To oversee system resources related to implementing and maintaining diverse control measures within the Fraud Control and Analytics team, ensuring effective management of fraud risks through prevention, detection, and financial crime analysis. Proactively monitor and utilize Fraud Risk Management (FRM) solutions alerts, reports, dashboards, and data analytics.
Main Responsibilities:
- Utilizing advanced data analytics techniques to closely monitor and analyze data, identify patterns and trends indicative of fraudulent activities, and promptly respond to any suspicious activities.
- Designing and implementing effective rules on financial and non-financial events focusing on Fraud Prevention and Detection, Anti-Money Laundering (AML), Customer Due Diligence (CDD), and Sanctions Screening while ensuring compliance with all regulatory as well as internal policy requirements, all of which targeted at mitigating financial crime risks and protecting the bank and its clientele.
- Identify the modus operandi of any fraudulent occurrences, whether reported by forensic investigation team, the business team, or detected internally through system or analytics, to swiftly implement controls to prevent such events from recurring.
- Management Information (MI) reporting established through creating and delivering a variety of reports on patterns, trends, and other statistical methodologies.
- Working collaboratively with ICT teams to maintain and improve systems and tools used for fraud detection and prevention, AML and CDD, ensuring optimal system performance.
- Keeping abreast of the latest trends and technologies in financial crime control, fraud detection, and prevention and incorporating this knowledge into the banks risk management practices.
- Providing training and education to bank employees on financial crime control and detection, promoting a culture of compliance and vigilance.
- Collaborating closely with other stakeholders within the bank to ensure that financial crime control policies and procedures are up-to-date, effectively implemented, and adhered to.
- Establishing a robust machine learning environment by incorporating approved third-party machine learning-focused tools into existing internal system resources.
- Developing and maintaining a network of professional contacts within the industry to keep being informed of best practices and emerging trends.
Knowledge and Skills:
- Knowledge in advanced data analytics tools and techniques such as SQL, Big Data Analytics coupled with the ability to detect hidden patterns and trends.
- Proficiency in machine learning algorithms and their practical applications is essential,
- Familiarity with Anti-Money Laundering (AML), Customer Due Diligence (CDD), and Sanctions Screening rules and regulations is vital.
- Strong knowledge of fraud detection and prevention strategies, Microsoft office (Excel and PowerPoints) is necessary.
- Skills in SQL, Python languages etc. and other tools for analyzing system data, detecting fraud trends, and providing data-driven recommendations to solve business problems.
- Ability to work in a fast-paced environment and manage multiple priorities.
- Having a fundamental understanding of information and communication technology (ICT) is an essential requirement for the role.
- Highly organized with exceptional attention to detail, demonstrating creativity and problem-solving skills when monitoring system information.
- Strong communication skills, able to write inputs for management reports which may present findings to diverse audiences, including legal proceedings.
- Excellent interpersonal skills, confident in stakeholder engagement, able to work independently under pressure, and meet deadlines.
- Integrity, determination, and a commitment to prioritize the banks interests above personal gain in uncovering the truth.
- Proactive in fostering open communication, teamwork, and trust to promote a customer-centric culture.
Qualifications and Experience:
- Bachelor’s degree or its equivalent in Data Science, IT Finance / Accounting, Banking, Economics, Actuarial Science, or equivalent qualifications.
- Professional qualifications in financial crime control such as CFE will be an added advantage.
- Minimum 3 years’ experience in Banking, Telecom, or other Industry all of which are related with Financial Crime Control.
- Experience in information security controls, electronic payments or risk operations and system Data Analytics.