Lead and manage the Fraud Analyst team to strengthen the company's fraud detection and prevention capabilities. The role is responsible for analyzing fraud data and emerging trends, optimizing fraud detection rules and models, identifying new fraud patterns, and developing fraud reports and dashboards to support management decision-making and minimize fraud risk and financial impact.
Key Responsibilities
Fraud Rule Optimization
- Monitor and evaluate the performance of existing fraud detection rules using key metrics such as Detection Rate, False Positive Rate (FPR), True Positive Rate (TPR), and Accuracy.
- Design, review, and optimize fraud rules and parameters based on evolving fraud patterns and business requirements.
- Analyze False Positive cases and identify opportunities to improve detection efficiency while maintaining effective fraud detection.
- Conduct testing and validation of new or modified fraud rules before production deployment.
- Perform A/B testing or pilot testing where appropriate to measure rule effectiveness.
- Monitor post-deployment rule performance and continuously optimize rules based on actual results.
- Maintain proper documentation of fraud rules, including rule logic, rationale, changes, and performance results.
Fraud Pattern Analysis
- Analyze transaction data, customer behavior, merchant behavior, and other relevant data sources to identify fraud patterns and emerging trends.
- Identify relationships, anomalies, and fraud networks across accounts, merchants, devices, IP addresses, transactions, and payment behaviors.
- Monitor emerging fraud typologies and new fraud techniques to ensure timely preventive actions.
- Conduct root cause analysis of fraud incidents and translate findings into preventive measures.
- Generate proactive fraud insights to identify potential fraud risks before significant losses occur.
- Collaborate with Fraud Operations, Risk, Product, Data, and Technology teams to share insights and strengthen fraud prevention capabilities.
Fraud Rule / Model
- Design, develop, test, and implement fraud detection rules and/or fraud detection models based on business risks and fraud scenarios.
- Identify and evaluate relevant data sources and features for fraud detection and model development.
- Evaluate model performance and continuously monitor model effectiveness after deployment.
- Review and recalibrate models based on changes in fraud patterns, transaction behavior, and business requirements.
- Maintain appropriate documentation and change management for fraud rules and models.
- Work closely with Data, IT, Product, and Technology teams to implement fraud rules and models into production systems.
- Establish appropriate monitoring mechanisms to identify model degradation and ensure continued detection effectiveness.
Fraud Report / Dashboard
- Develop and maintain fraud reports and dashboards to provide visibility into fraud trends, performance, and key risks.
- Define and monitor key Fraud KPIs/KRIs, such as Fraud Rate, Fraud Loss, Detection Rate, False Positive Rate, True Positive Rate, and Rule Performance.
- Analyze and summarize fraud trends, key findings, root causes, and business impacts for management.
- Develop management dashboards to support strategic and operational decision-making.
- Monitor the effectiveness and business impact of fraud prevention initiatives.
- Ensure fraud reporting is accurate, timely, reliable, and actionable.
- Continuously improve reporting and dashboard capabilities to provide meaningful insights to management and relevant stakeholders.
Leadership & Management Responsibilities
- Lead, manage, and develop the Fraud Analyst team to ensure strong analytical and fraud detection capabilities.
- Set team objectives, priorities, and work plans in alignment with the company's fraud prevention strategy.
- Review and provide guidance on fraud analysis, rule optimization, and model development.
- Monitor team performance and provide coaching and development opportunities.
- Promote a data-driven culture and the use of analytics for decision-making.
- Collaborate with key stakeholders, including Fraud Operations, Risk, Compliance, AML, Product, Data, and IT teams.
- Present fraud insights, trends, risks, and strategic recommendations to senior management.
- Drive continuous improvement in fraud detection processes, tools, rules, and analytical capabilities.
Qualifications
- Bachelor's or Master's degree in Data Analytics, Statistics, Mathematics, Computer Science, Information Technology, Finance, Risk Management, or a related field.
- Minimum 5 years of experience in Fraud Analytics, Risk Analytics, Data Analytics, Fraud Management, Financial Crime, or a related field.
- Minimum 2 years of experience in a leadership, supervisory, or senior analyst role.
- Strong understanding of fraud risks and fraud detection within e-Payment, Digital Payment, FinTech, or Financial Services environments.
- Strong data analysis and SQL skills.
- Experience with Python, R, Machine Learning, or BI tools such as Power BI or Tableau is preferred.
- Good understanding of Transaction Monitoring, Fraud Detection, and Fraud Risk Management.
- Strong ability to analyze large datasets and translate complex data into actionable business insights.
