Senior Fraud Analyst

Job description

- Analyze end-to-end lending lifecycle data (application, onboarding, bureau, repayment, device) to identify fraud patterns and high-risk segments - Track key fraud indicators such as First Payment Default (FPD), Early Payment Default (EPD), and abnormal delinquency trends - Perform deep-dive analyses and root-cause investigations on fraud spikes, portfolio deterioration, and channel-level risks - Support development, testing, and optimization of fraud rules, score cut-offs, and risk triggers to balance fraud capture and customer experience - Build and maintain analytical datasets (feature marts) by combining internal and external data sources for fraud detection and monitoring - Collaborate with Fraud Control Unit (FCU), Risk, Credit, and Business teams to provide data-backed insights and investigation inputs - Develop and maintain fraud monitoring reports and dashboards using tools such as SQL, Python, and Power BI - Assist in exploring new data sources (bureau, alternate data, device, telecom, etc.) and contribute to their evaluation for fraud use cases - Support development of machine learning models and analytical frameworks for anomaly detection, behavioural segmentation, and fraud risk prediction - Leverage basic Generative AI tools (LLMs, prompt-based workflows) for exploratory analysis, summarisation of fraud cases, and signal identification - Participate in POCs and pilot programs to evaluate new fraud detection techniques, models, and data capabilities - Translate identified fraud patterns (e.g., synthetic identities, mule accounts, sourcing fraud) into actionable analytical features and rules - Present insights, findings, and recommendations to stakeholders in a clear and structured manner - Strong analytical experience in fraud/risk analytics for digital or retail lending portfolios. - Ability to work with large datasets and derive actionable insights for fraud detection and risk mitigation.