Lead Analyst of Fraud Model Risk (Operational Risk Sr. Officer)

New York, New York
September 16 2020
Job Description

Important Note: During the application process, ensure your contact information (email and phone number) is up to date and upload your current resume when submitting your application for consideration. To participate in some selection activities you will need to respond to an invitation. The invitation can be sent by both email and text message. In order to receive text message invitations, your profile must include a mobile phone number designated as 'Personal Cell' or 'Cellular' in the contact information of your application.

At Wells Fargo, we want to satisfy our customers' financial needs and help them succeed financially. We're looking for talented people who will put our customers at the center of everything we do. Join our diverse and inclusive team where you'll feel valued and inspired to contribute your unique skills and experience.

Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.

Corporate Risk helps all Wells Fargo businesses identify and manage risk. The team focuses on several key risk types, including conduct, credit, financial crimes, information security, interest rate, liquidity, market, model, operational, regulatory compliance, reputation, strategic, and technology risk. The group provides leadership, enhances communications, assists with problem identification and solutions, and shares best practices. In addition, the group provides an enterprise-wide view of risk, assists management and our Board of Directors in identifying and monitoring risks that may affect multiple lines of business, and takes appropriate action when business activities exceed the risk tolerance of the company.

The team:
Within Corporate Risk, Operational risk focuses on oversight of operational risks across the enterprise. The Corporate Functional Model Oversight (CFMO) team for External Fraud is part of the Operational Risk Coverage Programs team with responsibility of overseeing all models used across Wells Fargo businesses for external fraud detections, prevention, and management. These models are used by various functions in the bank to detect, prevent, and manage external frauds including but not limited to credit/debit card application fraud, loan application fraud, identify theft, account taking over, and transactional fraud.

The role:
The Lead Analyst of Fraud Model Risk (Operational Risk Sr. Officer) oversight will be a subject matter expert in quantitative modeling and risk management, particularly in fraud risk, financial crimes, model risk, compliance, and operational risk. The role is responsible and accountable for certain model life-cycle activities for external fraud models including but not limited to model identification, model risk ranking, performance monitoring, usage oversight, and change management. As a senior team member, the role is expected to lead the team in developing procedures and methodologies specific for external model risk oversight, and to collaborate with other stakeholders for other model life-cycle activities such as model validation and model governance.

The Lead Analyst will provide sound business perspective and practical understanding of how models are built and used, especially models used for managing external fraud and financial crimes, as well as anticipated model performance.

Specific responsibilities include:
  • Establish and maintain model risk oversight methodology and processes for external fraud models to ensure compliance with regulatory expectations, policies, and other standards specific to the function. The oversight methodologies and processes include but not limited to external fraud model identification guidelines, risk ranking methodology and template, performance monitoring guidelines, model development guidelines.
  • Lead and coordinate closely with stakeholders such as lines of business model governance and Corporate Model Risk (CMoR) governance to risk rank quantitative and qualitative external fraud models according to CMoR policy/procedure and model risk ranking methodology, and provide credible challenges to ensure risk rankings reflect inherent model risks.
  • Work closely with stakeholders to evaluate completeness of externa fraud models in the model inventory. Provide credible challenges for models, especially the ones with sizable model risk, but not included in the inventory.
  • Provides project management expertise and leadership to ensure plans are in place and progress is being made in resolution of model issues;
  • Lead and provide guidance in developing performance monitoring metrics, triggering thresholds and action plans for high risk rank external fraud models.
  • Review periodic model performance monitoring reports and provide credible challenges to model owners on performance deficiencies.
  • Provide credible challenges to model usage which includes model limitations/restrictions, input assumptions, robustness of output and incorrect or unapproved use of models.
  • Review and approve model changes and documented exceptions.
  • Review model development documents, validation findings, and implementation plans. Support model validation team as a subject matter expert if necessary.
  • Work closely with stakeholders to promote and ensure compliance with regulatory expectations for model risk management.
  • Assist in resolving audit and regulatory issues related to external fraud model risks.

Required Qualifications

  • 10+ years of experience in risk management (includes compliance, financial crimes, operational risk, audit, legal, credit risk, market risk, IT systems security, business process management) or 10+ years of financial services industry experience, of which 7+ years must include direct experience in risk management

Desired Qualifications

  • Excellent verbal, written, and interpersonal communication skills
  • Ability to articulate complex concepts in a clear manner
  • Strong strategic and conceptual thinking skills
  • Strong analytical skills with high attention to detail and accuracy
  • Advanced Microsoft Office skills
  • Ability to work independently
  • Ability to organize and manage multiple priorities
  • Leadership skills including the ability to influence effectively in a matrix environment

Other Desired Qualifications
  • 5+ years experience in model risk management or model development, or a combination of both
  • Master's Degree or higher in quantitative disciplines such as economics, computer science, statistics, engineering, mathematics, or equivalent work experience.
  • Experience as a model developer or validator, or in a model risk management role. Experience and knowledge of statistical modeling and machine learning techniques, such as regression analysis, time series analysis, multivariate analysis, and supervised and unsupervised learning.
  • Experience and knowledge with quantitative modeling tools such as Matlab, R, SAS, and Python.
  • Fraud and Identity Theft Program experience and expertise with additional expertise in Policy, Governance and Business Oversight.
  • Meaningful knowledge of an enterprise risk management framework, including: risk identification, risk appetite and strategy, risk-related decisions, processes and controls, risk analytics and governance
  • Strong interpersonal, influencing, and communications skills with an ability to interact effectively with stakeholders across the organization, which includes virtual, matrixed leadership experience

Job Expectations

  • Ability to travel up to 10% of the time


All offers for employment with Wells Fargo are contingent upon the candidate having successfully completed a criminal background check. Wells Fargo will consider qualified candidates with criminal histories in a manner consistent with the requirements of applicable local, state and Federal law, including Section 19 of the Federal Deposit Insurance Act.

Relevant military experience is considered for veterans and transitioning service men and women.
Wells Fargo is an Affirmative Action and Equal Opportunity Employer, Minority/Female/Disabled/Veteran/Gender Identity/Sexual Orientation.

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