A Neuroscience-Informed AI Framework to Decode the Complexities of Neurofinance

Christos Bormpotsis, Michael Nanos, Asma Patel

Research output: Contribution to journalArticlepeer-review

Abstract

Financial decision-making, a cornerstone of individual prosperity and global economic stability, is hard to comprehend because it is a complex cognitive process concerned with emotional state and behavioural bias. This paper aims to decode the neural mechanisms behind financial behaviour to advance theoretical and empirical progress in neurofinance. Thus, to better capture financial behaviour, this article proposes an innovative framework that bridges neurofinance, neuroscience, and bio-inspired computational models, like the MCoRNNMCD-ANN. Key research areas include the role of neural processes driving decisions, the effect of cognitive preferences on judgment, and the potential of bio-inspired AI models to enhance understanding. The societal implications of this research seek to encourage equitable, stable and informed financial systems while addressing challenges at the intersection of neurofinance and neuroscience-informed AI.
Original languageEnglish
JournalIEEE Transactions on Technology and Society
Early online date8 Apr 2025
DOIs
Publication statusE-pub ahead of print - 8 Apr 2025

Keywords

  • Artificial intelligence
  • Decision making
  • Neuroscience
  • Brain modeling
  • Computational modeling
  • Convolutional neural networks
  • Complexity theory
  • Sentiment analysis
  • Encoding
  • Economics

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