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
tools for all portfolios.
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
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.
Qualification / Requirements:
8+ years of experience in Analytics domain with atleast 5 years in Consumer Credit / Fraud 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.
Strong written/oral communication skills.
Exposure to Big Data technologies
Knowledge of R/Python and other open source tools.
Ability to work in a matrix organization