Research On The Valuation Of Internet Finance Enterprise Based On Customer Lifetime Value

China's financial services have been in a state of polarization for a long time.while long-tailed users and small and medium-sized enterprises often find it hard to obtain the quality services provided by financial institutions.However,this situation has been broken with the appearance of the Internet finance.The combination of Internet information technology and financial services has enabled the Internet financial services to be characterized by low cost,flexibility,rapid innovation and risk reduction,resulting in the rapid development of this financial format in just a few years.According to the common law of the market,in accordance with the rapid' development of Internet finance,the industry will soon begin to integrate the tide of mergers and acquisitions.At this time,both business and investors must have a relatively accurate assessment of the value of the business as the basis for their M&A decisions.Due to the characteristics of internet financial enterprises,traditional methods of valuation of enterprises expose various kinds of inaccurate.Therefore,it is necessary to explore more scientific and effective valuation methods to meet the needs of enterprises and investors in all aspects of decision-making.At this time,the method of Customer lifetime value as estimation of internet finance enterprises value shows its charm.This paper focuses on the characteristics of Internet finance enterprises and the incomplete applicability of traditional valuation methods.Then it mainly introduces the theoretical basis of the customer lifetime value and the commonly used models of estimating the value.And then setting a hierarchical Bayesian model that integrates the characteristics of individual users.Based on the RFM theory in Internet operations,the value of the enterprise is estimated by using the variables of transaction probability,lifetime and transaction volume(PLS).Finally,a case that contains the actual data shows the application of the model which we set up,as well as the impact of changes and correlations among the parameters or variables on the final result.