BBVA Compass

  • Lead Fraud Risk Analyst

    Posted Date 2 weeks ago(12/5/2018 10:55 AM)
    EOE Statement
    Equal Opportunity Employer - Minority/Female/Disability/Veterans.
  • 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.  


    Learn more below.


    What you will be doing.


    This role will provide thought leadership relating to strategic analysis of current transactional fraud to support the credit and debit card portfolios. The Lead Fraud Risk Analyst will be responsible for using a wide variety of advanced analytical techniques to design, test and implement fraud prevention solutions to reduce fraud and optimize fraud strategy performance.   The Lead Fraud Risk Analyst will also be responsible for assuring the bank is in compliance with BBVA’s Model Governance standards as it relates to fraud model documentation and performance monitoring (SR 11-7).



    • Provide thought leadership in approaches relating to card fraud analytics
    • 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
    • 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
    • Drives the relationship with business partners and external vendors for model design, development, implementation, validation and model governance requirements
    • Continuously evaluate the effectiveness of existing models in use and recommend optimization within fraud prevention rules
    • Creating and maintaining model documentation and model monitoring as appropriate
    • Manage model risk management process on existing model inventory, including model overseeing validation, response to questions and assisting in development of action plans to address model deficiencies



    • M.S. in Statistics, Computer Science, Engineering, Applied Mathematics, or other quantitative fields.
    • Experience managing and manipulating large relational data sources
    • 5+ years analytics experience in Financial Services
    • 1+ years of modeling experience in financial industry
    • Proven data-mining and machine learning experience is required. Familiarity with different machine learning algorithms (Linear and Logistic Regression, Clustering Techniques, Neural Network, Decision Trees, etc.).
    • Advanced knowledge in at least one of the following software: SQL, SAS, R, Python
    • 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 drive positive results and move projects forward


    • Ph.D. in a quantitative field
    • 8+ Years Experience in Financial Services
    • 3+ years consumer banking fraud experience
    • 1+ year managerial experience
    • Spanish/English bilingual


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