Applications of Artificial Intelligence in Financial Management Decisions: A Mini-Review

Artificial Intelligence (AI) has, during the past few years, made many signs of progress which have enabled the creation of professional financing applications, which would, perhaps, disrupt the finance industry. Thus, it is assumed that the AI could not only replace human capital in full or in part but also enhance its performance beyond human benchmarks. For companies around the world, there are a variety of programs.

A systemic content analysis methodology was used to evaluate related literature publications in this study. A selection of papers, including posts, has been collected. This research focuses on broad publications peer-reviewed, including Scopus and SSRN, which are listed in quality and impact rankings. This selection of the highest-ranking papers not only guaranteed the quality of papers that were most reviewed and validated but also provided the most up-to-date research state during their publication periods. Some keywords are used to scan for artificial intelligence papers, such as artificial intelligence and financial articles such as corporate finance, artificial intelligence, digital finance, financial and artificial intelligence, etc.

AI has been found to be used by organizations around the world for the detection of anomalies. It is used to establish optimal investment strategies. The other use of AI in securities is algorithmic trading, programs that integrate information regarding changing market dynamics and price levels by using proprietary algorithms to making automated trading very rapidly.

However, given the financial consequences, companies should ensure a sufficient understanding of the AI and other technology used in business by the senior management and the board to ensure proper monitoring. This is particularly important in view of the growing expectations of Board members to monitor substantive issues affecting the long-term value of a company. The decision-making, deployment, and use of AI must be carried out within the context of risk management, in order to capture market improvements. It will include four main tasks, including risk recognition, risk assessment, prevention and risk control.