Abstract: In recent years, econometric predictions in the finance sector have gained popularity. Traditional methods have proven inadequate for these predictions, due to the frequent adoption of artificial intelligence. In this study, the aim is to create an FQFD model for artificial intelligence forecasting-based portfolio management products, intending to provide firms with a strategic direction. Significant attributes for customer requirements are identified through collaboration with experts and literature review. Initially, a survey is conducted among portfolio holders who actively monitor their investments. Based on the survey results, key attributes for customers are definitively determined using the Multiple Linear Regression method. Engineering characteristics to meet these requirements are similarly sourced from articles and expert consultations. The relationship between important customer attributes and engineering characteristics is established using the Fuzzy Quality Function Deployment method. According to this relationship, the best engineering characteristic is identified. The primary contribution of this study has no similar research has been conducted previously. Hence, it provides firms considering the development of such products with high quality and competitive advantage in the market.

Keywords: AI forecasting-based portfolio management products, Multiple Linear Regression, Fuzzy Quality Function Deployment, Marketing Analysis, Robo-Advisory, Fintech Strategy, Product Development, Artificial Intelligence in Finance, Portfolio Management

Pages: 22-31