AVP - Fraud - BFSI

We have job opening AVP Fraud Location hyderabad

Essential Functions/Responsibilities

Conduct analysis of ongoing fraud trends using historical authorization and fraud data to drive fraud strategies, reduce fraud losses and enhance customer experience.

Develop, implement, monitor and provide performance tracking of account management fraud strategies and fraud mitigation l tools for all .

Manage projects to ensure successful implementation of fraud strategies, tools and processes

Develop and maintain and monitor dashboards and reports designed to track portfolio losses associated with PLCC and DC portfolios.

Communicate fraud trends to Fraud Analysis and Strategy manager and senior leadership

Recommend counter measures to reduce fraud losses. Define & drive reporting standards with key focus on accuracy

Provide general consultancy to support to the business in their on-going use of scores and their generation and interpretation of scorecard monitoring reports

Work on a number of different projects simultaneously, of varying complexity and length.

Establishing priorities and coordinating work

Appropriate management of time and resources

Proactively manage efforts to maintain stakeholder satisfaction, and quantify project benefits delivered

Develop and support Best-in-class analytic solutions/algorithms

Provide thought leadership in various initiatives/projects

Influence Senior Management on new tools/solutions built by the team

8+ years of experience in Analytics domain with atleast 5 years in Consumer Credit / Fraud Analytics environment. Atleast 3 years of experience managing end to end project management

Masters or Ph.D. in Mathematics/Statistics, Operations Research, Economics, Computer Science/Engineering or other quantitative majors, or equivalent experience beyond Bachelors degree.

Deep experience with various Credit/Fraud Risk modeling & strategy building methodologies in a development role.

Big-picture understanding of Credit Risk & ability to communicate with business and technical stakeholders

Strong knowledge & hands-on experience of Logistical/Linear/Regressions CHAID / CART /

Clustering techniques, Optimization

Solid working knowledge of SAS, SQL, Unix, Excel.