Model Risk Management Lead - Ford Credit Bank

Ford Motor CompanySalt Lake City, UT
$94,800 - $166,200Onsite

About The Position

Ford Motor Credit Company is establishing Ford Credit Bank, a new de novo bank headquartered in Salt Lake City, Utah, with conditional regulatory approval. This bank aims to provide innovative banking solutions, including financing for Ford vehicles, parts, accessories, EV infrastructure, and software, as well as accepting FDIC-insured deposits. The Model Risk Management (MRM) Lead will be a key technical subject matter expert for the models and analytics used by the Bank, covering areas such as credit scoring, pricing, collections, financial crimes, and expected credit loss methodologies. This role will report to the Bank's Director of MRM and will be instrumental in executing the MRM program in accordance with the Bank's policies, procedures, and regulatory expectations. The MRM Lead will be responsible for the identification, assessment, validation, and ongoing monitoring of models and quantitative methodologies. New employees hired by the bank will initially be Ford Credit employees and may be transferred to the new bank once it is formally established.

Requirements

  • Technical subject matter expert for models and analytics.
  • Experience in credit scoring, pricing, collections, financial crimes, expected credit loss methodologies.
  • Understanding of MRM program execution in compliance with policy, procedures, and regulatory expectations.
  • Ability to identify, assess, validate, and monitor models and quantitative methodologies.

Responsibilities

  • Serve as the technical subject matter expert for models and analytics used to run the Bank.
  • Gain broad exposure across credit scoring, pricing, collections, financial crimes, expected credit loss methodologies, and more.
  • Assist in the execution of the MRM program in compliance with the Bank’s policy and procedures and regulatory expectations.
  • Ensure the appropriate identification, assessment, validation, and ongoing monitoring of models and quantitative methodologies.
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