Presenting a Model for Business Intelligence: A Case Study on the Insurance Industry

Document Type : Case study

Authors

1 Associate Professor, Department of Business Management, Faculty of Social Sciences, Ardabil University, Ardabil, Iran

2 PhD Student in Marketing, Department of Business Management, Faculty of Social Sciences, Mohaghegh Ardabili University, Ardabil, Iran

Abstract

In recent years, the growth and expansion of data production in various fields, while creating challenges regarding their management, provide opportunities for companies to achieve more accurate predictions about changes. has provided an environment. Therefore, there is a need for an expert diagnostic tool to position the competencies of knowledge management and business intelligence for comprehensive optimization of strategic analysis and intelligent decision support of strategic organizational performance management. In fact, tools such as business intelligence, by identifying environmental trends, provide the basis for timely decision-making and action for the organization. On the other hand, one of the indicators of the economic development of countries is the level of development of the insurance industry in those countries. The use of technology in the insurance industry in order to give more people access to financial services has received more attention than before, so that new insurance businesses have entered the field of competition with traditional insurance companies by creating a unique value proposition and improving the business model. In this research, a model was designed for smart business in the insurance industry. In this research, data base theory and qualitative findings were analyzed with MAXQDA software and finally, Strauss and Corbin data base theory paradigm model framework was used to design the model. The participants in this research are experts and managers of the insurance industry, whose number is 16 and they were selected based on a purposeful judgment. By analyzing the data, five categories were extracted, and finally by determining the causal conditions (accessibility quality, electronic acceptance and perceived risk), background conditions (internet limitations, ICT infrastructure and insurance policies) , intervening conditions (users' knowledge level, managers' attitude and perceived security "confidentiality"), central category (smartening the insurance industry), strategies (strengthening the culture of using the Internet, developing digital security and developing the level of knowledge) and consequences (achieving opportunities growth, competitive advantage and profitability) business intelligence model of the insurance industry was presented.

Keywords

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Reference
Albrecher, H., Bommier, A., Filipović, D., Koch-Medina, P., Loisel, S., & Schmeiser, H. (2019). Insurance: models, digitalization, and data science. European Actuarial Journal, 9(2), 349-360.‏
Al-Sabbagh, I., & Molla, A. (2004). Adoption and use of internet banking in the Sultanate of Oman: an exploratory study. Journal of internet banking and commerce, 9(2), 1-12.‏
Azeroual, O, & Theel, H, (2018). The Effects of Using Business Intelligence Systems on an Excell ence Management and Decision-Making Process by StartUp Companies: A Case Study. International Journal of Management Science and Business Administration, 4(3), 30-40.
Azeroual, O., & Theel, H. (2019). The effects of using business intelligence systems on an excellence management and decision-making process by start-up companies: A case study. arXiv preprint arXiv, 1901.10555.
Bargshady, G. Alipanah, F. Abdulrazzaq, A.W. & Chukwunonso, F. (2014). Business Inteligence Technology Implimentation Readiness Factors. Journal Teknologi (Sciences & Engineering), 68(3), 7–12.
Baumann, N. (2018). A Catalyst for Change—How Fintech Has Sparked a Revolution in Insurance.
Braun, A., & Schreiber, F. (2017). The current InsurTech landscape: Business models and disruptive potential (No. 62). I. VW HSG Schriftenreihe.‏
Cappiello, A. (2020). The technological disruption of insurance industry: A review. International Journal of Business and Social Science, 11(1), 1-11.‏
Caseiro, N., & Coelho, A. (2019). The influence of Business Intelligence capacity, network learning and innovativeness on startups performance. Journal of Innovation & Knowledge, 4(3), 139-145.‏
Castellanos, M., Umeshwar, D., & Miller, R. (2010). Enabling real-time business intelligence. Heidelberg: Springer.
Catlin T., Hartmann R., Segev I., and Tentis R. (2015). The Making of a Digital Insurer: The Path to Enhanced Profitability, Lower Costs and Stronger Customer Loyalty.
Chen, Y., & Lin, Z. (2021). Business intelligence capabilities and firm performance: A study in China. International Journal of Information Management, 57, 102232.‏
Chester, A., Hoffmann, N., Johansson, S., & Olesen, P. B. (2018). Commercial lines insurtech: A pathway to digital.
Chishti, S., & Barberis, J. (2016). The Fintech book: The financial technology handbook for investors, entrepreneurs and visionaries. John Wiley & Sons.‏
Choi, J., Yoon, J., Chung, J., Coh, B. Y., & Lee, J. M. (2020). Social media analytics and business intelligence research: A systematic review. Information Processing & Management, 57(6), 102279.‏
Das, A., Ray, S. C., & Nag, A. (2009). Labor-use efficiency in Indian banking: A branch-level analysis. Omega, 37(2), 411-425.‏
Drummer, D., Jerenz, A., Siebelt, P., & Thaten, M. (2016). FinTech–Challenges and Opportunities How digitization is transforming the financial sector. McKinsey & Company,(May), 1–7.‏
Egan, R., Cartagena, S., Mohamed, R., Gosrani, V., Grewal, J., Acharyya, M., & Ang, K. (2019). Cyber operational risk scenarios for insurance companies. British Actuarial Journal, 24.
Elbashir, M. Z., Sutton, S. G., Mahama, H., & Arnold, V. (2021). Unravelling the integrated information systems and management control paradox: enhancing dynamic capability through business intelligence. Accounting & Finance, 61, 1775-1814.‏
Eling, M., & Lehmann, M. (2018). The impact of digitalization on the insurance value chain and the insurability of risks. The Geneva papers on risk and insurance-issues and practice, 43(3), 359-396.‏
Fashanu, O. (2021). Drivers and performance outcomes of effective use of business intelligence (BI) system for managing customer relationships: A multiple case study in business-to-business sector.‏
Frankenfield, D. C. (2019). Impact of feeding on resting metabolic rate and gas exchange in critically ill patients. Journal of Parenteral and Enteral Nutrition, 43(2), 226-233.‏
Freysoldt, T., Johansson, S., Korwin-Szymanowska, C., Münstermann, B., & Vogelgesang, U. (2018). Evolving insurance cost structures. How incumbents can adapt and save to remain competitive in the digital age. Insurance Practice, McKinsey&Company.‏
Grabinska, A, & Ziora, L (2019). The Application of Business Intelligence Systems In Logistics. Review of Selected Practical Examples, Sciendo 1(1), 1028- 1035.
Hagen S & Thomas O. Expectations vs. Reality – Benefits of smart services in the field of tension between industry and science.
Hamad, F., Al-Aamr, R., Jabbar, S. A., & Fakhuri, H. (2021). Business intelligence in academic libraries in Jordan: Opportunities and challenges. IFLA journal, 47(1), 37-50.‏
Hassan, A., Mosconi, M. (2022). Social media analytics, competitive intelligence, and dynamic capabilities in manufacturing SMEs. Technological Forecasting and Social Change, 175(2), 121-416.
Hočevar, B., & Jaklič, J. (2010). Assessing benefits of business intelligence systems–a case study. Management: journal of contemporary management issues, 15(1), 87-119.‏
Howson, C. (2008). Successful Business Intelligence: Secrets to Making BI a Killer App. NewYork: McGraw-Hill.
Huang, Y., Vemer, P., Zhu, J., Postma, M. J., & Chen, W. (2016). Economic burden in Chinese patients with diabetes mellitus using electronic insurance claims data. PLoS One, 11(8), e0159297.
Huang, Z.; Savita, K. S., Zhong-ji, J. (2022). The Business Intelligence impact on the financial performance of start-ups, Information Processing & Management, 59(1), 102-761.
Isik, O. Jones, M. C. & Sidorova, A. (2013). Business intelligence success: The role of BI capabilities and decision environments. Information & Management, 50(1), 13-23.
Johansson, S., & Vogelgesang, U. (2015). Insurance on the threshold of digitization implications for the life and P&C workforce.
Kuzieva, N. (2020). Kuzieva Nargiza Ramazanovna Busıness Processes In The Insurance System And Theır Features. Архив научных исследований, (24).
Larsson, A., & Broström, E. (2019). Ensuring customer retention: insurers’ perception of customer loyalty. Marketing Intelligence & Planning.
Lings, I. N., & Greenley, G. E. (2009). The impact of internal and external market orientations on firm performance. Journal of Strategic Marketing, 17(1), 41-53.‏
Lukman, T., Hackney, R., Popovič, A., Jaklič, J., & Irani, Z. (2011). Business intelligence maturity: the economic transitional context within Slovenia. Information Systems Management, 28(3), 211-222.‏
Mackenzie, A., 2015. The Fintech Revolution. London Business School Review, 26(3), 50-53.
MunikhRe; Tech Trend Radar 2019: Top 10 Trends, MunikhRe, 2019.
Navita Kumari. (2013) Business Intelligence In A Nutshell. International Journal of Innovative Research in Computer and Communication Engineering, 1)4(, 969-975.
Neuhofer B, Buhalis D & Ladkin A. (2015). Smart technologies for personalized experiences: A case study in the hospitality domain. Electronic Markets: The International Journal on Networked Business, 25(3), 243-254.
Nicoletti B. (2017). The Future of FinTech. Cham: CH, Springe.
Nithya, N., & Kiruthika, R. (2021). Impact of Business Intelligence Adoption on performance of banks: a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 12(2), 3139-3150.‏
Niu, Y; Ying, L.; Yang, J., Sivaparthipan, C. B. (2021). Organizational business intelligence and decision making using big data analytics. Information Processing & Management, 58(6), 102-725.
OECD - Organisation for Economic Co-operation and Development. (2017). Technology and Innovation in the insurance sector.
Pousttchi, K., & Gleiss, A. (2019). Surrounded by middlemen-how multi-sided platforms change the insurance industry. Electronic Markets, 29(4), 609-629.
Rikhardsson, P., Yigitbasiog, O. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29(6), 37-58.
Schueffel, P. (2016). Taming the beast: A scientific definition of fintech. Journal of Innovation Management, 4(4), 32-54.‏
Segev I. and Vickers A. (2017). What the new world of insurance could look like. McKinsey & Company. August.
Singh, A., & Akhilesh, K. B. (2020). The Insurance Industry—Cyber Security in the Hyper-Connected Age. In Smart Technologies (pp. 201-219). Springer, Singapore.‏
SwissRe, S. (2018). World Insurance in 2017: solid, but mature life markets weight on growth. Erişim Tarihi, 27.
Wanda, P., & Stian, S. (2015). The Secret of my Success: An exploratory study of Business Intelligence management in the Norwegian Industry. Procedia Computer Science, 64, 240-247.‏
Watson, W. T. (2017). New horizon: How diverse growth strategies can advance digitisation in the insurance industry.‏
World Bank Group. (2018). How Technology Can Make Insurance More Inclusive. World Bank.‏
Yahya, S. & Sugiyanto, C. (2020). Indonesian Demand for Online Shopping: Revisited. Journal of Indonesian Economy and Business, 35(3), 188-203.
Yu, J., Chaomurilige, C., & Yang, M. S. (2018). On convergence and parameter selection of the EM and DA-EM algorithms for Gaussian mixtures. Pattern Recognition, 77, 188-203.
Zemblyto, J. (2015). The instrument for evaluating e-service Quality. ProcediaSocial and Behavioral Sciences, 213(1), 801-806.
Zhang, L., Vinodhini, B., & Maragatham, T. (2021). Interactive IoT Data Visualization for Decision Making in Business Intelligence. Arabian Journal for Science and Engineering, 1-11.‏
Volume 5, Issue 2 - Serial Number 17
Serial No.17-Summer Quarterly
September 2022
Pages 49-76
  • Receive Date: 04 July 2022
  • Revise Date: 21 July 2022
  • Accept Date: 06 September 2022