Algorithmics launches Algo First 4.0
The repackaged and updated operational risk database emphasises real-life relevance, says Algorithmics
TORONTO / LONDON – An updated version of the Algo First database of operational risk events has been launched. Algo First’s database relies on a case-study approach to operational risk-loss events – emphasising real-life relevance. The qualitative approach employed aims to provide causal explanations and applicable advice for event triggers and control breakdowns, through analysis of case studies covering around 7,000 risk-loss events.
“We hold global user conferences and the work we did on updating the front end of the First database reflects input from the entire client base,” says Dan Mudge, Algorithmics’ group managing director for op risk and content. Algorithmics also emphasises the importance of the database’s reports on clients’ peers in comparing operational risk exposure and management. The system enhancements aim to facilitate peer comparison. “We created the ability to generate these peer reports in the system instead of having to create them offline,” says Penny Cagan, head of research at Algo Op Vantage.
Cagan says the qualitative nature of its case-study approach assists with a wide range of issues, including cultural issues and viability of certain business models. “Our clients use the cases for inputs into self assessments, training initiatives, new product research and scenario models,” she says.
Mudge also highlighted the database’s role as an “institutional memory”, allowing clients to store, manipulate and retrieve case studies for scenario analysis. The increasing use of scenario analysis, according to Mudge, facilitates the use of cases as real-life examples when they are working on creating scenarios and envisioning what could happen to them.
In the current market volatility, case studies involving troubled institutions such as Northern Rock are under consideration. Cagan says that the case studies are “constantly being updated – especially in this volatile market environment”.
Ongoing enhancements are expected over the coming year, developed in conjunction with client user groups, and retaining the multi-tiered format and depth of the research underlying the case studies. “We are developing about a dozen further enhancements, including email alerts and automatic notification when new events are added to the database that match saved search criteria and peer reports,” says Cagan.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
How AI agents can join the dots for risk managers
Citi risk expert outlines agentic AI tool that would pull together structured and unstructured data on trading and lending approvals to create single, unified view of risk
The interplay between liquidity and collateral
The evolution of financing solutions as institutional investors raise and preserve cash
Do banks still need to validate GenAI models?
Regulators carved out GenAI models from new risk guidance. Banks shouldn’t see this as a reason to stop validating them.
FSB warns of ‘circles of risks’ in bank risk transfer deals
Credit lines, portfolio financing and NAV facilities for private credit funds could rebound on banks
Barclays built a risk framework for GenAI from scratch
Eleven teams contribute to assessing generative AI use cases in a system that includes 35 controls
Hopes, fears and ‘mass confusion’: the sudden end of SR 11-7
Banks welcome chance to prioritise model reviews, but fret over future policy changes and AI
Bootcamps and peer pressure: Goldman preps staff for AI future
Isda AGM: Tone from the top is not enough, says chief information officer Marco Argenti
In Iran war, VAR models ease cliff effect on Ice and CME margins
At 105%, EEX – using Span model – saw largest single-day jump compared with those CCPs