Ma, L.; Li, Y.; Li, D.; Li, H.; Wang, Y., and Ren, C., 2020. Risk identification and decision making for P2P companies: An empirical study in the Bohai Coast regions. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 191–196. Coconut Creek (Florida), ISSN 0749-0208.

This paper takes risk identification and risk profiling of new types of peer-to-peer (P2P) companies as the theme, efficiently integrates multidimensional variables, and builds a corporate risk identification model. On the basis of this model, it describes the risk profiling of P2P companies, thereby helping investors better identify corporate risks and reduce potential loss. This paper takes the data of 633 P2P platforms in the Bohai Coast regions extracted from the two authoritative websites of Wdzj and Tianyancha as examples, uses logistic regression models to analyze 16 variables in five dimensions, and draws the following conclusions: change log and platform transfer fees are significantly positively related to platform operating risks; platform background, platform management fees, and automatic bidding are significantly negatively related. Finally, it provides relevant recommendations on how investors choose a platform.