Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
Practice paper

Assessment of model risk in the aggregate: Contribution of quantification

Liming Brotcke and Raymond Brastow
Journal of Risk Management in Financial Institutions, 12 (1), 16-43 (2018)
https://doi.org/10.69554/PJHU4722

Abstract

The ability to assess model risk in the aggregate is desirable, as it provides senior management with information on the overall risk associated with models used by the organisation. More importantly, it enables effective challenges and hence a robust measurement by connecting isolated information in a transparent way. This paper introduces a quantitative element to the assessment framework that utilises various model statistics from model development and performance monitoring periods. The paper links the model life cycle concept to risk quantification within families of similar models by introducing two risk measures: the Model Robustness Index (MRI) and the Model Stability Index (MSI). MRI is used to evaluate individual models’ robustness and goodness of fit. MSI employs key ongoing monitoring metrics and can be used along with judgmental factors as a dynamic measure of risk as model performance changes over time. Next, the paper introduces an approach to establish thresholds for ongoing performance monitoring. The paper demonstrates the value of these concepts by applying them to an example using binary logistic regression, that is, a simple application of a machine learning algorithm.

Keywords: model risk; model life cycle; risk aggregation; SR 11-7; model validation

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Liming Brotcke is a quantitative manager at the Federal Reserve Bank of Chicago. She leads a team that supports large and Large Institution Supervision Coordinating Committee (LISCC) bank supervision across the Federal Reserve System. She has extensive modelling experience in the consumer lending and sufficient working knowledge of other modelling areas including wholesale, securities, market and liquidity, derivatives, and operational. Prior to joining the Fed, she worked at Citi Group and Discover Financial Services developing models and managing portfolios.

Raymond Brastow is a senior financial economist at the Federal Reserve Bank of Richmond. He participates in model reviews at large banks including the qualitative assessment of stress test models. Ray has actively published in academic journals, most recently in the field of residential real estate transactions. He has taught economics at several universities and is currently Emeritus Professor of Economics at Longwood University in Virginia.

Citation

Brotcke, Liming and Brastow, Raymond (2018, December 1). Assessment of model risk in the aggregate: Contribution of quantification. In the Journal of Risk Management in Financial Institutions, Volume 12, Issue 1. https://doi.org/10.69554/PJHU4722.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Journal of Risk Management in Financial Institutions
Journal of Risk Management in Financial Institutions
Volume 12 / Issue 1
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.