may reproduce biased data, obscure reasoning, over-rely on weak sources or change performance as names and typologies evolve. An AI-generated risk score is not a legal determination. Human oversight, explainability, validation, privacy protection, model monitoring and override governance are essential.

Useful performance measures include alert volumes, average investigation time, aged cases, repeat alerts, confirmed matches, missed-match findings, data-completeness rates and quality-assurance error rates. These are management indicators, not universally valid benchmarks. A low alert count can indicate effective tuning—or a dangerously insensitive system.

9. Applied case: Northbridge Bank and an indirect ownership alert

The following is an illustrative case, not a description of an actual institution.

Background

Northbridge Bank receives a large trade-finance payment for Meridian Components Ltd, a company incorporated in Country X. Meridian is not named on the bank’s sanctions list. The payment involves a correspondent in another jurisdiction and a currency subject to that jurisdiction’s sanctions rules.

The screening engine produces a possible match against a listed individual, Karim R., based on an indirect ownership record. The customer relationship manager states that Karim is only a minority investor and asks operations to release the payment immediately because the shipment is time-sensitive.

Problem

The alert cannot be resolved by comparing Meridian’s name with the list. The bank must determine whether Karim owns or controls Meridian, whether the relevant sanctions rule aggregates ownership, whether the payment involves additional restricted parties or goods, and whether a licence or exemption applies.

Analysis

The investigator obtains the latest corporate register, shareholder agreement, board records, beneficial-ownership declarations and reliable commercial intelligence. The evidence shows:

• an intermediate holding company owns 60% of Meridian;
• Karim owns 60% of that intermediate company;
• Karim has the right to appoint three of five Meridian directors under a shareholder agreement;
• another listed person owns 10% of the intermediate company;
• the goods are subject to an export-control review.

The investigator does not treat the customer’s “minority investor” description as decisive. The indirect chain indicates a substantial economic interest and possible control. The second listed person may also need to be aggregated under the applicable rule. The currency and correspondent create an additional jurisdictional nexus.

Approach and solution

Northbridge places the payment on hold under its documented escalation procedure. Sanctions counsel assesses the relevant law, the ownership rule, the goods and any available authorisation. The trade-finance team verifies the end user, route and shipping parties. The relationship manager is informed that release requires compliance clearance, not commercial approval.

The case file records the ownership calculation, control rights, source documents, list versions, legal analysis, decisions and communications. If the transaction is prohibited, the bank follows the applicable blocking, rejection and reporting requirements. If legally permissible under a licence, it documents the licence conditions and establishes controls to ensure that the transaction stays within them.

Outcome

The payment is not released while the legal assessment is pending. The bank identifies a control-rights issue that would have been missed by a simple name screen, updates Meridian’s customer risk profile, links the intermediate company and relevant persons in its screening system, and reviews other customers connected to the same ownership network.

Learning points

1. A non-listed customer can create sanctions risk through ownership or control.
2. Ownership analysis must include indirect interests and contractual rights.
3. A relationship manager’s commercial urgency cannot override a sanctions hold.
4. Payment screening should examine parties, goods, routes and jurisdictional links.
5. The final decision must be legally grounded and reproducible from the case record.

10. Challenges, limitations and ethical issues

Screening systems face an inherent tension between sensitivity and efficiency. Broad matching settings may create thousands of alerts and encourage superficial closure. Narrow settings may miss transliterated names, aliases and indirect relationships. Periodic tuning should use representative test data, confirmed cases, near misses and changes in list content.

Privacy is another challenge. Banks process identity, location, political-role and reputational data. Collection and sharing should be lawful, necessary, proportionate, secure and limited to authorised purposes. Customers should receive appropriate information about processing, subject to lawful restrictions on disclosure.

Fairness also matters. A person should not be treated as a sanctions subject merely because a common name resembles a listed name. Analysts should use objective identifiers and record uncertainty. Escalation decisions should not be influenced by nationality, ethnicity, religion or political opinion except where legally relevant facts establish risk.

Cross-border groups must manage inconsistent laws. One jurisdiction may require blocking, another may permit the transaction, and a third may restrict disclosure of customer information. Group policies should set a minimum standard while allowing local legal advice and documented deviations.

11. Best-practice operating model

A mature bank should:

• map legal obligations to products, entities and jurisdictions;
• maintain authoritative, timely and tested list feeds;
• collect complete identity and ownership information;
• screen customers, related parties and transactions at appropriate points;
• use risk-based matching and differentiated workflows for sanctions, PEP and adverse media;
• apply ownership and control analysis rather than name matching alone;
• preserve alerts, evidence, rationale and approvals;
• define hold, block, reject, report and release authorities;
• test for false negatives as well as false positives;
• train analysts in legal interpretation and cultural naming conventions;
• monitor vendors, models and data quality;
• provide independent assurance and board-level reporting;
• review controls after regulatory changes, system incidents and near misses.

The central principle is disciplined proportionality: strong enough controls to prevent prohibited activity, precise enough investigation to avoid unjustified restrictions, and transparent enough governance to demonstrate that decisions were lawful and effective.

Chapter Summary

Sanctions, watchlists and name screening form a specialised but interconnected part of banking financial-crime control. Sanctions impose legal restrictions that vary by authority, jurisdiction, programme and transaction context. Watchlists include sanctions lists, PEP data, adverse-media sources and internal risk records, but these categories do not have identical legal consequences.

Name screening produces alerts rather than final determinations. Reliable resolution requires complete identity data, aliases, transliteration handling, ownership and control analysis, authoritative evidence and documented escalation. Indirect ownership and control can extend sanctions risk to an entity not separately named on a list, although the applicable rule must always be verified.

Customer screening, payment screening and trade screening must be designed around the risks of each product. PEP status normally requires enhanced due diligence, not automatic rejection, while adverse media must be assessed for credibility and relevance. Technology and AI can improve efficiency but require validation, explainability, privacy safeguards and human accountability.

Finally, sanctions compliance is distinct from AML. A sanctions breach may occur without money laundering, and an AML concern may exist without a sanctions match. Effective institutions integrate the controls while preserving their separate legal tests, decision processes and reporting obligations.

Key Terms

Sanctions: Restrictive measures imposed by a competent authority against persons, entities, territories, sectors, goods or activities.

Targeted financial sanctions: Restrictions directed at identified persons or entities, often involving freezing or prohibiting dealings with assets.

Watchlist: A database or list used to identify legally restricted or higher-risk persons, entities or activities.

Name screening: Comparison of customer, counterparty or payment data with relevant list records.

PEP: A person entrusted with a prominent public function.

Family member: A relative of a PEP treated as relevant under applicable law or policy.

Close associate: A person closely connected to a PEP through business, ownership or social relationships.

Adverse media: Credible negative information relevant to financial-crime or integrity risk.

False positive: An alert concerning a person or entity different from the listed subject.

False negative: Failure to identify a genuine listed person, entity or activity.

Alias: An alternative name used by or associated with a person or entity.

Transliteration: Conversion of a name from one writing system or alphabet into another.

Beneficial owner: The natural person who ultimately owns or controls a customer under applicable AML rules.

Ownership and control: Economic ownership, voting rights or practical authority over an entity.

Indirect ownership: Ownership held through one or more intermediate persons or entities.

Payment screening: Screening parties and relevant information in a payment before or during processing.

Sanctions evasion: Conduct intended to circumvent or conceal a prohibited person, transaction, asset or activity.

Enhanced due diligence: Additional measures applied where risk is higher than ordinary customer risk.

Alert disposition: The documented decision to close, escalate, hold, block, reject or report an alert.

Tipping off: Improper disclosure that may prejudice an investigation or regulatory report.

Review Questions

Short Answer Questions

1. Why is sanctions compliance not the same as AML compliance?
2. What is the difference between a watchlist and a sanctions list?
3. Identify four data fields that help resolve a name-screening alert.
4. Why can a PEP result not automatically be treated as proof of criminality?
5. What is a false negative in name screening?

Long Answer Questions

1. Explain the legal and operational factors a bank should consider when determining which sanctions regimes apply to it.
2. Discuss how indirect ownership and control can create sanctions risk for a non-listed company.
3. Describe a complete process for investigating and documenting a potential sanctions match.
4. Compare customer screening, payment screening and adverse-media screening in terms of purpose, timing and evidence.
5. Evaluate the benefits and risks of using artificial intelligence in sanctions and watchlist screening.

Analytical / Application Questions

1. A customer’s name closely resembles a listed person’s name, but the date of birth, nationality and address differ. What further evidence should the investigator obtain, and what would justify closing the alert as a false positive?
2. Two listed persons own 30% and 25% respectively of an unlisted company, while a third person controls its board through a voting agreement. Analyse the issues the bank must resolve before processing a payment.
3. A relationship manager asks for immediate release of a payment held for a possible sanctions match because the customer is commercially important. Design an escalation and governance response that protects both compliance integrity and legitimate customer service.

Multiple Choice Questions with Answers

Question 1

Which statement best distinguishes sanctions compliance from AML compliance?

A. Sanctions compliance applies only to cash transactions.

B. AML compliance concerns concealment of illicit proceeds, while sanctions compliance concerns legally imposed restrictions, although the controls may overlap.

C. AML compliance is voluntary, while sanctions compliance is always international.

D. Sanctions compliance applies only after a suspicious transaction report is filed.

Correct Answer: B. AML compliance concerns concealment of illicit proceeds, while sanctions compliance concerns legally imposed restrictions, although the controls may overlap.

Question 2

What is the primary significance of a PEP classification?

A. It proves that the person has committed corruption.

B. It requires automatic account closure.

C. It indicates a need for risk-based enhanced due diligence under applicable rules.

D. It establishes that all transactions are prohibited.

Correct Answer: C. It indicates a need for risk-based enhanced due diligence under applicable rules.

Question 3

Which information is most useful for distinguishing two people with similar names?

A. The colour of the customer’s account statement

B. Date of birth, nationality and address

C. The customer’s preferred banking channel alone

D. The amount of the proposed transaction alone

Correct Answer: B. Date of birth, nationality and address

Question 4

Why is indirect ownership relevant to sanctions analysis?

A. It can cause a non-listed entity to be covered by a rule applying to ownership or control by listed persons.

B. It eliminates the need to identify beneficial owners.

C. It proves that every subsidiary is prohibited.

D. It applies only to personal accounts.

Correct Answer: A. It can cause a non-listed entity to be covered by a rule applying to ownership or control by listed persons.

Question 5

Which is the most appropriate first response to a possible true sanctions match in a payment?

A. Release the payment to avoid customer inconvenience.

B. Delete the alert and rescreen later.

C. Place the payment on hold according to policy and escalate for legal and compliance assessment.

D. Ask the customer to change the beneficiary name.

Correct Answer: C. Place the payment on hold according to policy and escalate for legal and compliance assessment.

Question 6

What is a false positive?

A. A genuine listed party that was missed by the system

B. An alert involving a different person or entity from the listed subject

C. A payment that is legally blocked

D. A list record that has expired

Correct Answer: B. An alert involving a different person or entity from the listed subject

Question 7

Which statement about adverse media is most accurate?

A. Every online allegation proves financial crime.

B. Adverse media should be assessed for source credibility, identity match, relevance and recency.

C. Adverse media has exactly the same legal effect as a sanctions designation.

D. Adverse media should never affect customer risk assessment.

Correct Answer: B. Adverse media should be assessed for source credibility, identity match, relevance and recency.

Question 8

What should a screening case file primarily demonstrate?

A. Only the final decision and no supporting evidence

B. The alert context, identifiers considered, evidence, legal reasoning and approval or escalation

C. The relationship manager’s commercial opinion

D. The number of alerts generated by the vendor worldwide

Correct Answer: B. The alert context, identifiers considered, evidence, legal reasoning and approval or escalation

Question 9

Which practice creates a significant payment-screening control risk?

A. Retaining relevant originator and beneficiary information

B. Escalating unresolved alerts

C. Removing payment information to avoid a screening result

D. Testing list updates before production use

Correct Answer: C. Removing payment information to avoid a screening result

Question 10

Why should AI-generated screening scores not be treated as final legal decisions?

A. AI cannot process any names.

B. A score may be affected by data limitations or model bias and may not explain the applicable legal test.

C. AI is prohibited in all banking functions.

D. Human investigators are never needed for sanctions cases.

Correct Answer: B. A score may be affected by data limitations or model bias and may not explain the applicable legal test.