ACAMS Certification - Anti Money Laundering Course in Kuwait
Curriculum mapped to official CAMS knowledge areas
Insights from experienced AML practitioners
AI-enabled compliance monitoring & detection concepts
Mock assessments & practical exam preparation
Flexible classroom & live online training with easy instalment plans
Overview
What our training includes:
- Aligned with the latest ACAMS examination blueprint
- Eight modules covering AML, CFT and financial crime compliance
- Practical workshops, case studies and investigation simulations
- AI-assisted transaction monitoring and compliance risk analysis
- Mock assessments designed to strengthen CAMS examination readiness
Upcoming sessions
Curriculum
What is money laundering and the stages of placement, layering, and integration
Definitions and distinctions: AML, CFT, sanctions, fraud, anti-bribery and corruption (ABC), and tax evasion
Financial crime landscape, predicate crimes, and global impact
Sector-specific financial crime risk: banking, insurance, MSBs/PSPs/ecommerce, VASPs and
cryptoassets, gaming and gambling, real estate, gatekeepers (lawyers, notaries, accountants), trusts and company service providers
FC risks related to PEPs and other highrisk customers
CAMS-aligned AML/AFC concepts (current blueprint)
AI Integration
- Analyze money laundering typologies and financial crime indicators using AI-assisted compliance research
- Generate structured AML concept summaries and revision notes
Activities/Case Study
- Identifying money laundering stages across multiple industries.
Customer Identification Program (CIP)
Customer Due Diligence (CDD)
Enhanced Due Diligence (EDD)
Beneficial Ownership
Ongoing Monitoring
Politically Exposed Persons (PEPs)
High-Risk Customers
Customer Risk Rating Methodologies
AI Integration
- Evaluate customer risk indicators and beneficial ownership structures
- Support customer due diligence documentation and risk classification
FATF Recommendations and GCC regulator linkages
(Note: FATF standards are globally neutral — the GCC regulator linkages are Learners Point's applied regional layer, not an ACAMS-defined scope.)
Public-private partnerships (PPP) and cross-border regulatory/FIU cooperation
United Nations conventions
Basel Committee guidance
Wolfsberg Principles
Financial Intelligence Units (FIUs)
International sanctions frameworks
AI Integration
- Compare global AML regulations and FATF requirements
- Analyze international compliance obligations across jurisdictions
Activities/Case Study
- Cross-border AML regulatory compliance assessment
Risk-Based Approach (RBA)
Enterprise AML governance framework
AML policies, procedures, and controls
AML risk assessments
Independent testing and audit
Compliance monitoring
Three lines of defense model
BSA Officer / MLRO roles and responsibilities
Risk Appetite Statement (RAS): purpose, drafting, communication, and control implementation
AI Integration
- Review AML governance structures and compliance frameworks
- Analyze enterprise risk assessment methodologies
Activities/Case Study
- Developing an enterprise AML compliance programme
Suspicious Activity Reports (SAR/STR)
Transaction monitoring
Investigation methodologies
Case management
Regulatory examinations
Enforcement actions
KPIs and KRIs for board and management reporting
De-risking and financial inclusion "Tipping off", customer communication, and use of Requests for Information (RFIs)
Named regulatory info-sharing regimes: FinCEN 314(a)/314(b), EU Regulation 2024/1624, COSMIC (Singapore)
Interaction between AFC professionals and the front office (relationship/account managers)
AI Integration
- Review suspicious transaction patterns and investigation workflows
- Support SAR drafting and case documentation analysis
Activities/Case Study
- Regulatory investigation involving complex financial crime activities
Sanctions compliance framework
OFAC, UN, EU and regional sanctions programmes
Transaction monitoring principles
Suspicious transaction indicators
Escalation procedures
Case documentation
Regulatory reporting obligations
AI Integration
- Analyze sanctions screening results and transaction monitoring alerts
- Support suspicious activity identification and escalation decisions
Activities/Case Study
- Identifying and escalating suspicious transactions involving sanctioned entities
Investigation planning
Evidence collection and documentation
Interview techniques
Case management lifecycle
Regulatory cooperation
Preparing investigation reports
Financial Intelligence Unit (FIU) engagement
AI Integration
- Organize investigation evidence and analyze transaction relationships
- Generate investigation timelines and reporting summaries
Activities/Case Study
- Multi-jurisdiction financial crime investigation involving complex transaction patterns
E-KYC, digital identity, facial recognition, liveness checks, biometrics, geolocation
Name/customer screening against named sanctions lists: OFAC, UN, EU
AI/machine-learning tools across onboarding, screening, transaction monitoring, and investigations
Traditional rules-based transaction monitoring: scenario coverage, threshold setting, statistical testing, model risk management and tuning
Network analysis tools
RegTech, data privacy/data protection considerations in AFC tools
Virtual assets and digital payment risks
AI Integration
- Apply AI-enabled onboarding, sanctions screening, transaction monitoring, network analysis, and investigation support tools
- Evaluate RegTech solutions and emerging digital financial crime risks
Activities/Case Study
- Implementing digital AML controls across a financial institution using modern compliance technologies
Learning Outcomes
Upon finishing the course, you will be able to:
1
Identify money laundering methods, financial crime risks, and suspicious activity indicators
2
Apply FATF recommendations, AML regulations, and international sanctions frameworks
3
Conduct KYC, customer due diligence, enhanced due diligence, and customer risk assessments
4
Investigate suspicious transactions and prepare structured SAR or STR documentation
5
Design and evaluate risk-based AML compliance programs, governance structures, and internal controls
6
Use AI-supported compliance tools, transaction monitoring systems, and analytical techniques while preparing confidently for the CAMS examination
Prerequisites
The eligibility requirements for the Anti Money Laundering Course in Kuwait are as follows:
- Get an active ACAMS membership
- Educational qualifications with a credit allocation of 10 for Associates, 20 for Bachelors, 30 for Masters and 40 for JD or PhD
- Work experience, where each year contributes 10 credits. Training in financial-crime-related areas, with a credit earned for every hour of training
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Frequently asked questions
Yes. The course content is aligned with the latest CAMS examination blueprint. It covers financial crime risks, global anti-financial crime frameworks, compliance program development, and the tools and technologies used to prevent financial crime.
This course is suitable for the following professionals:
- AML Analysts
- Compliance Officers
- KYC Specialists
- Sanctions Professionals
- Transaction Monitoring Analysts
It is also relevant to professionals working in banks, exchange houses, insurance companies, fintech businesses, payment service providers and virtual asset organizations.
Yes. Professionals learn how to conduct customer identification, customer due diligence and enhanced due diligence. The course also covers beneficial ownership, ongoing monitoring, high-risk customers, politically exposed persons and customer risk-rating methodologies.
AI-supported exercises help participants examine money laundering typologies, evaluate customer risks, review transaction patterns, organize investigation evidence and assess compliance frameworks. The course also introduces AI and machine-learning applications in onboarding, screening, transaction monitoring and investigations.
Learners Point delivers a structured 32-hour CAMS preparation program that combines examination-focused instruction with practical compliance learning. Participants benefit from:
- Eight Detailed Modules
- Instructor Guidance
- Case Studies
- Mock Tests
- **AI-Assisted Activities **
Yes. Every module includes application-based learning through workshops, case studies, mock tests and compliance scenarios. Activities include customer risk profiling, regulatory framework comparison, AML program design, sanctions alert review and end-to-end financial crime investigations.
Yes. The program provides structured coverage of AML fundamentals, customer due diligence, sanctions, transaction monitoring, investigations and compliance governance. It is suitable for professionals entering the AML field as well as those seeking to strengthen their existing compliance knowledge.
The course provides 32 hours of structured training across eight CAMS-aligned modules. You will complete practical exercises, case studies, module-wise mock tests, investigation activities and AI-supported compliance tasks designed to improve your subject knowledge, analytical ability and examination confidence.
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