Artificial intelligence in financial forecasting
: assessing its impact on decision-making

  • Franz Sebastian Rösler (Student)

Student thesis: Master's Thesis

Abstract

This thesis explores how Artificial Intelligence (AI) can enhance decision-making in financial forecasting. The research conducted aims to bridge the gap between the theoretical potential of AI and its practical application. For this purpose, a mixed-methods approach was applied that included expert interviews, a quantitative survey, and the review of literature. Additionally, the management theories Disruptive Innovation, the Technology Acceptance Model (TAM), and Prospect Theory were applied throughout the data collection and analysis. Findings from experts, the survey, and the literature indicated that AI improves decision-making by providing more accurate and efficient predictions. However, challenges such as the transparency and interpretability of AI-based predictions affect their trustworthiness. Trustworthiness itself emerged as a further critical factor during the research. A notable tradeoff between model accuracy and explainability was identified. Which suggested the need for a more balanced approach in AI implementation. In this context, trust in AI tools is significantly influenced by transparency and explainability, which play a critical role in fostering user confidence. AI's potential to disrupt traditional forecasting practices showed significance, but concerns about bias remain as potential barriers to full adoption.
Date of Award18 Oct 2024
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorPeter V. Rajsingh (Supervisor)

Keywords

  • Artificial intelligence
  • Financial forecasting
  • Decision-making
  • Transparency
  • Trustworthiness
  • Generative AI

Designation

  • Mestrado em Gestão e Administração de Empresas

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