Risk:Fraud Risk Analyst

Senior Manager - Fraud Risk Analytics

• Support the Head - Digital and Fraud Risk analysis in driving a data-led fraud risk analytics strategy for retail products and digital banking processes.
• Assist in execution of the Blaze rules engine orchestration program by coordinating with Risk, Technology, Product, Operations, and other stakeholders.
• Support implementation of the Fraud Risk Governance Framework, with focus on data, modelling, rule effectiveness, and control outcomes.
• Contribute to development of fraud rule strategies, decisioning frameworks, early warning triggers, and risk-based controls.

• Perform advanced data analysis and data handling to identify fraud trends, emerging risks, and control gaps across liability and digital banking processes.
• Support development and enhancement of fraud rules, triggers, early warning indicators, and risk-based decisioning logic.
• Assist in model orchestration execution, including rule configuration, testing, implementation, monitoring, and post-implementation review.
• Work with large datasets using SAS, SQL, BDL, and similar platforms for extraction, transformation, validation, and analysis.
• Develop and maintain Tableau / Power BI dashboards for fraud monitoring, control tracking, and senior management reporting.
• Support automation and enhancement of MIS, reporting, and exception monitoring frameworks.
• Analyze fraud incidents and loss events to identify process gaps, control weaknesses, and corrective actions for non-recurrence.
• Ensure data integrity, quality, and completeness across fraud risk systems, dashboards, and reporting outputs.
• Assist in model-related activities, including data validation, model testing, output validation, and performance monitoring.
• Coordinate with cross-functional teams and track execution of agreed deliverables, dependencies, and timelines.
• Support RCSA, control testing, and risk assessments for liability, onboarding, and digital banking processes

• MBA / Postgraduate with strong academic background preferred disciplines include Statistics, Econometrics, Mathematics, Data Science, or related quantitative fields.
• 5-10 years of experience in Banking, Fraud Risk, Analytics, Digital Risk, or related risk management functions.
• Experience in fraud analytics, modelling environment, rule-based decisioning, or quantitative risk will be preferred.

Technical & Analytical Skills

• Strong hands-on experience in SAS, SQL, BDL / big data platforms, data mining, data handling, and large dataset analysis.
• Experience in Tableau / Power BI for dashboarding, visualization, exception monitoring, and senior management reporting.
• Understanding of statistical techniques, modelling approaches, and analytical problem solving will be preferred.

Modelling & Governance

• Exposure to fraud / risk models, decisioning frameworks, model validation, testing, monitoring, and performance tracking.
• Ability to align model outputs with rule-based execution systems.

Domain Knowledge

• Understanding of liability products, CASA onboarding, digital banking, payments, fraud typologies, and control mechanisms.

Behavioral Skills

• Strong analytical, problem-solving, communication, and presentation skills, with ability to articulate insights to senior stakeholders.
• Strong stakeholder coordination and collaboration ability across Risk, Technology, Product, Operations, and Business teams.
• Ability to work in a fast-paced, execution-oriented environment with high attention to detail and ownership mindset.

Candidates with prior experience in fraud analytics and exposure to model governance within banking or fintech environments will be strongly preferred.