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

Causal analysis of operational risk for deriving effective key risk indicators

Lasse B. Andersen, David Häger and Hilde B. Vormeland
Journal of Risk Management in Financial Institutions, 9 (3), 289-304 (2016)
https://doi.org/10.69554/UDPX5085

Abstract

Key risk indicators (KRIs) are intended to track operational risk exposure and provide early indications of potential severe losses. Guidance on establishing the most effective KRIs for financial institutions is, however, limited and, as a result, KRIs are typically derived from an institution’s available metrics, often leading institutions to compensate for a lack of effective KRIs by increasing the number of KRIs monitored. Strengthening the ability to identify and evaluate KRIs’ effectiveness could increase the value of each KRI, further reducing the number of KRIs necessary and increasing the overall value of institutions’ KRI framework. This paper proposes a theoretical foundation and method for identifying and evaluating effective KRIs. The proposed solution originates from research on causal analysis of operational risk, particularly using Bayesian networks. It was found that high-frequency and tail events can be related to a shared set of causes which can be exploited for the identification and evaluation of two categories of KRIs: (1) shared causes that constitute major risk drivers; and (2) high-frequency events providing a strong indication of changes in exposure to low-frequency, high-severity events. Applying the suggested method, financial institutions can map and evaluate current and potential KRIs, ensuring reliable monitoring of the operational risk exposure level.

Keywords: operational risk; key risk indicators; causal modelling; Bayesian networks

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Lasse B. Andersen is a professor II in risk management at the University of Stavanger, Norway. Lasse has considerable research experience within several industrial sectors and has more than 20 years of experience with risk analysis in different sectors such as oil & gas and banking & finance. Lasse is currently CEO of Combitech Norway.

David Häger is an associate professor II in risk management at the University of Stavanger, Norway. He is a civil engineer and holds a PhD in stochastic modelling and analysis of operational risk in financial institutions from the University of Stavanger. From 2007 to 2014 he participated in a research project with five Norwegian banks on operational risk management and has more than 10 years of industry experience with risk analysis and risk management.

Hilde B. Vormeland holds a MSc in economics and currently is a PhD candidate in operational risk management in financial institutions at the University of Stavanger, Norway. She started her PhD in 2012, which is part of a research project on operational risk management with five participating Norwegian banks. David Häger is her main supervisor for the PhD.

Citation

Andersen, Lasse B., Häger, David and Vormeland, Hilde B. (2016, June 1). Causal analysis of operational risk for deriving effective key risk indicators. In the Journal of Risk Management in Financial Institutions, Volume 9, Issue 3. https://doi.org/10.69554/UDPX5085.

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 9 / Issue 3
© 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.