Associate Analyst - Fraud Risk Management

Beschreibung:

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