The modern finance industry is composed of not only numerous financial intermediaries but also internet-based mechanisms which are operated by mobile phone users and online consumers daily. In the coming 10 years, estimates suggest that over half of banks’ functions will likely be replaced by high-tech artificial intelligence. Given the great ongoing shifts in contemporary financial systems, the transmission effects of internet-based finance practices have introduced an important yet unaddressed empirical question on the coupling relationship between the internet finance industry and economic policy uncertainty (EPU). This paper adopts the time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model and novel data from Alibaba Corp. to investigate this relationship. We find: First, the impact of internet-based financial approaches on EPU is greater than the reversal effect, indicating that China’s gross domestic product (GDP) is largely influenced by the online finance industry. Second, the lag impacts are time varying and become stable after 2016, corresponding to the current Chinese government’s long-term strategic plan that emphasizes maintaining the economy’s overall stability. Lastly, additional evidence shows that the online financial approaches are positively correlated with consumers’ behaviors, implying that the online finance industry is gaining its momentum when people are using e-currency rather than real cash. After all, it takes time to observe the real effect of these macro policies. With internet and information technology developing, artificial intelligence is being used in the areas of big data, credit lending, and risk control. This largely reduces the data analyzing cost for internet finance companies and makes risk control more convenient.

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