Roles and Responsibilities:
- Conceptualize and implement early warning triggers & strategies from fraud perspective in both assets and liabilities
- Develop analytics to identify suspected frauds in both credit and non-credit areas
- Monitor 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 accuracy
- Design fraud monitoring framework through data analytics and collaboration with first line of defense
- Analyze historical data on EWS, RFA and credit frauds across industry to develop and implement EWS triggers
- Interpret data and present actionable insights to key stakeholders
- Lead collaboration between stakeholders – RCU, product, analytics, IT, BSG & business to design/implement solutions w.r.t. Fraud identification and monitoring
- Monitor & maintain fraud analysis solutions / models to improve efficiency & effectiveness
- Collaborate with FinTechs / external vendors for exploring on new ideas / innovations and implement the same
- Presentation 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 skills
- Good written and verbal communication skills
- Professional Qualifications - MSc Statistics/ MTech/BTech/MBA from Tier1 colleges or universities with CFE certification preferred
