AVP - Fraud Analytics - Bank

Discipline - Banking

Subsector - Analytics

Location - Delhi NCR

About our Client : Our client is a leading global bank with significant growth plans for the India region, our client is embarking on the next stage of their development. As part of their growth & expansion plans they are looking for a seasoned analytics professional having strong background in Fraud modeling for their credit card portfolio.

Job Description : Reporting into the Risk Lead, you will be responsible to:

- Independently manage development and implementation of effective Fraud detection and prevention strategies that help mitigate fraud losses.

- Apply innovative analytical techniques to customer and transaction data to build risk mitigation strategies.

- Enable use of statistical tools and techniques such as - forecasting, segmentation, predictive analytics, Enterprise Miner, CART, etc.

- Identify new opportunities for enhancing, streamlining services through use of advanced analytics, automation and optimization

- Identify opportunities to reduce loss, enhance revenue by building new rules & strategies, collection strategies, cross sell, up sell models

- Process substantial interaction with Fraud Policy, Fraud Operations, Client Development and other functional business partners to optimize business strategies.

- Ensure consistent and timely delivery of analytics support to minimise losses and maximise profits through Root Cause Analysis, Trend Analysis, Impairment Analysis, Account management analysis, Scenario testing, Stress testing, Fraud analytics, Collections strategies, response models and loss reduction strategies

The Successful Candidate:

- 6+ years experience in the credit risk modeling domain for a banking/financial institution with good exposure to fraud model development

- Advanced degree in a quantitative subject, such as Mathematics, Operations Research, Statistics, Economics or Finance from a tier one institution

- Must have in-depth knowledge in applying Segmentation, classification/decision tree, Regression (Logistic, Linear) sequencing/association tools for credit risk/fraud model development

- Strong data handling, interpretive, and problem solving skills with the ability to process large volume of transaction level data and efficiently derive actionable results taking into consideration operational aspects and risk impacts

- Strong programming skills in SAS, MS Office (Power Point, Excel, Word)

What's on Offer: This is an excellent opportunity to develop your career within one of the prestigious financial services firms and head their fast growing analytics business.

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