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논문 기본 정보

자료유형
학술저널
저자정보
김성현 천지원 이미영
저널정보
한국생산성학회 생산성연구: 국제융합학술지 생산성연구: 국제융합학술지 제32권 제1호
발행연도
2018.3
수록면
173 - 207 (35page)

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The analysis target data, analysis algorithm, and analysis utilization scenario were defined and developed by identifying eight key analysis services by the value chain of the insurance business. Thus, the insurance big data strategy model was shared and diffused to enable small and medium-sized insurance companies to apply the analysis results to their business while minimizing trial and error in the field of big data adoption. Since most business is processed online in the domestic financial sector, the volume of accumulated internal data is enormous, and its types are diverse, and this has consequently improved the level of big data activation compared to other industries; hence the high potential value and possibilities for the utilization of data analysis. Large insurance companies such as S Life Insurance, H Life Insurance, and K Life Insurance have introduced big data analysis to the domestic insurance industry, which is experiencing continuous trial and error due to the lack of shared information on the effects of the introduction and application of big data analysis. The main contents of this case study are as follows. First, development of a strategy model that internalizes big data analysis based on the value chain of the insurance industry. Second, formation of big data analysis environment through the application of open source technology and STT/TA environment for unstructured text analysis. At last, Sharing of big data analysis strategy model that is suitable for the business and data management status of medium-sized insurance companies.

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