Fintech application on banking stability using Big Data of an emerging economy

Abstract

Abstract The rapid growth and development of financial technological advancement (Fintech) services and innovations have attracted the attention of scholars who are now on a quest to analyse their impact on the banking sector. This study conducts several kinds of analyses to measure the effect of the fintech era on the stability of the Chinese banking sector. It uses Big Data and performs Pearson correlation and regression analysis on the fintech era’s transition period to measure the impact of several explanatory variables— institutional regulation, government stability, bank credit to deposit ratio, and economic growth— on the outcome variables, which includes Nonperforming loans (NPLs) and its numerical measurement in relation to the mean score of the Big Data (Z-score). This study uses yearly Big Data from 1995–2018 and revealed that compared to the first wave of the fintech era, the second wave helped in the reduction of NPLs and the enhancement of financial stability in China. This study concludes that in the second wave of the fintech era, the explanatory variables mentioned above had a positive impact on NPLs and banking stability. This work helps comprehend fintech development in modern society and the importance of its disruptive forces in developing and developed countries.

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