Transaction Monitoring Program Design
5 minutes
5 Questions
Transaction Monitoring (TM) Program Design is a core pillar of an Anti-Financial Crime (AFC) program and a key focus area for CAMS practitioners working in governance and risk management. Its purpose is to detect unusual or suspicious activity that may indicate money laundering, terrorist financing, sanctions evasion, fraud, or other financial crimes, enabling timely investigation and regulatory reporting (e.g., SARs/STRs). Effective design begins with a risk-based approach. The institution's enterprise-wide risk assessment (EWRA) identifies inherent risks across customers, products, services, geographies, and delivery channels. TM scenarios and typologies should map directly to these identified risks so that monitoring coverage is defensible and proportionate—higher-risk segments warrant more intensive or lower-threshold monitoring. Key design components include: (1) Data governance—ensuring complete, accurate, and timely data feeds from source systems, with data lineage and reconciliation controls, since poor data quality undermines detection; (2) Scenario and rule development—selecting rules (e.g., structuring, rapid movement of funds, unusual cash activity, high-risk jurisdiction flows) and, increasingly, behavioral or machine-learning models, each supported by documented rationale; (3) Threshold setting and segmentation—calibrating parameters by customer segment to balance detection effectiveness against false positives, supported by statistical analysis such as above-the-line/below-the-line testing; (4) Alert management—defining workflows, prioritization, escalation paths, investigation standards, and documentation requirements; and (5) Model risk management—independent validation, periodic tuning, change management, and ongoing performance monitoring consistent with regulatory expectations such as OCC 2011-12/SR 11-7. Governance is essential. Senior management and the board should approve the TM framework, receive management information (alert volumes, SAR conversion rates, backlogs, tuning outcomes), and ensure adequate staffing and technology. Policies and procedures must be documented, roles clearly assigned across the three lines of defense, and the program subjected to independent audit. Ultimately, a well-designed TM program is dynamic—continuously refined in response to emerging typologies, regulatory feedback, business changes, and lessons learned—demonstrating to regulators that the institution understands and actively manages its financial crime risk.
Transaction Monitoring Program Design: A Complete CAMS Study Guide
Why Transaction Monitoring Program Design Matters
Transaction monitoring (TM) is the engine room of an anti-financial crime (AFC) program. Customer due diligence tells you who your customer is and what you expect them to do; transaction monitoring tells you whether they are actually behaving that way. Without a well-designed monitoring program, a financial institution cannot credibly detect suspicious activity, cannot file timely Suspicious Activity Reports (SARs) or Suspicious Transaction Reports (STRs), and cannot demonstrate to regulators that its risk-based approach is more than words on paper.
Regulators worldwide treat TM failures as evidence of systemic AML weakness. Many of the largest enforcement actions in history (consent orders, deferred prosecution agreements and multi-billion-dollar penalties) cite poorly calibrated scenarios, missing data feeds, unmanaged alert backlogs, undocumented threshold changes or a monitoring system that was never aligned to the institution's own risk assessment. For the CAMS exam, this topic sits within AFC Program Governance and Risk Management because the examiners want you to understand monitoring as a governed, risk-based, documented and continuously improved process, not simply as a piece of software.
What Transaction Monitoring Program Design Is
Transaction monitoring program design is the structured process by which an institution decides what activity it will watch, how it will watch it, who will review the results, and how it will prove the system works. It covers the full lifecycle from data capture through alert generation, investigation, escalation, reporting and feedback. A sound design is:
• Risk-based – driven by the enterprise-wide AML risk assessment (customers, products, services, channels, geographies).
• Data-driven – built on complete, accurate and timely data from all relevant systems.
• Typology-informed – scenarios reflect known money laundering, terrorist financing, fraud and sanctions-evasion patterns relevant to the institution.
• Governed – changes to rules, thresholds and models are approved, documented and auditable.
• Tested and validated – performance is measured, tuned and independently reviewed.
• Resourced – staffed with trained investigators and supported by clear procedures and escalation paths.
Regulatory anchors you should recognize include FATF Recommendation 10 (ongoing due diligence and scrutiny of transactions), Recommendation 20 (reporting of suspicious transactions), the US Bank Secrecy Act and FinCEN requirements for a reasonably designed program with internal controls and independent testing, the EU Anti-Money Laundering Directives requiring ongoing monitoring, and industry guidance such as the Wolfsberg Group statements on monitoring and the use of technology. The common thread: monitoring must be appropriate to the institution's size, complexity and risk profile.
How Transaction Monitoring Program Design Works
1. Start with the risk assessment. The enterprise-wide risk assessment identifies inherent risks and residual risks after controls. TM scenarios should map back to those risks. If the risk assessment identifies correspondent banking, cash-intensive businesses, high-risk jurisdictions or virtual asset customers as elevated risks, the monitoring program must contain scenarios that specifically address them. A gap between identified risks and monitoring coverage is a classic exam scenario and a classic regulatory finding.
2. Define coverage and typologies. Designers inventory the products, channels and customer segments in scope and select typologies to detect, such as structuring below reporting thresholds, rapid movement of funds (pass-through or funnel accounts), unusual cash activity, round-dollar wire transfers, activity inconsistent with stated business, dormant account reactivation, high-risk jurisdiction flows, trade-based money laundering indicators, and patterns associated with human trafficking, elder abuse or terrorist financing. Coverage assessments compare the list of relevant typologies against implemented scenarios to identify gaps.
3. Secure data integrity. The system is only as good as its inputs. Design work includes data lineage mapping (which source systems feed the TM engine), completeness checks (are all accounts, all transaction types and all legal entities captured?), accuracy checks (are country codes, customer types and transaction codes correct?), and timeliness (is data loaded daily or in real time where needed?). Reconciliation controls confirm that transactions in the core system match transactions received by the monitoring system. Missing wire fields, unmapped product codes or excluded subsidiaries are frequent root causes of monitoring failure.
4. Choose the detection approach.
• Rules-based (scenario) monitoring uses predefined logic and thresholds (for example, aggregate cash deposits over X within Y days). It is transparent and explainable but can generate high false positives and may miss novel patterns.
• Behavioral or profile-based monitoring compares current activity against the customer's own historical baseline or peer group, flagging deviations.
• Statistical and machine learning models score risk, prioritize alerts or detect anomalies. They can improve efficiency but demand stronger model governance, explainability and validation.
• Real-time versus batch: payments screening and some fraud controls run in real time; most AML monitoring runs in post-transaction batch cycles.
Most mature programs blend these approaches. The exam expects you to know the trade-offs rather than to declare one approach always superior.
5. Segment and set thresholds. Customers are grouped into segments with similar expected behavior (retail, small business, high-net-worth, correspondent banks, money services businesses, etc.). Thresholds are set per segment so a legitimate large corporate does not trigger the same cash rule as a student account. Threshold setting uses historical data analysis, statistical distributions and sampling. Above-the-line and below-the-line testing checks whether alerts just above the threshold are productive and whether activity just below the threshold is being missed. Thresholds must be documented with a rationale; undocumented or arbitrary thresholds are a major examination weakness.
6. Alert generation, triage and investigation. Alerts are prioritized (often by risk score), assigned to analysts and reviewed within defined service-level timelines. Investigators gather KYC information, transaction history, open-source intelligence and internal records, document their analysis and reach a disposition: close as not suspicious, escalate to a case, or recommend a SAR/STR. Procedures must define escalation criteria, four-eyes review for closures, quality control sampling and documentation standards so that any reviewer can understand why a decision was made.
7. Reporting and record keeping. When suspicion is confirmed, the institution files within the regulatory deadline (for example, 30 days from initial detection in the US, with a possible 30-day extension to identify a subject, and continuing activity reviews typically every 90 to 120 days). Records of alerts, investigations and supporting documentation are retained for the mandated period (commonly five years) and must be retrievable for regulators and law enforcement. Tipping-off prohibitions must be built into procedures.
8. Tuning, optimization and the feedback loop. A monitoring program is never finished. Periodic tuning analyzes alert volumes, false-positive rates, SAR conversion rates and investigator feedback to refine scenarios and thresholds. New typologies from regulators, FIUs, law enforcement requests, internal SAR trends and industry bodies are fed back into design. Every change passes through a documented change-management process with business justification, testing, approval and post-implementation review.
9. Model validation and independent testing. Independent validation (by a function separate from those who built and run the system) assesses conceptual soundness, data quality, implementation accuracy, performance and ongoing monitoring. Internal audit then tests the program end to end, including governance, coverage, data, tuning evidence, alert handling, backlog, staffing and management reporting. Findings are tracked to remediation.
10. Governance, metrics and oversight. Senior management and the board receive management information such as alert volumes by scenario, aging and backlog, closure rates, SAR filings, quality-control results, system outages and open audit issues. The Compliance Officer or Money Laundering Reporting Officer owns the program, with clear roles across first line (business), second line (compliance) and third line (audit). Policies and procedures document the entire design so it can be explained and defended.
Common Design Weaknesses the Exam Likes to Test
• Scenarios not linked to the risk assessment or coverage gaps for high-risk products.
• Incomplete data feeds (acquired entities, new products or specific transaction types excluded).
• Thresholds set only to manage workload rather than to detect risk.
• Changing thresholds without documentation, testing or approval.
• Alert backlogs that cause missed filing deadlines.
• No independent validation of the system or model.
• Investigators closing alerts without adequate documentation or without considering the full customer relationship.
• Failure to incorporate new typologies, law enforcement requests or SAR trend analysis.
• Over-reliance on vendor default settings without customization to the institution's risk profile.
• Treating a technology purchase as a complete solution without procedures, training and governance.
Exam Tips: Answering Questions on Transaction Monitoring Program Design
Tip 1 – Always anchor to the risk-based approach. When a question asks what should drive scenario selection, threshold setting or resource allocation, the correct answer almost always links back to the institution's risk assessment and customer risk profiles, not to regulator preferences, vendor defaults, cost or alert volume alone.
Tip 2 – Look for the governance answer. If a scenario describes a proposed change to a rule or threshold, the best answer involves documentation, analysis, testing, approval through change management and independent review. Answers that involve a single person quietly adjusting settings to reduce alerts are distractors.
Tip 3 – Data before technology. When a system is producing poor results, the CAMS examiner frequently expects you to identify data completeness and accuracy as the first thing to check. Buying a new system or hiring more analysts is rarely the first step.
Tip 4 – Know the difference between tuning and suppression. Legitimate tuning is evidence-based, documented and tested with above- and below-the-line analysis. Simply raising thresholds to eliminate a backlog or excluding a profitable customer from monitoring is a red flag, and answer options describing this are wrong.
Tip 5 – Remember independence. Validation and testing must be performed by parties independent of those who designed and operate the system. If an answer has the model developer validating their own model, eliminate it.
Tip 6 – Backlogs connect to filing deadlines. Questions about alert backlogs are often really about timely SAR/STR filing and escalation to senior management. The best response is to prioritize by risk, escalate the issue, document the remediation plan and ensure filing obligations are met, not to bulk-close alerts.
Tip 7 – Think end to end. A monitoring program includes design, data, detection, investigation, reporting, tuning, validation and governance. If an answer addresses only the software, it is usually incomplete. Prefer answers that treat monitoring as a program with people, processes and technology.
Tip 8 – Identify the most appropriate, not merely a correct, action. CAMS questions frequently offer several plausible steps. Ask which action a competent compliance officer would take first or which is most effective. Typically: assess, document, escalate, remediate in a controlled way.
Tip 9 – Match monitoring to the entity. Scenarios involving correspondent banking, MSBs, casinos, securities firms or virtual asset service providers call for sector-specific typologies and segmentation. Generic retail scenarios applied to these segments indicate a design flaw.
Tip 10 – Watch the vocabulary. Be comfortable with terms such as scenario, typology, threshold, segmentation, false positive, false negative, SAR conversion rate, above-the-line/below-the-line testing, coverage assessment, data lineage, model validation, change management, alert aging and continuing activity review. The exam often tests understanding through the correct use of these terms.
Worked Example
Scenario: A bank recently acquired a smaller institution with a large base of money services business customers. Six months later, internal audit notes that no SARs have been filed on any acquired MSB customer, although alert volumes overall have risen sharply. The compliance officer discovers the acquired customers were loaded into the monitoring system under the standard retail segment. What is the most appropriate response?
Analysis: The core issue is a design and segmentation failure: high-risk MSB customers are being monitored with retail thresholds and scenarios that do not reflect their risk profile, which may produce both irrelevant alerts and missed suspicious activity. The best answer is to perform a coverage and segmentation review, reclassify the MSB customers into an appropriate high-risk segment with tailored scenarios and thresholds, conduct a look-back on their activity since acquisition, document and approve the changes through change management, and report the issue and remediation to senior management. Options such as simply closing the excess alerts, waiting for the next annual review or relying on the acquired bank's prior approach would be incorrect.
Key Takeaways
• Transaction monitoring is a risk-based, governed program, not just a tool.
• Scenarios and thresholds must trace back to the risk assessment and be documented.
• Data completeness and accuracy are foundational; verify them first.
• Tuning is evidence-based and controlled; suppression to reduce workload is a violation of program integrity.
• Independent validation and audit, timely investigations, proper record keeping and management reporting complete the cycle.
• On the exam, choose the answer that reflects a documented, risk-based, independently tested and escalated approach.
Transaction monitoring (TM) is the engine room of an anti-financial crime (AFC) program. Customer due diligence tells you who your customer is and what you expect them to do; transaction monitoring tells you whether they are actually behaving that way. Without a well-designed monitoring program, a financial institution cannot credibly detect suspicious activity, cannot file timely Suspicious Activity Reports (SARs) or Suspicious Transaction Reports (STRs), and cannot demonstrate to regulators that its risk-based approach is more than words on paper.
Regulators worldwide treat TM failures as evidence of systemic AML weakness. Many of the largest enforcement actions in history (consent orders, deferred prosecution agreements and multi-billion-dollar penalties) cite poorly calibrated scenarios, missing data feeds, unmanaged alert backlogs, undocumented threshold changes or a monitoring system that was never aligned to the institution's own risk assessment. For the CAMS exam, this topic sits within AFC Program Governance and Risk Management because the examiners want you to understand monitoring as a governed, risk-based, documented and continuously improved process, not simply as a piece of software.
What Transaction Monitoring Program Design Is
Transaction monitoring program design is the structured process by which an institution decides what activity it will watch, how it will watch it, who will review the results, and how it will prove the system works. It covers the full lifecycle from data capture through alert generation, investigation, escalation, reporting and feedback. A sound design is:
• Risk-based – driven by the enterprise-wide AML risk assessment (customers, products, services, channels, geographies).
• Data-driven – built on complete, accurate and timely data from all relevant systems.
• Typology-informed – scenarios reflect known money laundering, terrorist financing, fraud and sanctions-evasion patterns relevant to the institution.
• Governed – changes to rules, thresholds and models are approved, documented and auditable.
• Tested and validated – performance is measured, tuned and independently reviewed.
• Resourced – staffed with trained investigators and supported by clear procedures and escalation paths.
Regulatory anchors you should recognize include FATF Recommendation 10 (ongoing due diligence and scrutiny of transactions), Recommendation 20 (reporting of suspicious transactions), the US Bank Secrecy Act and FinCEN requirements for a reasonably designed program with internal controls and independent testing, the EU Anti-Money Laundering Directives requiring ongoing monitoring, and industry guidance such as the Wolfsberg Group statements on monitoring and the use of technology. The common thread: monitoring must be appropriate to the institution's size, complexity and risk profile.
How Transaction Monitoring Program Design Works
1. Start with the risk assessment. The enterprise-wide risk assessment identifies inherent risks and residual risks after controls. TM scenarios should map back to those risks. If the risk assessment identifies correspondent banking, cash-intensive businesses, high-risk jurisdictions or virtual asset customers as elevated risks, the monitoring program must contain scenarios that specifically address them. A gap between identified risks and monitoring coverage is a classic exam scenario and a classic regulatory finding.
2. Define coverage and typologies. Designers inventory the products, channels and customer segments in scope and select typologies to detect, such as structuring below reporting thresholds, rapid movement of funds (pass-through or funnel accounts), unusual cash activity, round-dollar wire transfers, activity inconsistent with stated business, dormant account reactivation, high-risk jurisdiction flows, trade-based money laundering indicators, and patterns associated with human trafficking, elder abuse or terrorist financing. Coverage assessments compare the list of relevant typologies against implemented scenarios to identify gaps.
3. Secure data integrity. The system is only as good as its inputs. Design work includes data lineage mapping (which source systems feed the TM engine), completeness checks (are all accounts, all transaction types and all legal entities captured?), accuracy checks (are country codes, customer types and transaction codes correct?), and timeliness (is data loaded daily or in real time where needed?). Reconciliation controls confirm that transactions in the core system match transactions received by the monitoring system. Missing wire fields, unmapped product codes or excluded subsidiaries are frequent root causes of monitoring failure.
4. Choose the detection approach.
• Rules-based (scenario) monitoring uses predefined logic and thresholds (for example, aggregate cash deposits over X within Y days). It is transparent and explainable but can generate high false positives and may miss novel patterns.
• Behavioral or profile-based monitoring compares current activity against the customer's own historical baseline or peer group, flagging deviations.
• Statistical and machine learning models score risk, prioritize alerts or detect anomalies. They can improve efficiency but demand stronger model governance, explainability and validation.
• Real-time versus batch: payments screening and some fraud controls run in real time; most AML monitoring runs in post-transaction batch cycles.
Most mature programs blend these approaches. The exam expects you to know the trade-offs rather than to declare one approach always superior.
5. Segment and set thresholds. Customers are grouped into segments with similar expected behavior (retail, small business, high-net-worth, correspondent banks, money services businesses, etc.). Thresholds are set per segment so a legitimate large corporate does not trigger the same cash rule as a student account. Threshold setting uses historical data analysis, statistical distributions and sampling. Above-the-line and below-the-line testing checks whether alerts just above the threshold are productive and whether activity just below the threshold is being missed. Thresholds must be documented with a rationale; undocumented or arbitrary thresholds are a major examination weakness.
6. Alert generation, triage and investigation. Alerts are prioritized (often by risk score), assigned to analysts and reviewed within defined service-level timelines. Investigators gather KYC information, transaction history, open-source intelligence and internal records, document their analysis and reach a disposition: close as not suspicious, escalate to a case, or recommend a SAR/STR. Procedures must define escalation criteria, four-eyes review for closures, quality control sampling and documentation standards so that any reviewer can understand why a decision was made.
7. Reporting and record keeping. When suspicion is confirmed, the institution files within the regulatory deadline (for example, 30 days from initial detection in the US, with a possible 30-day extension to identify a subject, and continuing activity reviews typically every 90 to 120 days). Records of alerts, investigations and supporting documentation are retained for the mandated period (commonly five years) and must be retrievable for regulators and law enforcement. Tipping-off prohibitions must be built into procedures.
8. Tuning, optimization and the feedback loop. A monitoring program is never finished. Periodic tuning analyzes alert volumes, false-positive rates, SAR conversion rates and investigator feedback to refine scenarios and thresholds. New typologies from regulators, FIUs, law enforcement requests, internal SAR trends and industry bodies are fed back into design. Every change passes through a documented change-management process with business justification, testing, approval and post-implementation review.
9. Model validation and independent testing. Independent validation (by a function separate from those who built and run the system) assesses conceptual soundness, data quality, implementation accuracy, performance and ongoing monitoring. Internal audit then tests the program end to end, including governance, coverage, data, tuning evidence, alert handling, backlog, staffing and management reporting. Findings are tracked to remediation.
10. Governance, metrics and oversight. Senior management and the board receive management information such as alert volumes by scenario, aging and backlog, closure rates, SAR filings, quality-control results, system outages and open audit issues. The Compliance Officer or Money Laundering Reporting Officer owns the program, with clear roles across first line (business), second line (compliance) and third line (audit). Policies and procedures document the entire design so it can be explained and defended.
Common Design Weaknesses the Exam Likes to Test
• Scenarios not linked to the risk assessment or coverage gaps for high-risk products.
• Incomplete data feeds (acquired entities, new products or specific transaction types excluded).
• Thresholds set only to manage workload rather than to detect risk.
• Changing thresholds without documentation, testing or approval.
• Alert backlogs that cause missed filing deadlines.
• No independent validation of the system or model.
• Investigators closing alerts without adequate documentation or without considering the full customer relationship.
• Failure to incorporate new typologies, law enforcement requests or SAR trend analysis.
• Over-reliance on vendor default settings without customization to the institution's risk profile.
• Treating a technology purchase as a complete solution without procedures, training and governance.
Exam Tips: Answering Questions on Transaction Monitoring Program Design
Tip 1 – Always anchor to the risk-based approach. When a question asks what should drive scenario selection, threshold setting or resource allocation, the correct answer almost always links back to the institution's risk assessment and customer risk profiles, not to regulator preferences, vendor defaults, cost or alert volume alone.
Tip 2 – Look for the governance answer. If a scenario describes a proposed change to a rule or threshold, the best answer involves documentation, analysis, testing, approval through change management and independent review. Answers that involve a single person quietly adjusting settings to reduce alerts are distractors.
Tip 3 – Data before technology. When a system is producing poor results, the CAMS examiner frequently expects you to identify data completeness and accuracy as the first thing to check. Buying a new system or hiring more analysts is rarely the first step.
Tip 4 – Know the difference between tuning and suppression. Legitimate tuning is evidence-based, documented and tested with above- and below-the-line analysis. Simply raising thresholds to eliminate a backlog or excluding a profitable customer from monitoring is a red flag, and answer options describing this are wrong.
Tip 5 – Remember independence. Validation and testing must be performed by parties independent of those who designed and operate the system. If an answer has the model developer validating their own model, eliminate it.
Tip 6 – Backlogs connect to filing deadlines. Questions about alert backlogs are often really about timely SAR/STR filing and escalation to senior management. The best response is to prioritize by risk, escalate the issue, document the remediation plan and ensure filing obligations are met, not to bulk-close alerts.
Tip 7 – Think end to end. A monitoring program includes design, data, detection, investigation, reporting, tuning, validation and governance. If an answer addresses only the software, it is usually incomplete. Prefer answers that treat monitoring as a program with people, processes and technology.
Tip 8 – Identify the most appropriate, not merely a correct, action. CAMS questions frequently offer several plausible steps. Ask which action a competent compliance officer would take first or which is most effective. Typically: assess, document, escalate, remediate in a controlled way.
Tip 9 – Match monitoring to the entity. Scenarios involving correspondent banking, MSBs, casinos, securities firms or virtual asset service providers call for sector-specific typologies and segmentation. Generic retail scenarios applied to these segments indicate a design flaw.
Tip 10 – Watch the vocabulary. Be comfortable with terms such as scenario, typology, threshold, segmentation, false positive, false negative, SAR conversion rate, above-the-line/below-the-line testing, coverage assessment, data lineage, model validation, change management, alert aging and continuing activity review. The exam often tests understanding through the correct use of these terms.
Worked Example
Scenario: A bank recently acquired a smaller institution with a large base of money services business customers. Six months later, internal audit notes that no SARs have been filed on any acquired MSB customer, although alert volumes overall have risen sharply. The compliance officer discovers the acquired customers were loaded into the monitoring system under the standard retail segment. What is the most appropriate response?
Analysis: The core issue is a design and segmentation failure: high-risk MSB customers are being monitored with retail thresholds and scenarios that do not reflect their risk profile, which may produce both irrelevant alerts and missed suspicious activity. The best answer is to perform a coverage and segmentation review, reclassify the MSB customers into an appropriate high-risk segment with tailored scenarios and thresholds, conduct a look-back on their activity since acquisition, document and approve the changes through change management, and report the issue and remediation to senior management. Options such as simply closing the excess alerts, waiting for the next annual review or relying on the acquired bank's prior approach would be incorrect.
Key Takeaways
• Transaction monitoring is a risk-based, governed program, not just a tool.
• Scenarios and thresholds must trace back to the risk assessment and be documented.
• Data completeness and accuracy are foundational; verify them first.
• Tuning is evidence-based and controlled; suppression to reduce workload is a violation of program integrity.
• Independent validation and audit, timely investigations, proper record keeping and management reporting complete the cycle.
• On the exam, choose the answer that reflects a documented, risk-based, independently tested and escalated approach.
Test mode:
CAMS - Transaction Monitoring Program Design Example Questions
Test your knowledge of Transaction Monitoring Program Design
Question 1
In tuning a transaction monitoring system, which of the following best describes below-the-line testing?
Question 2
A compliance analyst reconciles core banking records against the transaction monitoring system. The analyst finds that wire transfers from a channel added during a system migration six months ago were never loaded into monitoring. The data feed has now been corrected and is loading in full. What should the MLRO do NEXT to address the risk created by the gap?
Question 3
A payment service provider is launching a cross-border payout service for small merchants. To save time, the compliance team plans to reuse the transaction monitoring scenarios already running on its domestic wallet product. Before go-live, which step BEST supports an effective monitoring design for the new service?
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More Transaction Monitoring Program Design questions
18 questions (total)
Other AFC Program Governance and Risk Management concepts
BSA Officer and MLRO Role, Authority and IndependenceCommunicating Risk Appetite and Linking ControlsCulture of Compliance and Tone from the TopCustomer Due Diligence and Beneficial OwnershipCustomer Life-Cycle Controls and Exit DecisionsCustomer Risk Rating and AssessmentEnhanced Due Diligence: Triggers and MeasuresEnterprise-Wide Risk Assessment MethodologyGovernance Committees and Terms of ReferenceHorizon Scanning and Regulatory Change ManagementIncorporating Guidance and Best Practice into PoliciesInherent Risk, Control Effectiveness and Residual RiskKeeping Accounts Open for Law EnforcementKey Performance Indicators and Key Risk IndicatorsKnow Your Customer and Customer IdentificationManagement Information and Board ReportingPillars of an AFC Compliance ProgramPolicies, Standards and Procedures: Hierarchy and ContentRisk Appetite Statement: Purpose and ContentSuspicious Activity Reporting ObligationsThe Risk-Based Approach and Proportionate ControlsThree Lines of Defence ModelThreshold and Currency Transaction ReportingTypes of Risk Assessment: Inputs, Outputs and MitigationWorking with Other Risk Management Functions