VP - Global Fraud Management - Risk

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. 

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Vice President Expectations

• Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
• Manage and mitigate risks through assessment, in support of the control and governance agenda.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Embark your transformative journey as VP - Global Fraud Management lead. This team encompasses fraud analytics, strategy, and operations functions and supports the business units in maintaining fraud within their risk appetite while enhancing both customer and colleague experiences. Key responsibilities include supporting the business units by providing first-line defines fraud optimization analytics. The span includes development of strategic and tactical fraud detection and prevention systems and controls, optimal fraud detection and prevention strategies and solutions. The fraud analytics VP is responsible for management of the design and production of analysis and monitoring to improve fraud detection rule strategies, responding to emerging trends and attack. They must undertake analytical research and data acquisition with the aim of creating strategically important new ‘future state’ Fraud risk management and decision capability. They will be Leading a team of AVP’s to continuously optimize Fraud Detection Rules and Model strategies. This is team management role.

 To be successful in this role you should have experience with/able to lead:

• Strong Analytical skills and experience in analytics domain.
• Strategic thought and change leadership. 
• Self-starter and ability to lead, successful track record in leading through influence.
• People management and stakeholder management.  
• Strong SAS+SQL coding skills.

Some other highly valued skills may include.

• Prior working experience in Fraud domain.
• Knowledge of Fraud detection model and rule strategy optimization in Retail Banking, Credit Cards. Using Tsys, Falcon, Instinct, RSA solutions.
• Familiarity with PYTHON and AWS, Hive, Impala and Machine learning techniques (Random Forest, SVM etc.).
• Advanced statistical understanding, ideally working knowledge of statistical modelling, neural networks, and Machine Learning models.
• Knowledge of Fraud detection model and rule strategy optimization in Retail Banking, Credit Cards; using Tsys, Falcon, Instinct, RSA solutions.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.

This role is for Noida Location.