Cognitive Computation on Consumer’s Decision Making of Internet Financial Products Based on Neural Activity Data

Hongzhi Hu, Yunbing Tang, Yanqiang Xie, Yonghui Dai, Weihui Dai

Internet finance has become a popular business in today society. However, different from the physical objects or services sold online, Internet financial products are actually the contracts defined by financial terms which make customers bear the possibility of capital loss and liquidity restrictions, but they can obtain profits in the future with some uncertainties. This paper takes consumer’s cognition in the decision making of Internet financial products as research circumstances, studies the above issue by conducting an EEG-fNIRS experiment, and proposed an effective cognitive computation method based on neural activity data through BP-GA algorithm. On this basis, a new recommendation approach of Internet financial products is explored according to consumer’s typical shared mental model. The computing and testing results indicate that researches of this paper provide promising new ideas and novel methods for the cognitive computation of artificial intelligence and the recommendation of Internet financial products.