Menu Expand

Chances and Challenges of Business Intelligence: Insights from the German Insurance Market

  1. Journals
  2. Economics, Finance, Business & Management
  3. Zeitschrift für die gesamte Versicherungswissenschaft
  4. Vol. 112, Issue 3
  5. pp. 237–259

JOURNAL ARTICLE

Cite JOURNAL ARTICLE

Style
Eden, T., Werth, O., Aschenbach, C., Breitner, M. Chances and Challenges of Business Intelligence: Insights from the German Insurance Market. Zeitschrift für die gesamte Versicherungswissenschaft, 112(3), 237-259. https://doi.org/10.3790/zverswiss.2023.1428201
Eden, Theresa; Werth, Oliver; Aschenbach, Claus Marcus and Breitner, Michael H. "Chances and Challenges of Business Intelligence: Insights from the German Insurance Market" Zeitschrift für die gesamte Versicherungswissenschaft 112.3, 2023, 237-259. https://doi.org/10.3790/zverswiss.2023.1428201
Eden, Theresa/Werth, Oliver/Aschenbach, Claus Marcus/Breitner, Michael H. (2023): Chances and Challenges of Business Intelligence: Insights from the German Insurance Market, in: Zeitschrift für die gesamte Versicherungswissenschaft, vol. 112, iss. 3, 237-259, [online] https://doi.org/10.3790/zverswiss.2023.1428201
Format
Download

Chances and Challenges of Business Intelligence: Insights from the German Insurance Market

Eden, Theresa | Werth, Oliver | Aschenbach, Claus Marcus | Breitner, Michael H.

Zeitschrift für die gesamte Versicherungswissenschaft, Vol. 112 (2023), Iss. 3 : pp. 237–259

Read Now Download (PDF)

Additional Information

Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/zverswiss.2023.1428201
Language
German
Pages
23

Author Details

Theresa Eden (korrespondierende Autorin), Gottfried Wilhelm Leibniz Universität Hannover, Institut für Versicherungsbetriebslehre, Otto-Brenner-Straße 7, D-30159 Hannover, Deutschland

Dr. Oliver Werth, OFFIS e.V. – Institute for Information Technology, https://orcid.org/0000-0002-6767-5905, Escherweg 2, D-26121 Oldenburg, Deutschland

Gottfried Wilhelm Leibniz Universität Hannover, Institut für Versicherungsbetriebslehre, Otto-Brenner-Straße 7, D-30159 Hannover, Deutschland

Prof. Dr. Michael H. Breitner, Gottfried Wilhelm Leibniz Universität Hannover, Institut für Wirtschaftsinformatik, Königsworther Platz 1, D-30167 Hannover, Deutschland

References

  1. Amini, M./Salimi, S./Yousefinejad, F./Tarokh, M. J./Haybatollahi, S. M. (2021): The Implication of Business Intelligence in Risk Management: A Case Study in Agricultural Insurance. Journal of Data, Information and Management 3(2), 155–166.  Google Scholar
  2. Baars, H./Zimmer, M./Kemper, H. G. (2009): The ICT Convergence Discourse in the Information Systems Literature – A Second-Order Observation. In: Proceedings of the 17th European Conference on Information Systems (ECIS), Verona, Italy, June 8–10, 2009.  Google Scholar
  3. Catlin, T./Hartmann, R./Segev, I./Tentis, R. (2015): The Making of a Digital Insurer: The Path to Enhanced Profitability, Lower Costs and Stronger Customer Loyalty. http://www.mckinsey.com/industries/financial-services/our-insights/the-making-of-a-digital-insurer, accessed 11 Dec. 2022.  Google Scholar
  4. Chee, T./Chan, L./Chuah, M./Tan, C./Wong, S./Yeoh, W. (2009): Business Intelligence Systems: State-of-the-art Review and Contemporary Applications. In: Proceedings of the 2009 Symposium on Progress in Information and Communication Technology (SPICT’09), Kuala Lumpur, Malaysia, December 7–8, 2009.  Google Scholar
  5. Chung, W. (2009): Enhancing Business Intelligence Quality with Visualization: An Experiment on Stakeholder Network Analysis. Pacific Asia Journal of the Association for Information Systems 1(1), 33–54.  Google Scholar
  6. Curko, K./Bach, M. P./Radonic, G. (2007): Business Intelligence and Business Process Management in Banking Operations. In: Proceedings of the 29th International Conference on Information Technology Interfaces (ITI), Cavtat, Croatia, June 25–28, 2007.  Google Scholar
  7. Davenport, T. H. (2014): How Strategists Use “Big Data” to Support Internal Business Decisions, Discovery and Production. Strategy & Leadership 42(4), 45–50.  Google Scholar
  8. Dreyer, S./Werth, O./Olivotti, D./Guhr, N./Breitner, M. H. (2022): Knowledge Management Systems for Smart Services: A Synthesis of Design Principles. e-Service Journal 13(2), 27–67.  Google Scholar
  9. Eckert, C./Eckert, J./Zitzmann, A. (2021): The Status Quo of Digital Transformation in Insurance Sales: An Empirical Analysis of the German Insurance Industry. Zeitschrift für die gesamte Versicherungswissenschaft 110(2), 133–155.  Google Scholar
  10. Eckert, C./Osterrieder, K. (2020): How Digitalization affects Insurance Companies: Overview and Use Cases of Digital Technologies. Zeitschrift für die gesamte Versicherungswissenschaft 109(5), 333–360.  Google Scholar
  11. Eggert, M./Alberts, J. (2020): Frontiers of Business Intelligence and Analytics 3.0: A Taxonomy-based Literature Review and Research Agenda. Business Research 13(2), 685–739.  Google Scholar
  12. 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.  Google Scholar
  13. Eling, M./Nuessle, D./Staubli, J. (2022): The Impact of Artificial Intelligence Along the Insurance Value Chain and on the Insurability of Risks. The Geneva Papers on Risk and Insurance–Issues and Practice 47(2), 205–241.  Google Scholar
  14. Gehra, B./Gentsch, P./Hess, T. (2005): Business Intelligence for the Masses. Controlling & Management Review 49(3), 236–242.  Google Scholar
  15. Gioia, D. A./Corley, K. G./Hamilton, A. L. (2013): Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology. Organizational Research Methods 16(1), 15–31.  Google Scholar
  16. Gupta, B./Goul, M./Dinter, B. (2015): Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs. Communications of the Association for Information Systems 36(1), 450–476.  Google Scholar
  17. Helfand, R. D. (2017): Big Data and Insurance: What Lawyers Need to Know and Understand. Journal of Internet Law 21(3), 2–35.  Google Scholar
  18. Hsieh, H.-F./Shannon, S. E. (2005): Three Approaches to Qualitative Content Analysis. Qualitative Health Research 15(9), 1277–1288.  Google Scholar
  19. Huang, Z. X./Savita, K. S./Dan-yi, L./Omar, A. H. (2022): The Impact of Business Intelligence on the Marketing with Emphasis on Cooperative Learning: Case-study on the Insurance Companies. Information Processing & Management 59(2), 1–10.  Google Scholar
  20. Keller, B. (2018): Big Data and Insurance: Implications for Innovation, Competition and Privacy. https://www.genevaassociation.org/research-topics/cyber-and-innovation-digitalization/big-data-andinsurance-implications-innovation, accessed 10 Dec. 2022.  Google Scholar
  21. Kuckartz, U. (2018): Qualitative Inhaltsanalyse. Methoden, Praxis, Computerunterstützung, 3rd Ed. Beltz Juventa, Weinheim/Basel.  Google Scholar
  22. Kyper, E. S./Douglas, M. J./Lievano, R. J. (2009): Operational Business Intelligence: Applying Decision Trees to Call Centers. In: Proceedings of the 15th Americas Conference on Information Systems (AMCIS), San Francisco, California, USA, August 6–9, 2009.  Google Scholar
  23. Mayring, P. (2015): Qualitative Inhaltsanalyse: Grundlagen und Techniken, 12th Ed. Beltz, Weinheim/Basel.  Google Scholar
  24. Myers, M. D./Newman, M. (2007): The Qualitative Interview in IS Research: Examining the Craft. Information and Organization 17(1), 2–26.  Google Scholar
  25. Negash, S. (2004): Business Intelligence. Communications of the Association for Information Systems 13(2004), 177–195.  Google Scholar
  26. Ngai, E. W./Hu, Y./Wong, Y. H./Chen, Y./Sun, X. (2011): The Application of Data Mining Techniques in Financial Fraud Detection: A Classification Framework and an Academic Review of Literature. Decision Support Systems 50(3), 559–569.  Google Scholar
  27. Petrini, M./Pozzeborn, M. (2008): What Role is “Business Intelligence” Playing in Developing Countries? A Picture of Brazilian Companies. In: Rahman, H. (Hrsg.) Data Mining Applications for Empowering Knowledge Societies, S. 237–257. Information Science Reference, Hershey, New York.  Google Scholar
  28. Phillips-Wren, G./Daly, M./Burstein, F. (2021): Reconciling Business Intelligence, Analytics and Decision Support Systems: More Data, Deeper Insight. Decision Support Systems 146(2021), 1–10.  Google Scholar
  29. Rostek, K. (2009): Business Intelligence for Insurance Companies. Foundations of Management 1(1), 65–82.  Google Scholar
  30. Schmidt, C. (2018): Insurance in the Digital Age: A View on Key Implications for the Economy and Society. https://www.genevaassociation.org/sites/default/files/research-topics-document-type/pdf_public/insurance_in_the_digital_age_01.pdf, accessed 11 Dec. 2022.  Google Scholar
  31. Schnell, R./Hill, P. B./Esser, E. (2011): Methoden der empirischen Sozialforschung, 9th Ed. Oldenbourg, München.  Google Scholar
  32. Schulte-Noelle, H. (2001): Technological Changes in IT and Their Influence on Insurance: The Change Ahead (I). The Geneva Papers on Risk and Insurance – Issues and Practice 26(1), 83–88.  Google Scholar
  33. Schultze, U./Avital, M. (2011): Designing Interviews to Generate Rich Data for Information Systems Research. Information and Organization 21(1), 1–16.  Google Scholar
  34. Toreini, P./Langner, M./Maedche, A./Morana, S./Vogel, T. (2022): Designing Attentive Information Dashboards. Journal of the Association for Information Systems 23(2), 521–552.  Google Scholar
  35. Trieu, V. H./Burton-Jones, A./Green, P./Cockcroft, S. (2022): Applying and Extending the Theory of Effective Use in a Business Intelligence Context. MIS Quarterly 46(1), 645–678.  Google Scholar
  36. 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(2015), 240–247.  Google Scholar
  37. Watson, H. J. (2009): Business Intelligence – Past, Present, and Future. In: Proceedings of the 15th Americas Conference on Information Systems (AMCIS), San Francisco, California, USA, August 6–9, 2009.  Google Scholar
  38. Werth, O./Schwarzbach, C./Rodríguez Cardona, D./Breitner, M. H./Graf von der Schulenburg, J.-M. (2020): Influencing Factors for the Digital Transformation in the Financial Services Sector. Zeitschrift für die gesamte Versicherungswissenschaft 109(2), 155–179.  Google Scholar
  39. Yin, R. K. (2009): Case Study Research: Design and Methods. 4th Ed. SAGE Publications, Thousand Oaks, CA, London/New Delhi.  Google Scholar

Abstract

Im Rahmen der digitalen Transformation bieten neue Analyseverfahren und Visualisierungen für Versicherungsunternehmen die Möglichkeit bestehende Geschäftsprozesse zu unterstützen, neue Geschäftsprozesse zu ermöglichen und neue Kunden zu gewinnen. Insbesondere infolge einer schnellen, hochwertigen und intuitiven Datenaufbereitung können erhebliche Wettbewerbsvorteile generiert werden. Business Intelligence (BI) Systeme unterstützen und ermöglichen dabei die Datenverarbeitung und sind in Finanzdienstleistungsunternehmen von besonderem Interesse, da große Datenmengen an Kundeninformationen wertschöpfend genutzt werden können. Mit qualitativen Interviews mit Experten aus der deutschen Versicherungsbranche untersucht dieser Beitrag die aktuellen Einsatzpotentiale von BI in Versicherungsunternehmen sowie die mit der Einführung und Nutzung resultierenden Chancen und Herausforderungen. Die Ergebnisse und Erkenntnisse zeigen, dass der Einsatz von BI als vorteilhaft angesehen wird und die Nutzung in Versicherungsunternehmen deutlich zunehmen wird, da potentielle Einsatzmöglichkeiten derzeit ungenügend ausgeschöpft werden. Unsere Forschung unterstützt auch den Entscheidungsprozess von Praktikern, in welchem Umfang die Implementierung von BI sinnvoll ist.

Table of Contents

Section Title Page Action Price
Theresa Eden et al.: Chances and Challenges of Business Intelligence: Insights from the German Insurance Market 237
Abstract 237
Zusammenfassung 238
1. Introduction 238
2. Business Intelligence in Insurance Companies 239
3. Research Design and Research Methods 241
4. Results 245
4.1 Definition 245
4.2 Chances 245
Reporting System 245
Sales Analysis 246
Market Forecasts 247
Usability 247
4.3 Challenges 248
Data and Privacy 248
IT Landscape and Programming 248
Employee Involvement 249
4.4 Impact on Processes 250
Management Processes 250
Decision-Making Processes 251
5. Discussion and Implications 253
6. Limitations, Future Research Directions and Conclusions 256
References 257

Contact

Duncker & Humblot GmbH Carl-Heinrich-Becker-Weg 9 12165 Berlin, Deutschland T: +49 30 790006-0

Quick Navigation

2024 Duncker & Humblot GmbH

Powered by CloudPublish

We use cookies to ensure that you get the best experience on our website. Learn more about how we use cookies.