Research on FinTech Talent Evaluation Index System and Recruitment Strategy: Evidence From Shanghai in China

Xue Ding, Mengling Qin, Linsen Yin, Dayong Lv and Yao Bai

SAGE Open, 2023, vol. 13, issue 4, 21582440231212256

Abstract: In recent years, the development and iteration of information technology have prompted the financial industry to transform and upgrade to financial technology (FinTech), which has received emerging attention from the global financial industry. While the FinTech industry is growing rapidly around the world, however, few studies have foucusd on the shortage of talent and difficulties in recruiting talent. First, this paper clarifies the shortage of FinTech talent through expert interviews and a questionnaire survey of 112 financial industry enterprises in Shanghai, China. Following, based on role theory, we construct a talent capability evaluation index system using 5 primary and 17 secondary indicators. Based on the exploration above, a gray optimization model is designed to support talent recruitment strategy for FinTech enterprises. The results indicate that Chinese FinTech talent should have composite abilities with outstanding professional technical skills and learning abilities, innovation and teamwork ability, project experience, and international vision. This study provides methodological guidelines for global FinTech talent evaluation and recruitment strategies and broadens the application of role theory and gray clustering theory.

Keywords: financial technology (FinTech); talent evaluation index; talent recruitment strategy; role theory; gray optimization model; gray relational analysis; analytic hierarchy process (AHP) (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231212256

DOI: 10.1177/21582440231212256

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