BBVA Compass

  • Card Fraud Analyst

    Job ID
    FLSA Status
  • Responsibilities

    Future of Banking

    At BBVA, we’re working to make banking better for everyone. That’s where you come in. We’re looking for smart, team-oriented people who want to be part of a first-class workforce that gives people the tools they need to meet their financial goals, all while delivering an outstanding client experience.


    Digital transformation is at the heart of BBVA. It’s how we will achieve our purpose to bring the age of opportunity to everyone. Our purpose reflects the bank’s role as a facilitator, offering customers the best banking solutions, helping them make the best financial decisions and making a real difference to their lives. We live in the age of opportunities where technology offers universal access to education and offers many more people than ever before the possibility of embarking on projects and pursuing their dreams.


    Are you a visionary?  Are you revolutionary?  Our Engineering teams are charged with reinventing the banking industry.  We are revolutionizing how banking is done today and how it will be done in the future.  Our team is made up of risk taking, intellectually curious, entrepreneurs who want to create the future of banking.  


    What you will be doing.



    This role will provide strategic analysis of current transactional fraud and analytical supports for the credit and debit card portfolios. The Fraud Risk Analyst will be responsible for using a wide variety of analytical techniques to design fraud prevention solutions to reduce fraud and optimize fraud strategy performance.  




    • Develop and maintain fraud strategy for the Payments line of business, considering customer experience and operational workload when optimizing fraud detection to minimize fraud losses for the bank
    • Evaluate the effectiveness of existing strategies in use and recommend optimization within fraud prevention rules
    • Evaluate the effectiveness of existing models in use and recommend optimization within fraud prevention rules
    • Create and maintain strategy rule documentation / governance as appropriate
    • Develop analysis and reporting as needed to understand and communicate trends
    • Documentation of various model methodologies and assumptions to comply with SR 11-7
    • Explore quantitative segmentation strategies with advanced statistical techniques e.g. Logistic Regression, CHAID / CART Decision Trees
    • Analyze trends for Compromise Events to track bank impact & utilization in strategy rules
    • Build and foster relationships, gain operational understanding & document current business processes relating to fraud, and present findings / recommendations to management



    • B.S. in Statistics, Computer Science, Engineering, Applied Mathematics, Statistics, or other quantitative fields.
    • Experience managing and manipulating large relational data sources
    • 2+ years of modeling/analytics experience in financial industry
    • Advanced knowledge in at least one of the following: SQL, SAS, R, Python
    • Exposure to and familiarity with different analytical techniques (Linear and Logistic Regression, Clustering Techniques, Neural Network, Decision Trees, etc.).
    • Familiarity with wide array of fraud vendors, tools, applications and solutions (FICO, VISA, TSYS Falcon, Lynx, VRM, CardGuard, Determinator, EWS, Detica, etc.)
    • Strong interpersonal skills with the ability to interact with all levels of internal and external contacts.
    • Proven ability to work autonomously with minimal oversight to elicit buy-in and move projects forward
    • Proven ability to solve complex problems in a complex environment, translating business problems into recommendations that have measurable business impact
    • Strong interpersonal skills with the ability to interact with all levels of internal and external contacts, including senior management.
    • Ability to present findings and deliver recommendations to various levels of management
    • 2+ years Credit Card Industry Experience


    • Master’s Degree in a quantitative field
    • Understanding of advanced analytical techniques (Logistic Regression, Neural Networks, Machine Learning methodologies, etc.
    • 5+ Years Experience in Financial Services
    • 2+ years Consumer Banking Fraud experience  with exposure to different verticals (payment card fraud, check fraud, ach/wire, loans, etc.)
    • Spanish/English bilingual


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