Job Title

Roles and Responsibilities:Conceptualize and implement early warning triggers & strategies from fraud perspective in both assets and liabilitiesDevelop analytics to identify suspected frauds in both credit and non-credit areasMonitor efficacy of the analytical / predictive models implemented and advise updations/modifications Monitor effectiveness of triggers and rules set for fraud identification and suggest refinements/additional rules to improve efficacy and accuracyDesign fraud monitoring framework through data analytics and collaboration with first line of defenseAnalyze historical data on EWS, RFA and credit frauds across industry to develop and implement EWS triggersInterpret data and present actionable insights to key stakeholdersLead collaboration between stakeholders – RCU, product, analytics, IT, BSG & business to design/implement solutions w.r.t. Fraud identification and monitoringMonitor & maintain fraud analysis solutions / models to improve efficiency & effectivenessCollaborate with FinTechs / external vendors for exploring on new ideas / innovations and implement the samePresentation to relevant committees and senior management:Job Requirements:Candidate should have minimum 5-6 years’ experience in analytical/statistical modelling and data analytics in Fraud Risk with overall experience of at least 8 years. Prior experience in Analytics on Python/SAS is must. Candidate should have excellent logical thinking and solution building skills.Above average to advanced excel and presentation skillsGood written and verbal communication skillsProfessional Qualifications - MSc Statistics/ MTech/BTech/MBA from Tier1 colleges or universities with CFE certification preferred