Fraud Analyst

Job description

**Role Title** Fraud Transactions Analyst / Specialist UPI & Digital Payments **Experience** 4–7 years **Role Overview** We are looking for a Fraud Analytics Specialist with strong experience in UPI / TPAP transaction fraud prevention, fraud rule creation, and AML monitoring. The ideal candidate will have hands-on experience in analysing transaction patterns, identifying emerging fraud typologies, designing fraud detection rules, and working with analytics teams to reduce fraud losses while maintaining customer experience. The role requires a strong understanding of digital payments fraud, UPI ecosystem, transaction monitoring, risk controls, and data-driven decision-making. **Key Responsibilities** Fraud Rule Strategy & Transaction Monitoring • Analyse UPI transaction data to identify suspicious transaction patterns, fraud trends, and emerging fraud typologies. • Design, implement, and optimize real-time fraud detection rules across payment journeys. • Develop transaction monitoring strategies using parameters such as: o Transaction velocity o Device intelligence o User behaviour patterns o Transaction amount and frequency o Beneficiary risk signals o Geographic/IP/device anomalies o Account takeover indicators • Continuously monitor rule performance and optimize thresholds to improve fraud detection while minimizing false positives. Fraud Analytics & Investigation • Perform deep-dive analysis of fraudulent transactions to identify root causes and fraud patterns. • Create fraud segmentation frameworks and dashboards to track: o Fraud rates o Fraud losses o Detection rates o False positive rates - Rule effectiveness o Customer impact • Analyse customer, device, transaction, and behavioural data to identify risk signals. • Support investigation teams with data-driven insights on fraud cases. AML & Regulatory Monitoring • Support AML transaction monitoring activities for suspicious payment behaviours. • Identify patterns related to: o Money mule accounts o Account takeover o Phishing/social engineering fraud o Suspicious fund movement o Layering and rapid movement of funds • Assist in improving monitoring scenarios and risk-based controls. Fraud Control Optimization • Partner with product, engineering, operations, and risk teams to implement fraud prevention controls. • Evaluate impact of fraud controls on customer conversion and payment success rates. • Conduct post-implementation analysis of fraud rules and recommend improvements. • Stay updated on evolving UPI fraud trends and industry best practices. **Required Skills & Experience** Must Have • 4–7 years of experience in fraud analytics, transaction monitoring, risk analytics, or digital payments fraud prevention. • Prior experience in UPI / TPAP / payment aggregator / digital wallet fraud management. • Strong SQL skills and experience working with large transaction datasets. • Experience with analytics tools such as Python / R / SAS / Excel / BI tools. • Understanding of fraud metrics: o Fraud rate o Chargeback/fraud loss o Detection rate o False positives o Precision/recall of fraud rules **Preferred Experience** • Experience working with UPI ecosystem players: o TPAPs o PSP banks o Payment gateways o Digital wallets o Fintech platforms • Experience designing: o Real-time transaction monitoring rules o Velocity controls o Device/network-based fraud rules o Behavioural risk models • Exposure to machine learning-based fraud detection models. • Knowledge of RBI guidelines related to digital payment fraud and AML controls. **Technical Skills Required** • SQL (strong) • Data analysis • Fraud rule engines • Transaction monitoring systems • Excel / BI dashboards **Good to Have** • Python for analytics • Machine learning models • Device fingerprinting solutions • Graph/network analytics • Feature engineering