Cutting Through the Noise of FinTech: How Business Model Innovation of FinTech in China is Driven by Big Data

Shanshan Wei

Student thesis: Master thesis

Abstract

Over the past decades, FinTech has hogged the limelight of the publicity and flourished the whole finical service industry. The uniqueness and complexity of the Chinese market originated from
multiple factors including its immature financial infrastructure, its transforming towards a domestic consumption-driven economy defines Chinese market as a fertile ground for FinTech players. The
likes of Ant Financial, ZhongAn have spread their reputations across the world through their adept mastering of advanced technologies in shaping the landscape of traditional financial services.
However, how specific technologies such as Big data are driving the business model innovation (BMI) of FinTech in China have received little attention. With the aim to formulate holistic paradigm on this research body, this dissertation undertakes a multiple case study approach by deeply analyzing the BMI among four organizations covering four biggest FinTech segments in China. The big picture of how Big data analytics assisted BMI in FinTech in China is configured in this dissertation. The extensive review on keywords extracted from both preliminary review and co-occurrence analysis
provide conceptual understandings of FinTech under different contexts, as well as Big data technologies in FinTech and its role in BMI of FinTech. The multiple case study method is adopted
to compare the various aspects of BMI in FinTech through Big data technologies. The result of case study and literature review highlights that a virtuous and sustainable circle has been established with
the assistance of Big data technologies through dynamic data feeding mechanism within the core elements of BMI. The collaborative nature in the inter-relationship and ecosystem-oriented growth
model of Chinese FinTech players enable them to capture and feed data in a mutually supportive manner, which in turn results in the most disruptive BMI.

EducationsMSocSc in Service Management, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2018
Number of pages116
SupervisorsPeter Ping Li