Artificial Intelligence, Machine Learning, Deep Learning, and Blockchain in Financial and Banking Services: A Comprehensive Review
DOI:
https://doi.org/10.5281/zenodo.12826933Keywords:
Artificial Intelligence, Deep Learning, Finance, Banking, Machine Learning, Forecasting, ChatGPT, BlockchainAbstract
This research offers a thorough overview of the current research on artificial intelligence, machine learning, deep learning, and blockchain applications in the financial and banking industries, emphasizing the notable influence these technologies have had on spurring innovation and enhancing operational effectiveness. The research landscape is defined by key themes and trends through a detailed analysis of keyword co-occurrence and clusters in the study. The results highlight the important role of artificial intelligence in improving decision-making abilities, promoting innovation in financial markets, creating sophisticated trading strategies, and maintaining strong cybersecurity measures. Support vector machines and neural networks are more frequently utilized in predictive modeling, fraud detection, and portfolio management. Sophisticated data analysis tasks benefit from deep learning techniques like convolutional neural networks and long short-term memory networks, providing a more in-depth understanding of market trends and customer behaviors. Blockchain technology, known for its decentralized and transparent features, has become a crucial element in fintech advancements, guaranteeing secure and efficient transaction processing, ultimately building trust and minimizing the threat of fraud. The research also points out the merging of AI and blockchain, which is driving the creation of new financial products and services and encouraging digital transformation in the industry. Moreover, the research delves into the possibilities of new technologies such as quantum computing in solving intricate computational problems in the financial sector, including portfolio optimization, risk management, and cryptography. The research contributes by outlining key research topics, offering perspectives on various AI methods and uses, and proposing new research paths for exploring AI's integration in finance and banking.