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:

• Bachelors 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.