Wells Fargo

Job Category:



Minneapolis, Minnesota


United States

Postal Code:


Approximate Salary:

Not Specified

Position Type:

Full Time


415) 820-7800

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Credit Risk Analytics Consultant 3

Wells Fargo - Minneapolis, Minnesota

Posted: 09/22/2018

Job Description

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. We focus on three key risk areas: credit risk, operational risk and market risk. We help our management and Board of Directors identify and monitor risks that may affect multiple lines of business, and take appropriate action when business activities exceed the risk tolerance of the company.

The Credit and PPNR Modeling (CaPM) Team is a unit within Corporate Credit and Market Risk and is responsible for model development and implementation of the following model types:

  1. Credit loss estimation models for the entire loan portfolio to support Allowance for Credit Loss (ACL), including preparations for Current Expected Credit Loss (CECL); estimation of risk weighted assets (RWA) in compliance with Basel regulations; and, economically sensitive credit loss estimation in compliance with Dodd Frank and the Comprehensive Capital Analysis and Review exercises (CCAR).
  2. Models to support Pre-Provision Net Revenue (PPNR) estimates including forecasting models to support Dodd Frank and the Comprehensive Capital Analysis and Review exercises (CCAR).

The team is seeking an Analytic Consultant to focus on the implementation and execution of Credit and PPNR models in support of the Corporate and Regulatory (CCAR/DFAST) Stress Tests and ACL/CECL/IFRS9 processes.

This position resides within CaPM Model Implementation and Production (MIP) team and will work closely with model development teams and business partners on the implementation of models for production and to support model execution, performance monitoring, and reporting. Asset types include one or more of the following: retail, commercial, and PPNR.

This position joins a high functioning, high profile team and requires strong SQL/SAS programming and data analysis skills; ability to understand complex loss and PPNR forecasting models; possess organizational and prioritization skills; as well as strong attention to detail. This role is highly dynamic and will require critical thinking and a tactical approach to problem solving.

The person in this role will work with others within CaPM who are responsible for developing models of credit performance for each of these three areas to ensure that the data they are using to create their models is accurate, comprehensive, and suited to purpose. He or she will collaborate across Corporate Risk, the Lines of Business, and the Finance organization to ensure that complete and accurate historical data is available. They will be responsible for enhancing the data so that it is consistent across the time periods used for modeling. This will involve the creation of additional data elements so that historical data values can be translated to be comparable to current data values to support analyses that cover 10 years or more of historical results. They will also maintain and enhance an appropriate data process control framework for data quality monitoring and review which will effectively adhere or surpass regulatory and audit standards. They will be responsible for ensuring that the data are updated and reconciled each month and that discrepancies are appropriately handled according to policy and the needs of the model developers.

The responsibilities of this position include the following:

  • Providing data support for CCAST’s modeling efforts to ensure that Probability of Default, Exposure at Default, and Loss Given Default models for wholesale exposures and Loss Forecasting models for commercial/wholesale Allowance and Stress Testing purposes are able to comply with regulatory and Corporate requirements and are responsive to regulatory, Corporate Model Risk (CMOR) and internal and external Audit feedback.
  • Data Support responsibilities include but are not limited to providing monthly and quarterly data to end users, perform data quality checks, represent CCAST end users’ interests in various data forums and upstream data providers’ meetings/calls, actively engage in and perform necessary data governance and compliance related activities.
  • Understanding data systems of record and data warehouses that support the exposures covered by the team.
  • Understanding the requirements for the modeling database.
  • Performing analyses to verify the completeness and accuracy of data added to the database.
  • Researching discrepancies and taking action consistent with procedures to remediate problems.
  • Ensuring that data issues and prioritization of data remediation needs are effectively communicated throughout CCAST and to our Corporate Risk, Technology and LOB partners.
  • Ensuring appropriate controls are established to protect the integrity of the data
  • Establishing strong controls and creating consistent and robust execution processes across models
  • Developing analytics around model results for enhancing forecast performance
  • Understanding the trends within loan portfolios, their impact on model performance, and quantifying the risks not captured by models via management adjustments
  • Maintaining documentation for key implementation processes across the team with focus on standardization of implementation and execution controls
  • Performing related tasks as needed.

Please Note: Based on the volume of applications received, this job posting may be removed prior to the indicated close date. If you do not apply prior to the closing of this posting, we encourage you to apply for other opportunities with Wells Fargo.

Required Qualifications

  • 7+ years of risk reporting experience, risk analytics experience, or a combination of both
Desired Qualifications

  • Excellent verbal, written, and interpersonal communication skills
  • Extensive knowledge and understanding of research and analysis
  • Strong analytical skills with high attention to detail and accuracy
  • Ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment
  • Ability to interact with integrity and a high level of professionalism with all levels of team members and management
  • Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment
  • Knowledge and understanding of SQL or SAS
  • Ability to execute in a fast paced, high demand, environment while balancing multiple priorities
Other Desired Qualifications
  • A deep understanding of data and analytics across multiple product classes, systems, and organizations.
  • Demonstrated excellence at identifying stakeholders, understanding needs, and driving to resolution.
  • Demonstrated excellence at developing sound model execution or reporting processes, evaluating, and enhancing existing processes.
  • Knowledge of SR15-18, BCBS 239 and other regulatory requirements on data and model usage/applications.
  • Experience creating documentation of code used for audit and/or training of other programmers
  • Experience with UNIX/LINUX environments

  • 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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