Bii K. Harrison

Work place: University of Kabianga/School of Information Science and Knowledge Management, Kericho, Kenya

E-mail: jhkbii@gmail.com

Website:

Research Interests: Software Development Process, Computer systems and computational processes, Information Security, Information Systems, Information Storage Systems

Biography

Dr. Bii K. Harrison is a senior lecturer and dean at the School of Information Science and Knowledge Management, University of Kabianga, Kenya. He holds a PhD, in Management Science & Engineering (Information Systems Management), from Wuhan, China (2009) and a Master of philosophy in Information Sciences (2001) in addition to a bachelor’s degree in Information Sciences (Information and Media Technology) (1995) from Moi University, Kenya. His research Interests are in the areas of Information Systems Development process, social media in decision making and curriculum delivery, ICT in knowledge management and ICT management.

Author Articles
A Knowledge-Based System for Life Insurance Underwriting

By Mutai K. Joram Bii K. Harrison Kiplang at N. Joseph

DOI: https://doi.org/10.5815/ijitcs.2017.03.05, Pub. Date: 8 Mar. 2017

The purpose of this work is to enhance the life insurance underwriting process by building a knowledge-based system for life insurance underwriting. The knowledge-based system would be useful for organizations, which want to serve their clients better, promote expertise capture, retention, and reuse in the organization. The paper identifies the main input factors and output decisions that life insurance practitioners considered and made on a daily basis. Life underwriting knowledge was extracted through interviews in a leading insurance company in Kenya. The knowledge is incorporated into a knowledge-based system prototype designed and implemented, built to demonstrate the potential of this technology in life insurance industry. Unified modelling language and visual prolog language was used in the design and development of the prototype respectively. The system's knowledge base was populated with sample knowledge obtained from the life insurance company and results were generated to illustrate how the system is expected to function.

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