Specialist: Fraud Detection at Road Accident Fund

Purpose of the Job:

• Reporting to the Senior Manager: Cyber Forensic, the successful incumbent is responsible for developing and implementing fraud detection strategies and practices by using fraud trend insights within the fraud community to effectively and proactively detect fraud incidents.

Key Performance Areas

Fraud Detection Analysis

• Analyse incidents that lead to fraud detection.
• Analyse suspicious behaviour or patterns that might indicate suspected fraud.
• Conduct analysis and review allegations of suspected fraud.
• Conduct thorough research suspected fraud allegations to gather evidence in determing a fraud activity.

Fraud Detection Interventions and Enhancement

• Implement fraud detection systems that are equiped to dapt to new threats as they emerge.
• Drive continuous harvesting of insights from fraud loss events and build fraud intelligence to inform controls and development of new system rules and enhancements.
• Monitor the implementation and effectiveness of proposed system, control and detection enhancements to improve fraud detection.
• Ensure that required systems are available for use, suitable rules are applied, and fraud intervention processes are executed within the required timelines and compliance standards.

Conduct Regular System Audits

• Conduct assessments to identify vulnerabilities and system gaps.
• Ensure that the fraud detection system is functioning effectively.
• Detect control weaknesses and evolving fraud tactics.

Lifestyle Audit

• Data colllection: Extraction of financial documents and any other supporting documents.
• Data preparation: Transforming, converting and enriching data.

Policy Review and Implementation

• Develop, review and implement departmental policies and procedures and processes.
• Keep up to date with effective policy and practice execution strategies.
• Develop and implement the appropriate Fraud Control strategy with priorities and objectives for the forthcoming year.

Reporting

• Track and analyse potential fraud trends and performance.
• Collect data from various sources, from external threat intelligence  to be used in detailed analysis.
• Analyse data form for detailed fraud patterns.
• Conduct fraud analytics to improve the detection speed and accuracy.
• Extract and share insights and lessons learnt from root cause analysis applied in fraud cases to inform further fraud prevention improvements across a wide range of processes and systems, regulation and policies.
• Compile and communicate accurate and timely reports to track progress made and keep key stakeholders informed of fraud detection.
• Prepare detailed reports on findings and provide recommendations for preventive measures in consultation with Fraud Prevention unit.

Stakeholder Management

• Communicate to relevant stakeholders and fraud teams to alert them to potential threats that could harm RAF.
• Collaborating with other data analysts, you will help build models and rules to prevent fraud while minimising customer impact.
• Coordinate with law enforcement agencies when required.
• Active participation in and contribution to specialist practice forums to share information and insights across the business.

Qualifications and Experience

• Bachelor’s Degree/ Advanced Diploma in Information Technology/ Computer Science/ Information Management/ Data Analysis/ Data Science.
• Association/ Affiliation in one or more of the following professional bodies ACFE/ ICFP or ISACA.
• ACL Certified Data Analyst (ACDA)/ MCSE/ Certified Analytics Professional (CAP)/ Certified Data Management Professional (CDMP) or any other equivalent Data Analytics Certificate will be added advantage.
• Relevant 5 - 7 years’ experience in data analytics, auditing or banking environment inclusive of experience in analysis methodologies, process disciplines, system development lifecycle methodologies and automation and scheduling experience.
• Experience in data mining and the development of procedures automated for management reporting purposes will be an added advantage.
• Experience in the application of data analysis tools such as: MS SQL/ ACL/ Analyst Notebook/ MS Power BI/ AWS Database.

Technical and Behavioral Competencies Required

• Resilience.
• Network and alliance.
• Employee engagement.
• Ethics and values.
• Change management.
• Critical and innovative thinking
• Policy conceptualisation and formulation.
• Risk Management.
• Stakeholder development and relations.
• Reporting.
• Ability to develop data interrogation techniques and the creation of data cubes.
• Knowledge of database tools, structures and extraction tools.
• Knowledge of data integration and transformation practices.
• Knowledge of data quality practices.
• Knowledge of data mining and analysis.
• Knowledge data analysis tools such as: MS SQL/ ACL/ Analyst Notebook/ MS Power BI/ AWS Database/Tableau.
• Computer Literacy (MS Word, MS Excel, MS Outlook).