Manager - Fraud Strategy - NBFC

Fraud Strategy Manager - NBFC - Gurgaon

- Managing fraud Analytics for Fraud Prevention & Detection, impacting fraud loss along with FPR, Dispute rate, Fraud rate. Implement and drive customer segmentation to minimize fraud loss and enhance customer experience

Roles and Responsibilities :

Fraud Analytics and Management:

1. Continuously Analyze data on frauds & prevented frauds to Identify and implement rule strategies to reduce frauds, enhance customer experience and ensure regulatory compliance.

2. Use data science to identify upcoming fraud trends & plug process gaps.

3. Design and implement rules in the fraud monitoring systems (Falcon / Wibmo / Hunter) to control key fraud control metrics like FPR, ADR, VDR etc.

4. Apply consumer behavior patterns, key portfolio drivers and macro-economic indicators for improving forecast accuracy.

5. Build Machine Learning predictive models to detect fraud trends.

6. Prepare & publish reports for Management on various key indicators i.e. consumer transaction behavior, demographic indicators and key fraud drivers.

7. Build Fraud models using RPA for early detection / prevention of Frauds.

Stakeholder Liasoning and Process Improvement:

1. Liaison with internal stakeholders Credit, Sales, Marketing, Operations, IT, and CS to highlight fraud trends, suggest fraud prevention measures and take-up cross functional projects for process improvement.

2. Continuously engage with VISA, Mastercard, Amex, NPCI, Merchants, Fraud Engine Vendors WIBMO, Falcon, Experian, etc. to highlight fraud trends & keep SBI Card abreast with the latest trends & technologies in the market.

3. Analyze data to recommend Fraud Rules rationalization for Increased Fraud Catch and reduced False Positives,

4. Identify and suggest improvement areas for enhanced fraud mitigation, increased merchant reversals and enhanced throughput.

5. Monitor fraud trends and alert decisioning, feed back the learnings/observations into the system and training people for process improvements.

Desired Candidate Profile :

1. Good Knowledge of Analytics tools including SAS, SAS-VA, Python, R, SQL, Excel, Tableau

2. Fraud Engine Rule Writing & Review,

3. Indepth knowledge of Data Analytics for predicting and analyzing large data.

4. Knowledge of Data Analytics tools including SAS, SAS-VA, Python, R, SQL, Excel, Tableau etc.

5.. Knowledge of Data Science concepts & their application on large data.

6. Experience of generating reports, dashboards and performing analysis.