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AVP- Compliance System Governance
4 weeks ago
Job Description
JOB PURPOSE:
Compliance Systems Governance and Model Validation Unit
The unit is responsible for managing the Group Compliance system monitoring and validation programme (as the second line of defence) to provide assurance that the Group is operating in line with regulatory requirements and internal compliance policies and procedures. This entails planning, development and implementation of a risk-based Group Compliance system Validation plan, working with other Compliance units to undertake reviews and issuing reports that provide assurance as well as highlighting deficiencies so that they can be corrected. The function also aids in the development of compliance reports to support the EXCO, Compliance Operating Committee, GCC and MRMC.
The Transaction Monitoring SAS AML Model Validation Specialist will be responsible for validating and ensuring the accuracy and effectiveness of AML (Anti-Money Laundering) models used for transaction monitoring. This role requires a deep understanding of SAS AML solutions, statistical modeling, and regulatory requirements.
KEY ACCOUNTABILITIES:
Job Specific Accountabilities
Policies, Systems, Process & Procedures
- Follow all relevant departmental policies, processes, standard operating procedures, and instructions so that the work is carried out in a controlled and consistent manner.
Key Responsibilities:
- Conduct comprehensive validation of sanctions screening models, including data integrity, model performance, and output accuracy.
- Perform detailed data analysis to assess the performance and accuracy of AML models, identifying any potential weaknesses or areas for improvement.
- Develop and implement validation methodologies and frameworks in line with industry best practices and regulatory guidelines.
- Perform quantitative and qualitative analysis to assess model risk and performance.
- Collaborate with model developers, compliance teams, and other stakeholders to address validation findings and improve model robustness.
- Prepare detailed validation reports and documentation for internal and regulatory review.
- Stay updated with the latest regulatory requirements, industry trends, and advancements in transaction monitoring technologies.
- Provide recommendations for model improvements and enhancements based on validation results.
- Work closely with the AML team, data scientists, and IT department to implement and validate models effectively.
- Generate regular reports on model performance, validation results, and any necessary adjustments or recalibrations.
Reporting
- Collaborate with Compliance SMEs,work closely with Subject Matter Experts (SMEs) in Compliance to develop Management Information (MI) dashboards related to compliance systems validation.
- Create periodic review plans and regularly report the status of these reviews to senior management.
- Track and ensure timely closure of any pending issues identified in previous reviews.
- Contribute to the development of the annual review plan in accordance with regulatory requirements, internal audit (GIA) guidelines, and any ad hoc requirements.
Qualifications
Minimum Qualification
- Bachelor's or master's degree in Finance, Economics, Statistics, Mathematics, Computer Science, or a related field.
- Proven experience in model validation, risk management, or a similar role within the financial services industry.
- In-depth understanding of sanctions regulations and compliance standards, including OFAC, EU sanctions, and other international sanctions regimes. Understanding of CBUAE regulations is desirable.
Minimum Experience
- 8 to 10 years of experience with financial institutions, regulators, and/or professional services firms, focusing on Financial Crime Technology and Analytics work streams/services.
- Strong understanding of transaction monitoring processes, regulatory requirements, and compliance standards.
- Extensive experience with SAS AML, including model development, implementation, tuning and validation.
- Proficiency in SAS programming, SQL, and other relevant programming languages.
- Proficiency in statistical analysis, data modeling, and programming languages such as Python, R, or SAS.
- Strong understanding of statistical methods and their application in model validation.
- Familiarity with machine learning algorithms and techniques for model development and validation.
- Experience in data governance, including data quality management, data lineage, and data stewardship, ensuring that data used in model validation is accurate, consistent, and reliable.
- Strong skills in data extraction, transformation, and loading (ETL) processes.
- Experience with SQL for database management and querying large datasets.
- Understanding of data warehouse, master data management, and data lake concepts is desirable.
- Excellent understanding of IT service management (ITSM) frameworks such as ITIL and other system performance monitoring controls.
- Good understanding of Disaster Recovery (DR) and Business Continuity Planning (BCP) to Ensure System Resilience and Availability
- Ability to conduct comprehensive quantitative and qualitative analysis to assess model performance and risk.
- Proficiency in backtesting, stress testing, and sensitivity analysis to evaluate model robustness.
- Ability to work independently and as part of a team, collaborating with model developers, compliance teams, and other stakeholders.
- Strong interpersonal skills to build effective working relationships across the organization.
- Strong technical writing skills for preparing detailed validation reports and documentation.
- Experience in preparing reports for regulatory review and compliance purposes.
- Attention to detail and a commitment to maintaining high standards of accuracy and integrity.
- Certification in ACAMS or SAS is an added advantage.
- Excellent analytical, problem-solving, and communication skills.