Optimizing Investment Decision-Making Through Ai-Augmented Financial Analysis

Abstract

Financial markets are becoming more complicated, rendering old forecasting techniques inadequate for making authentic decisions due to globalization, technological development, and massive data expansion. Artificial intelligence (AI) is revolutionizing the financial decision process with unparalleled accuracy, efficiency and predictive capabilities. Despite the advantages of including AI in financial decision-making, it draws important issues such as data security,algorithmic biases, ethical issues, transparency hurdles, and regulatory problems. Gaining user trust and adhering to new international rules require AI-driven financial systems to be fair and explainable. The paper examines the optimization of investment decision making through augmented financial analysis. The independent variables used in the paper were augmented analytic and fintech integration. The paper employed a purposive sampling technique. The findings showed that rules, the quality of the data and how willing businesses are to use AI all affect how accurate AI augmentation is. It also showed that fintech analysts showed more confidence and concern towards the adoption of AI augmentation for the investment decision making process.