Digital Fraud Analytics Officer / Senior Officer

Bank Alfalah is seeking a data-driven and analytical professional to join its Fraud Risk Management Department in Lahore as a Digital Fraud Analytics Officer / Senior Officer. The role focuses on identifying and analysing fraud patterns across customer transactions, devices, and digital banking channels, while using advanced analytics and machine learning techniques to strengthen proactive fraud prevention. The successful candidate will investigate anomalies and emerging fraud risks, support the development and optimization of fraud detection rules and thresholds, develop analytical models and dashboards, and translate complex data findings into actionable fraud-risk mitigation strategies. The role will involve close collaboration with Business, Technology, Operations, Risk, and other stakeholders to improve fraud monitoring capabilities and support data-driven decision-making.

Key Responsibilities

• Analyze customer, transaction, device, and digital-channel data to identify fraud trends and anomalies.
• Conduct fraud-pattern analysis and root-cause investigations.
• Assess the effectiveness of existing fraud controls and monitoring mechanisms.
• Support the development, tuning, and optimization of fraud detection rules, thresholds, and scenarios.
• Develop analytical models to improve fraud detection and predictive risk identification.
• Explore and apply machine learning techniques to fraud analytics.
• Develop and maintain fraud dashboards, MIS reports, and management presentations.
• Generate actionable insights and recommend preventive and detective controls.
• Monitor fraud performance indicators and emerging digital fraud trends.
• Collaborate with Business, Technology, Operations, Risk, and other teams.
• Support fraud investigations and ad hoc analytical assignments.
• Assist with regulatory, management, and fraud-risk reporting.
• Translate analytical findings into practical recommendations for fraud prevention.

Requirements

• Bachelor's degree in Finance, Business Administration, Computer Science, Data Science, Data Analytics, Statistics, Risk Management, Machine Learning, or a related discipline.
• Relevant experience in fraud analytics, digital banking, data analytics, risk management, compliance, audit, financial services, or machine-learning applications is preferred.
• Strong analytical, problem-solving, and data-interpretation skills.
• Proficiency in Microsoft Excel and PowerPoint.
• Working knowledge of SQL, Power BI, Python, R, and machine-learning frameworks.
• Understanding of statistical modelling, predictive analytics, and data visualization.
• Knowledge of fraud detection and digital banking risks will be an advantage.
• Strong communication and presentation skills.
• Ability to convert complex analytical findings into clear, actionable business insights.

Preferred Technical Skills

• SQL – transaction and customer-data analysis
• Python/R – analytics and machine learning
• Power BI – fraud dashboards and visualization
• Excel – data analysis and reporting
• Machine Learning – anomaly detection and predictive modelling
• Statistical Modelling – fraud-risk identification and assessment