USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN FINANCE: SYSTEMATIC LITERATURE REVIEW

Abstract

FinTech (Financial-Technology) concept has been defined in order to reveal the interaction and intersection of artificial intelligence technology and finance. In this context, it was seen that many studies were carried out and it was thought that these studies should be evaluated systematically. By examining these studies, it is aimed to determine the current situation and to make inferences about possible changes and developments. For this, a literature search was carried out in Google Academy, Dergipark and YÖK databases over keywords such as digital currencies, blockchain, deep learning, artificial neural networks. The studies reviewed were classified as empirical and non-empirical studies. For empirical studies, descriptive statistical analyzes were carried out on year, sector, unit (investment instrument) and technical basis. General inferences were made by using the information in the non-empirical review studies. Based on the findings, the studies were mostly carried out with the artificial neural network technique for the prediction of investment instruments such as stocks, gold, etc. According to the findings, it has been observed that the studies are mostly carried out with artificial neural networks technique for the prediction of stocks, gold etc. investment instruments, but in recent studies, there has been a rapid increase in studies using more advanced analysis such as deep learning for bitcoin price prediction with blockchain.