Business Analytics Sr Analyst – Fraud Utility, Credit Abuse, Assistant Vice President

The Business Analytics Sr Analyst is a seasoned professional role. Applies in-depth disciplinary knowledge, contributing to the development of new techniques and the improvement of processes and work-flow for the area or function. Integrates subject matter and industry expertise within a defined area. Requires in-depth understanding of how areas collectively integrate within the sub-function as well as coordinate and contribute to the objectives of the function and overall business. Evaluates moderately complex and variable issues with substantial potential impact, where development of an approach/taking of an action involves weighing various alternatives and balancing potentially conflicting situations using multiple sources of information. Requires good analytical skills in order to filter, prioritize and validate potentially complex and dynamic material from multiple sources. Excellent communication and diplomacy skills are required. Regularly assumes informal/formal leadership role within teams. Involved in coaching and training of new recruits. Significant impact in terms of project size, geography, etc. by influencing decisions through advice, counsel and/or facilitating services to others in area of specialization. Work and performance of all teams in the area are directly affected by the performance of the individual.

Responsibilities:

• This position is within the USCC Credit Abuse/First Party Fraud Strategy team as an individual contributor for managing Model/Strategy ruleset documentation, review and governance process
• Drive credit abuse (First party fraud) acquisition/ECM/Pay float strategy documentation and model governance for USCC portfolios
• Should have the ability to manage different stakeholders – FPF strategy teams, MRM, Fraud Modeling, Legal/compliance, IT, Regulators, Operations, Audit, governance teams etc.
• Knowledge and experience of credit card strategy build process and usage of various statistical models and on -us off us attributes for risk /fraud decision across credit life cycle. Should have knowledge of various KPI's pertaining to strategy/ model performance e.g. bad rate, good bad ratio, incidence rate, P&L drivers etc.
• Effective communication and collaboration with senior management and other stakeholders for various strategies and model changes.
• Monitor strategies built by the Strategy team in accordance with the Fraud modeling policies and procedures and MRM requirements.
• The resource would be interacting with the MRM and Policy teams on all problems pertaining to USCC portfolios. They would be working with Limitations, Root Cause Analysis and other monitoring related issues for USCC portfolios FPF strategies and models
• Understanding of Model monitoring concepts like KS, PSI, ROB, model classification, model materiality etc.
• Ability to deliver required model policy documentation pertaining to fair lending reviews, annual model validations, limitation requirements etc.
• Evaluates the control environment pertaining to Model governance by ensuring appropriate controls are in place.
• Coordinates audits, examinations, and deliverable requirements from internal and external reviewers by supporting coordinating activities.
• Has the ability to operate with a limited level of direct supervision.
• Acts as SME to senior stakeholders and /or other team members on matters of Model classification, monitoring and governance.
• Drive issue management, Corrective action plans, Milestone, issue remediations related to strategy execution with various issue management and governance teams
• Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
• Develop Risk Segmentation, Strategies for credit abuse/first party fraud risk identification at Acquisition and Existing Customer Management stages. Work in establishing the swap set analysis and PnL optimization using the models
• Develop recommendations to adjust credit abuse strategies by analyzing loss and financial performance and utilizing statistical scoring, segmentation, and regression and simulation techniques
• Participate in developing, testing, and optimizing abuse strategies, ensuring consistency and regulatory compliance, and assist in the implementation of those strategies, processes and other related initiatives

Education:

• Advanced Degree (Masters preferred) in Statistics, Applied Mathematics, Operations Research, Economics, MBA (Finance), or other highly quantitative discipline from top education institute

Qualifications:

• 7+ years relevant experience in banking/financial industry model monitoring or risk/fraud analytics role

• Experience in statistical analysis with working knowledge of at least one of the following statistical software packages: SAS, SQL, Python in Unix environment
• Highly proficient in Excel/pivot tables and PowerPoint with excellent presentation skills Experience in managing issues, Corrective action plan, milestone pertaining to issue management lifecycle  
• Excellent Interpersonal skills and ability to work well in a team environment collaborating across diverse groups
• Demonstrated understanding of Model/ruleset risk and monitoring requirements  
• Ability to prioritize and manage multiple projects simultaneously
• Credit card/Financial Industry regulatory policies, Strategy/Model performance indicators, Business Key performance indicators (delinquencies, losses, receivables etc.)  and procedures knowledge along with Citi issue management policy

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Job Family Group:

Decision Management

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Job Family:

Business Analysis

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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