SAS launches Advanced Credit Risk Solutions Course

Continuation of SAS Business Knowledge Series

Dublin, Ireland, 19. Jun. 2007 -  SAS, the leader in business intelligence, today announced the launch of their Advanced Credit Risk Solutions Course. The course helps financial institutions build effective and high-performing credit scoring systems as required under Basel II. The course is aimed at anyone involved in building scoring systems or responsible for monitoring a system's behaviour and performance. It is the second course in SAS' Basel II business knowledge series and follows the successful Credit Risk solutions course held earlier this year. Basel II requires that financial institutions calculate and aggregate market, credit and operational risk measures, provide transparency and comparability and minimise efforts and investments in risk management.

"The Advanced Credit Risk course is designed to provide the next level of education for Basel II practitioners. The course will go into more detail on the challenges arising when modelling loss given default (LGD) and exposure at default (EAD)," commented Martin Duffy, Head of Professional Services, SAS Ireland. 'This course is uniquely tailored for people involved in building scoring systems and is the only one of its kind running in Ireland.'

Advanced Credit Risk Modeling for Basel II will run from Wednesday 5th to Friday 7th of September 2007 at the New Horizons Computer Learning Centre, 22-24 Great Strand Street, Dublin 1. Dr. Bart Baesens from the School of Management at the University of Southampton will present this course. For more information, please visit www.sas.com/ireland/education/basel2.html. Places are limited so those interested in attending should book early by contacting Yvonne Adams by email Yvonne.adams@suk.sas.comor telephone +353 (1) 613 6400.

FOR FURTHER INFORMATION:
Siobhan Molloy/Louise Cassidy Weber Shandwick
Tel: 01 676 0168

About the Lecturers
Dr. Bart Baesens is Assistant Professor at the School of Management from the University of Southampton. His research focuses on the use of data mining and machine learning techniques for credit scoring and customer relationship management (CRM) applications. His findings have been published in various journals and presented at international conferences. He has already successfully organised this course on various continents where it has been attended by more than 200 people from financial institutions.

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