CFP last date
15 May 2024
Reseach Article

Design of Integrated Business Intelligence System Framework for Insurance Business Processes

by Dilbag Singh, Pradeep Kumar
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 3 - Number 3
Year of Publication: 2012
Authors: Dilbag Singh, Pradeep Kumar
http:/ijais12-450485

Dilbag Singh, Pradeep Kumar . Design of Integrated Business Intelligence System Framework for Insurance Business Processes. International Journal of Applied Information Systems. 3, 3 ( July 2012), 42-48. DOI=http:/ijais12-450485

@article{ http:/ijais12-450485,
author = { Dilbag Singh, Pradeep Kumar },
title = { Design of Integrated Business Intelligence System Framework for Insurance Business Processes },
journal = { International Journal of Applied Information Systems },
issue_date = { July 2012 },
volume = { 3 },
number = { 3 },
month = { July },
year = { 2012 },
issn = { 2249-0868 },
pages = { 42-48 },
numpages = {9},
url = { https://www.ijais.org/archives/volume3/number3/214-0485/ },
doi = { http:/ijais12-450485 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:45:37.631549+05:30
%A Dilbag Singh
%A Pradeep Kumar
%T Design of Integrated Business Intelligence System Framework for Insurance Business Processes
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 3
%N 3
%P 42-48
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Business intelligence is a key means to promote core competence of enterprise. The high construction cost of business intelligence severely limits the popularization and development of business intelligence system. Business process management (BPM) is a key business initiative that enables companies to align strategic and operational objectives with business activities in order to fully manage performance through better informed decision making and action. Effective business performance requires an organization to model and monitor not only its tactics but also its strategies and the assumption on which these strategies are built. Decision making is an important task for enterprise managers, and is typically based on various data sources derived from information systems, such as enterprise resource planning, supply chain management and customer relationship management. Numerous business intelligence tools (BI) thus have been developed to support decision making. Some existing BI tools have several limitations, for example lacking data analysis and visualization capabilities. The aim of this paper is to examine the processes, methodologies and technologies underlying BPM in insurance, the relation between BPM and business intelligence, and to propose a framework for integrating corporate performance management and business intelligence.

References
  1. Chan-Chine chang, Ruey-Shun Chen, Zhuo, Y. C. 2005. The case study for building a data warehouse in semiconductor manufacturing, International Journal of Computer Applications in Technology, Vol. 24, No. 4, pp. 195-202.
  2. Cooper, B. L. , Watson, H. J. , Wixom, B. H. and Goodhue, D. L. 2000. Data Warehousing supports corporate strategy at First American Corporation, MIS Quarterly, Vol. 24, No. 4, pp. 547-567.
  3. Inmon, W. H. 2000. Building the Data Warehouse, Third Edition, New York: Wiley and Sons.
  4. Dedrick, J. , Gurbaxani, V. and Kraemer, K. 2003. Information Technology and Economic Performance: A critical review of the Empirical Evidence, ACM Computing Surveys, Vol. 35, No. 1, pp. 1-28.
  5. McManus, D. J. and Snyder, C. A. 2003. Synergy between data warehousing and knowledge management: three industries reviewed, International Journal of Information Technology and Management, Vol. 2, No. 1, pp. 85-99.
  6. C. Wingyan, et al. , 2003. Business Intelligence Explorer: A Knowledge Map Framework for Discovering Business Intelligence on the Web, Proceedings of the 36th Annual Hawaii International Conference on System Sciences,
  7. W. Liya, et al. , 2007. A Service-Oriented Architecture for Business Intelligence, IEEE International Conference on Service-Oriented Computing and Applications, pp. 279-285.
  8. D. Krneta, et al. , 2008. Realization Business Intelligence in Commerce Using Microsoft Business Intelligence, The sixth International Symposium on Intelligent Systems and Informatics, pp. 1-6.
  9. Z. Michalewicz and M. Michalewicz, 2008. Machine Intelligence, Adaptive Business Intelligence, and 2Natural Intelligence, IEEE Computational Intelligence Magazine, vol. 3, no. 1, pp. 54-63.
  10. J. Y. Wu and C. J. Lu, 2009. Neuro-Computing Method for Data Mining, The 2009 International Conference on Artificial Intelligence and Computational Intelligence, pp. 184-188.
  11. J. Y. Wu and C. J. Lu, 2009. Applying Classification Problems via a Data Mining Approach Based on a Cerebellar Model Articulation Controller," 1st Asian Conference on Intelligent Information and Database Systems, pp. 61-66.
  12. S. T. Li, et al. , 2008. Business Intelligence Approach to Supporting Strategy-Making of ISP Service Management, Expert Systems with Applications, vol. 35, no. 3, pp. 739-754.
  13. W. Xie, et al. , 2001. Business Intelligence Based Group Decision Support System, International Conferences on Info-tech and Info-net, 2001, pp. 295-300.
  14. M. A. Mazurowski, et al. , 2008. Training Neural Network Classifiers for Medical Decision Making: The Effects of Imbalanced Datasets on Classification Performance," Neural Networks, vol. 21, no. 2-3, pp. 427-436.
  15. H. J. Kim and K. S. Shin, 2007. A Hybrid Approach Based on Neural Networks and Genetic Algorithms for Detecting Temporal Patterns in Stock Markets, Applied Soft Computing, vol. 7, no. 2, pp. 569- 576.
  16. S. Mitra, et al. , 2002. Data Mining in Soft Computing Framework: A Survey, IEEE Transactions on Neural Networks, vol. 13, no. 1, pp. 3-14.
  17. D. H, 1993, Business Intelligence: Competing Against Time, Twelfth Annual Office Information Systems Conference. Gartner Group, pp. 5-7.
  18. W. Zhuo and G. Jie, 2004. The Trinity of Business Intelligence (BI)—Management, Technology and Application, Publishing House of Electronics Industry, Beijing, pp. 11-13.
  19. L. Bing and Y. C. Wang, 2008. Enterprise Business Intelligence Services Broker Platform Based on JADE, Computer Engineering, Vol. 34, pp. 280-282.
  20. X. Na, Z. W. Yun and P. Xin, 2007. Research on Business Intelligence Model Based on Agent, Computer Applications and Software, Vol. 24, pp. 13-16.
  21. J. G. Rui, 2006. The Study of Flexible Business Intelligence Platform Based on Multi-agent for Small and Medium-sized Enterprises, Commercial Research, Vol. 346, pp. 43-46.
  22. Ballard, C. 2006. Business performance management meets Business Intelligence available on line at http:/www. ibm. com/redbooks
  23. BPM Standards Group 2005. Business Performance Management :Industry Framework Document, available on line at http:/www. bpmstandardsgroup. org
  24. Ekerson W. W. 2007. Best practices in operational BI – Converging analytical and operational processes"available on line at www. tdwi. org/
  25. Heizenberg J. 2009 BI predictions 2009: The paradox between demand and supply, available on line at www. bi-guru-nhm. com
  26. Jayanthi Ranjan, Saani Khalil, 2008. Building Data Warehouse at Life Insurance Corporation of India: A Case Study, International Journal of Business Innovation and Research - Vol. 2, No. 3 pp. 241 - 261
  27. Dilbag Singh, Pradeep Kumar, 2011. Identification of vertices and suggestion of data mining techniques for business intelligence in insurance, Proceeding of National Conference on Challenges in Information Systems & Technology (NCCIST), PP 37-40 ,
Index Terms

Computer Science
Information Sciences

Keywords

Insurance Business Intelligence Business Process Framework