Earticle

초록

영어

Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents’ heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Related Work
2.1. Customer Segmentation
2.2. Financial Decision
Ⅲ. Current Practice
3.1. Customer Segmentation Practice
3.2. Customer Persuasion
3.3. Discussion
Ⅳ. Application for Customer Segmentation
4.1. CRISP-DM Model
4.2. Our Guideline
Ⅴ. Conclusion
Acknowledgements

키워드

저자

• Kyeongmin Yum [ Ph.D. Candidate, College of Business Administration, Seoul National University, Korea ]
• Byungjoon Yoo [ Professor, College of Business Administration, Seoul National University, Korea ]
• Jaehwan Lee [ Ph.D., Institute of Management Research, Seoul National University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658