Sponsor's article> An Integrated Approach to Operational Risk Management
Over the last several years, major financial institutions around the world have struggled with a number of questions that have arisen as a result of challenging regulatory directives. Included among these are:
Over the last several years, major financial institutions around the world have struggled with a number of questions that have arisen as a result of challenging regulatory directives. Included among these are:
• How do I develop a standardized approach to capture and analyze internal loss data across the organization?
• How do I validate and benchmark my internal loss data against relevant external loss data?
• What is the most effective way to qualitatively assess the risks and controls of our businesses?
• How can I draw on lessons learned (and millions lost) at other financial institutions to create scenarios to understand strategic exposures?
• Who should be responsible for what, and how do I integrate all of this qualitative and quantitative information to get a clear sense of my firm's overall operational risk and exposure?
As institutions strive to develop and implement sensible, integrated operational risk frameworks to address these directives, a number of best practices have emerged. For example, many banks have learned that it is critical to assign responsibility for internal loss data to those individuals who have sufficient information to report and assess losses - and to empower these same individuals to put in place corrective actions to mitigate future losses. This information can in turn be used to inform group-level risk and control self-assessment processes.
Similarly, when it comes to validating internal data against external "peer" data, or to reviewing risk and control assessments and conducting "what-if" scenario analyses, managers with strategic and P&L responsibility for the business are best-positioned to make the relevant comparisons and analysis. Finally, as it relates to modeling, many quants are well along in their understanding of the sensitivities of the factors that are likely to either overstate or understate their aggregate loss, and they are adjusting their models accordingly.
While the progress made by global financial leaders in a few short years is considerable, new challenges continue to emerge. Many of these challenges stem from the difficulties that arise when firms try to integrate the detailed internal loss data and risk and control assessments prepared by hundreds, or even thousands, of individuals in business units across an organization, with the strategic assessments conducted several levels up by a handful of seasoned business leaders. Operational risk managers at many global institutions are now working to develop integration processes to prevent disconnects, and to control for potential bias in both quantitative data and the qualitative assessments before developing an aggregate estimate of their companies' overall capital requirements.
Understanding how all the pieces fit together upfront can help ensure that the right people are involved and the right processes are employed, and can help to prevent institutions from committing resources to efforts with marginal value. Getting the top-down, bottom-up linkages in place, and applying appropriate techniques to minimize the inherent bias in expert risk assessments, will help ensure that meaningful operational risk data is being used to not only generate the best possible estimates of operational risk capital but also to provide proper incentives and the transparency that business managers require to make decisions that will most benefit the organization.
A Partner on the Road to Best Practices
At Algorithmics, the Algo OpVantage Advisory team works in partnership with some of the world's most respected financial leaders to develop practical solutions to measure and manage operational risk. The Algo OpVantage Advisory team is comprised of industry thought leaders, former regulators and risk practitioners who have developed an integrated methodology and assisted world-class financial institutions implement sound operational risk frameworks. The team works with clients to identify emerging risks, promote a greater understanding of risk exposure through capital measurement, encourage proactive communication through lessons-learned initiatives, and meet the regulatory and reporting requirements of Basel II AMA and Sarbanes Oxley.
ALGO OPVANTAGE INTEGRATED METHODOLOGY: Software, Services, Advisory and Content
Founded in 1989, Algorithmics is the world's leading provider of enterprise risk management solutions and services that enable financial institutions to effectively understand and manage their financial risk. Algorithmics has over 200 clients, including more than 60 of the 100 largest financial institutions in the world. Algorithmics was recently recognized as the dominant enterprise risk solution provider in market, credit and operational risk in Risk Magazine's 2004 Technology Rankings.
To learn more about Algorithmics, visit: www.algorithmics.com.
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
More on Risk management
Too ’Berg to fail? What October’s Instant Bloomberg outage means for the industry
The ubiquitous communications platform is vital for traders around the globe, especially in fixed income and exotic derivatives. When it fails, the disruption can be great
SEC leadership change puts Treasuries mandate under scrutiny
FICC clearing models approved, but critics think delay could revive prospects of done-away trading
Markets Technology Awards 2025: Untangling the knots
Vendors jockeying for position in this year’s MTAs, as banks and regulators take aim at counterparty blind spots
Risk Awards 2025: The winners
UBS claims top derivatives prize, lifetime award for Don Wilson, JP Morgan wins rates and credit
An AI-first approach to model risk management
Firms must define their AI risk appetite before trying to manage or model it, says Christophe Rougeaux
BofA sets its sights on US synthetic risk transfer market
New trading initiative has already notched at least three transactions
Op risk data: At Trafigura, a $1 billion miss in Mongolia
Also: Insurance cartels, Santander settlement and TSB’s “woeful” customer treatment. Data by ORX News
Cyber risk can be modelled like credit risk, says Richmond Fed
US supervisors may begin to use historical datasets to assess risk at banks and system-wide