Head of Retail Bank Fraud Business Analytics Director

Head Of Retail Bank Fraud Business Analytics Director

This critical leadership role within Citi's Fraud Analytics and Modeling organization is responsible for strategically leading all fraud prevention and detection efforts across the Retail Bank's digital payments, wires, and checks. The role involves managing a team of teams to leverage data, identify emerging fraud trends, and design and implement advanced strategiesincluding those using AI and automationto prevent and mitigate all types of fraud attacks, from application fraud to sophisticated digital schemes. This leader will collaborate closely with various internal partners, including Financial Threats, Fraud Policy, and Operations, as well as business executives, to ensure fraud strategies are integrated, effective, and responsive to evolving business, technology, and threat landscapes, ultimately protecting both Citi and its customers.

Responsibilities:

• End-to-end ownership of Retail Bank Fraud Analytics across Fraud lifecycle.
• Ownership of New Deposit Account as well as Early Months on Book Deposit Fraud.
• Ownership and management of fraud rules, scores, and detection strategies, Risk appetite execution, POS interdiction strategies and defect analysis.
• Drive Digital fraud analytics using available digital fraud tools (i.e. TMX, BioCatch, etc.) for Cards and Retail Bank new applications and digital transactions.
• Leverage global cutting-edge techniques and thought leadership to drive innovation, while maintaining end-to-end view of business needs/goals.
• Continually assess manual and automated processes to identify potential process gaps and opportunities to strengthen risk and controls.
• Establish network and followership within and outside Fraud to drive cross-function collaboration.
• Champion organizational agenda and initiatives with executive audience.
• Integrate/connect team initiatives, actions and culture to drive a broader vision and support business goals.
• Effectively mentor and coach direct reports and cross business partners; attract new talent and build diverse talent pipelines.

Knowledge/Experience/Technical Skills:

• Interdiction strategy experience that goes beyond theory. Practical experience with building and deploying real-time interdiction logic, understanding the trade-offs, ability to speak to both operational impact and customer experience.
• 10+ years in fraud or risk management; experience in analytics and modeling or relevant area preferable.
• Extensive quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis.
• Extensive experience working with Big Data environment, coding within various traditional (SAS, SQL, etc.) and/or open source (i.e. Python, Impala, Hive, etc.) tools, and advanced machine learning techniques.
• Understanding of the threat landscape, as well as impacts of macroeconomic, industry, regulatory and fraud trends.
• Decisive with the ability to formulate and communicate a vision that is forward thinking and responsive to changes in the environment.
• Ability to effectively engage and inspire small and large audiences for collaboration and innovative changes.
• Experience with large scale Fraud organizations within financial services or related industry with a strong knowhow of Retail Bank payments and products.
• 8-10+ years of managing staff at various levels; experience in leading teams of Data Analysts / technical professionals.

Personal Qualities:

• Excellent written and verbal communication skills; ability to report back findings in a structured, clear and simple way that is understandable to non-technical partners.
• Hands-on, high-impact, leader that inspires confidence, can build and lead a team, shape a vision, drive execution and exercise sound judgement and decision making on behalf of the organization.
• Ability to collaborate across fraud, product, technology, and compliance partners.
• Strong business acumen and an executive presence.
• Superior planning and organizational skills; results oriented with ability to execute.
• Able to be independent and a self-starter, comfortable in a fast-paced matrixed and ambiguous environment.
• Acts with curiosity and takes the initiative to identify problems, offer creative solutions and resolve issues. Energized by asking "what if", "why not", and "what would happen to us if" questions, e.g. how this will affect the business, industry, or market.
• Passionate about data science and the value that can be created through information analysis.

Education:

• Master's Degree or PhD required in statistics, mathematics, physics, economics, engineering or other analytical or quantitative discipline.