DocumentCode :
1878745
Title :
An Intelligent Decision Support Model for Actuarial Profession
Author :
Zhou, Harry ; Ashby, Tova
Author_Institution :
Dept. of Comput. Sci., Towson Univ., Baltimore, MD, USA
fYear :
2009
fDate :
27-29 May 2009
Firstpage :
140
Lastpage :
143
Abstract :
As actuarial analysis and evaluation is a time-consuming, complex and error-prone process, it can be improved or enhanced considerably by automated reasoning. Efforts to reduce the inaccuracy and incorrectness of analyses and to enhance the confidence levels of actuarial analysis have led to the development of an intelligent decision support system called ActuaExpert, which assists, not replaces, actuaries. ActuaExpert assumes the role of a hypothetical actuary capable of assessing risks, creating policies that minimize risk and its financial impacts on companies, and maximizing the profits for insurance companies. It has a knowledge base containing the expertise of statistics, finance, and business, and a case base of past episodes and consequences of decisions. By combining knowledge-based problem solving with case-based reasoning, ActuaExpert demonstrates forms of intelligent behavior not yet observed in traditional decision support systems and expert systems.
Keywords :
case-based reasoning; decision support systems; expert systems; financial data processing; risk management; ActuaExpert; actuarial profession; automated reasoning; case-based reasoning; error-prone process; expert systems; financial impacts; intelligent decision support model; knowledge-based problem; Artificial intelligence; Business; Companies; Decision support systems; Expert systems; Finance; Insurance; Intelligent networks; Statistical analysis; Statistics; case-based reasoning; decision support systems; expert systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09. 10th ACIS International Conference on
Conference_Location :
Daegu
Print_ISBN :
978-0-7695-3642-2
Type :
conf
DOI :
10.1109/SNPD.2009.100
Filename :
5286678
Link To Document :
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