The Development of Credit Channels in the transition to the Digital Economy: Demand Modelling

Abstract

The article substantiates and formalizes, in analytical form, the probabilistic model of demand for alternative lending channels, taking into account the common and distinctive characteristics of traditional and new ways to take a credit. To develop this model, the advantages and disadvantages of lending channels have emphasized. The possible exclusive scenarios of the credit market development in conditions of digitalization of the economy have been identifed. Taking into account the trends and scenarios for the development of credit channels, a descriptive model of the institutional structure of the demand and supply of credit has been proposed. It is supposed that traditional lending institutions will be able to adapt the business to innovative technologies, offering customers fundamentally new business models, which will perfectly correspond to the sphere of FinTech. According to the descriptive model, the authors proposed to estimate the market share of lending channels based on the application of utility theory and discrete choice models. It is assumed that potential borrowers make a choice of one / another lending channel from available alternatives, maximizing the utility, under the influence of personal and consumer characteristics of the loan. The authors formalized a multidimensional logit model (nested logit model — NLM) for describing the discrete choice of an alternative lending channel and the corresponding subgroups of lenders (traditional, FinTech and BigTech companies). In this case, the distinctive feature of NLM is a possibility of taking into account the correlations in borrowers’ preferences. The conditions for the application of the developed model have determined. Due to the lack of relevant statistical data as to the volume of lending by the digital channels, the authors modelled changes in the market share of the traditional lending channel based on hypothetical data (characteristics of credit). In the process of modelling, the authors showed nonlinear changes in the demand for an alternative lending channel owing to the existence of individual preferences of potential borrowers. The proposed approach can be used to model and forecast the changes in the credit market conditions

Keywords

• digital economy
• the credit market
• banks
• p2p-lending
• p2b-lending
• fintech companies
• bigtech companies
• models of discrete choice
• logit model
• market share
• demand for loan