The database utilizes a unique real-life case study approach and is designed to assist institutions with their analysis of external operational risk events. It is used as a qualitative tool, providing information on control breakdowns, event triggers, insight into why the losses occurred and lessons learned. Containing case studies on approximately 7,000 risk loss events, it is unrivalled in its depth of analysis and coverage.

Dan Mudge, Group Managing Director of Algorithmics said "The new FIRST interface was developed in consultation with clients and demonstrates our continued commitment and investment to our operational risk content business. We currently have over 85 global organizations, including banks, investment banks, insurance companies and buy-side firms as clients and we are constantly working with them to develop and improve the product.

"Careful analysis of past operational risk events can help risk managers understand the causative factors of what can go wrong and how it can impact their business. With over 20 years of in-depth research into operational risk events, and timelines for larger events, Algo FIRST can assist them to truly their critical risks and necessary controls."

The features of Algo FIRST 4.0 include:

• an updated Graphical User Interface
• the ability to search multiple organizations and firms
• the ability to create peer groups and do = trend analysis on events
• an updated search engine
• an undated reporting engine
• the ability for multiple users in organizations to share and clone queries

Further enhancements will continue over the course of the next year, developed in conjunction with client user groups, whilst always retaining the format and depth of the research underlying the case studies.

Separately, Algorithmics today announced that its Algo Credit Advisory practice has completed the first in a range of planned methodological templates to model the credit risk associated with low default porttfolios. The initial template covers hedge funds.

Dr. Colin Farquhar, Managing Director of the Algo Credit Advisory practice commented: "Banks around the world are facing significant challenges in preparing for Basel II, particularly in relation to internal rating methodologies. There are particular difficulties associated with traditionally low default loan portfolios, such as lending to hedge funds, especially where the counterparties may have no existing assessment of the quality of the underlying assets.

"To assist banks in assessing the credit risk underlying these loans in a consistent and verifiable way, we are developing a number of templates, using methodologies based on our extensive credit risk knowledge, credit risk assessment methodologies from Fitch Ratings and the wide range of clients we have advised on other aspects of Basel II in the past.

"These templates allow banks to align theory with reality, whilst satisfying regulatory reviews. The first template covers the credit risk banks take when lending to hedge funds. One of the main advantages of this template approach is to force consistency and clarity in a bank's internal rating methodologies, thus facilitating improved back testing of predicted credit ratings. Basel II regulations ideally require seven years of historical data, whereas for the instruments underlying some low default portfolios, there is little market recognized data available."

The Algo Credit Advisory team will tailor these templates to an individual client's requirements, in order to check the client's existing internal rating procedures, or to provide a consistent framework to calculate credit ratings where such rating data does not already exist. The low default portfolio templates can be used in conjunction with other Algorithmics' software solutions or with a client's internal software. Further templates under development cover brokers and insurance companies, with more to follow later.