Prediction of the effect of digital transformation in banking on inflation with machine learning: A Türkiye study

The use of digital technologies in banking has created a new model in the sector. The digital transformation of the banking sector, which is an important member of the financial industry, is an issue that needs to be analyzed in itself and economically. Considering the rapid spread and impact of digitalization, it is necessary to evaluate the macroeconomic dimension of this impact along with the banking sector. This study develops a predictive model using machine learning methods to understand the impact of digitalization on inflation in the banking sector. Taking into account various dimensions of digitalization such as online banking services and digital payment methods, the study investigates the effects of these dimensions on inflation. Machine learning methods, which achieve successful results in large data sets, will be used to measure this effect. According to the results of the analysis, the algorithm that predicts inflation most accurately is gradient boosting. At the same time, mobile banking usage is the attribute that affects inflation the most.