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A Review of Computational Intelligence Algorithms in Insurance Applications (pp. 1-50) $100.00
Authors:  (S. Salcedo-Sanz, L. Cuadra, A. Portilla-Figueras, S. Jimenez-Fernandez and E. Alexandre, Department of Signal Theory and Communications, Universidad de Alcala, Madrid, Spain)
Abstract:
Insurance sector, one of the cornerstones the financial system is based
on, is currently facing major changes because of the urgent necessity of
being adapted to the new context of global economic crisis. Within this
frame, the financial system of any modern country needs to develop novel
procedures aiming to make it more competitive and efficient, along with
the compliance with commitment agreed with the policyholders. Part of
this important responsibility relies on the inclusion of more effective and
accurate computing techniques able to provide better solutions for crucial
problems in different key components of the system, including, of course,
the insurance sector. In this respect, this chapter presents a review of
those Soft-Computing applied in the field of insurance companies and related
problems, which have been very active and successful over the past
10 years. The aims of this chapter are thus: 1) to illustrate in a comprehensive
way those features of Soft-Computing algorithms that make them
suitable to tackle insurance problems; 2) to provide a good and up-dated
review of their main applications in insurance-related problems; and 3) to
show to what extent Soft-Computing algorithms work accurately in a real
application. Just in this regard, this chapter ends up with details about the
application of several of these techniques in predicting vehicle accidents
using drivers and vehicles’ data, which is useful for vehicle insurance
companies. 


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A Review of Computational Intelligence Algorithms in Insurance Applications (pp. 1-50)