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This position is within the Cards Credit Abuse/First Party Fraud Strategy Management team. Role highlights include working on credit abuse acquisition/ECM strategy development/maintenance for Cards, collaboration with multiple stakeholders like portfolio policy team, IT, regulators, compliance, and effective communication to senior management for various strategy changes.
Job Responsibility:
Lead end to end credit abuse strategy including development/enhancement, implementation, maintenance, MIS management etc.
Develops Risk Segmentation models by deploying sophisticated statistical techniques like CHAID, cluster analysis, pattern recognition etc. for credit abuse/first party fraud risk discrimination at Acquisition and Existing Customer Management stages
Work in establishing the swap set analysis and P&L optimization using the models
Hands on experience of Credit/Fraud Risk strategy development
Work closely with cross functional teams, including business stakeholders, MRM and governance teams, and strategy implementation teams
Implement initiatives to ensure consistency and compliance with global credit policies
Observe key credit abuse trends, threats, inaccuracies and drivers of those observations
Support Audit requirements from external/internal auditors & queries from Independent Risk
Strong analytic, strategic and project management skills
Effective communication is critical. Should be able to effectively provide updates and communicate key initiatives to senior risk management
Mentoring/Guiding junior resources – Drive projects as lead with junior resources
Should have the ability to manage different stakeholders – Risk Policy, IT, Regulators
Presentations to both technical and non-technical personnel are required to be made frequently as part of the job.
Requirements:
Under Grad/ Post Graduate degree with a specialization in Statistics, Mathematics, Engineering or other quantitative discipline
4+ years’ work experience required
Experience in strategy/model development in banking preferred
Preferred knowledge of credit/fraud risk analytics
Strong analytical skills in conducting sophisticated analysis
Experienced in developing, implementing and monitoring, that is end-to-end project management
Experience in statistical analysis with working knowledge of at least one of the following statistical software packages: SAS, Python, R
Highly proficient in Excel/pivot tables and PowerPoint
Tableau is a plus
Exposure to project/process management
Prior experience in leading a team of juniors or mentoring is preferred
Strong communication and presentation skills targeting a variety of audiences
A qualified candidate needs to be able to work with cross functional teams
Flexibility in approach and thought process
Ability to work effectively across portfolio risk policy teams and functional areas teams
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