The Intermediary Role of Deep Learning in Financial Resource Allocation

Abstract

In the context of digital economy development and the advancement of “dual carbon” goals, fintech has become a core driving force for optimizing financial resource allocation. However, there is a structural contradiction between financial agglomeration in the eastern region and inclusive finance lagging in the western region, with a prominent issue of the lack of spatial coordination mechanisms. On the basis of panel data from 31 provinces in China from 2011--2020, this paper explores the impact mechanism of fintech on resource allocation efficiency through the coupling coordination degree model, a three-step regression method for mediating effect testing, and Moran's I analysis. The authors find that fintech indirectly optimizes resource allocation by enhancing the degree of coupling coordination, i.e., “technology-inclusiveness-greenness”, with the mediating effect accounting for 52.3%. The degree of coupling coordination exhibited significant regional agglomeration, with a pattern of “high in the east and low in the west” and increasing spatial dependence annually. This research provides micromechanism support for regional financial coordination policy formulation and spatial planning, echoing the requirements of high-quality development.