Associate Analyst - Fraud Risk Management

Role: Associate Analyst - Fraud Risk Management 

Location: Sharjah, UAE

This position is for fresh graduates UAE Nationals only.

Role purpose:

• Support Fraud Risk Management in improving fraud detection, prevention, sampling, verification monitoring and control effectiveness through data analytics, automation and responsible use of AI and machine learning.

• The graduate role combines fraud-risk development with hands-on analytical, sampling, MIS and process-improvement support.

• Under supervision, assist fraud operations, model owners, technology, data and model risk teams with data preparation, performance analysis, testing, workflow automation and documentation. 

Key accountabilities/Responsibilities: 

• Prepare, reconcile and quality-check approved fraud datasets while maintaining confidentiality and access controls.

• Analyze fraud model and rule performance, including alert volumes, detection coverage, confirmed outcomes, false positives, false negatives, precision, recall and efficiency.

• Support analysis of fraud typologies, products, channels, customer segments, payment types and emerging patterns.

• Assist controlled testing and impact assessment of fraud rules, thresholds and analytical models.

• Support AI and machine learning use cases for detection, prioritization, anomaly identification and investigation assistance.

• Automate repetitive data preparation, reconciliation, alert-triage support, dashboard preparation and evidence collection using approved tools.

• Maintain dashboards, KRIs and KPIs for fraud trends, model effectiveness and operational efficiency.

• Capture investigation feedback and outcomes to support monitoring and future tuning.

• Support validation requests, UAT evidence, change records, issue tracking and remediation.

• Apply explainability, fairness, data quality, privacy, security, human oversight and auditability controls.

• Escalate unusual patterns, data concerns, unexpected model behavior and potential customer impact.

• Support fraud, risk sampling across products, sourcing channels and customer acquisition processes, including sample extraction, evidence collation, outcome tagging and follow-up of exceptions.

• Assist sampling reviews for application fraud, contact point verification, documentary checks, impairment indicators, syndicate-fraud signals and vendor or agency control monitoring.

• Prepare sampling MIS and trend analysis to highlight control gaps, recurring exceptions, turnaround-time adherence and areas requiring corrective action by Fraud Risk, Operations, Underwriting or business teams.

• Support controlled mystery-shopping, seeding, queue monitoring and alert-review analytics where required, ensuring findings are documented, escalated and linked to control improvement actions.

Education and experience:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Business Analytics, Finance, Economics or related discipline.

• Fresh graduate or up to two years of relevant internship or work experience.

• Foundation knowledge of statistics, data analysis and machine learning. Classification metrics or anomaly detection exposure is advantageous.

• Good knowledge of Excel and PowerPoint. Exposure to Python, SQL, R, SAS, Power BI or automation tools is advantageous.

• Strong analytical curiosity, pattern recognition, documentation and attention to detail.

• Ability to handle confidential information and follow data, access and change-control requirements.

• Working understanding of fraud sampling, application verification, contact point verification, preliminary investigation support, fraud MIS preparation and control-exception tracking are advantageous.

Early career development expectations:

• Complete required induction, risk, conduct, data protection and role-specific learning within agreed timelines.

• Develop from supervised task execution to reliable preparation of analyses, working papers, trackers and management materials.

• Seek feedback, demonstrate continuous learning and build practical knowledge of ADIB products, processes and risk governance.

• Use approved data, systems and AI tools responsibly, maintaining confidentiality, evidence and appropriate human review.

• Demonstrate integrity, professional judgement, collaboration and timely escalation of issues or uncertainty.

Indicative first-year success measures:

• Accurate and timely completion of assigned analysis, documentation, reporting and follow-up activities.

• Complete, traceable and well-organized records with minimal rework required.

• Constructive engagement with stakeholders and consistent adherence to approved governance and control requirements.

• Effective support to fraud sampling cycles, including accurate sample lists, evidence packs, exception trackers and concise MIS highlighting key themes and required follow-up.

• Visible development of technical knowledge, analytical capability and professional communication.

• Practical contributions to at least one controlled efficiency, automation or process-improvement opportunity.