From Risk Prediction to Intelligent Financial Decision Making: An ISM Framework of Neurofinance

Abstract

Nurofinance is an emerging field that offers novel insights into financial decision-making through neural mechanisms. It helps to understand investor behaviour beyond traditional rational models. But its application is constrained by several theoretical and methodological factors. This paper aims to identify the key impediments to the adoption of neurofinance through Interpretive Structural Modelling (ISM). Data were collected from the experts in the collaborative fields, including financial managers, neuroscientists, and psychologists. Twenty-four barriers were identified through systematic analysis, and eighteen were finalized through expert validation. The ISM model shows the contextual relationship between the identified barriers. Results indicate that unsupported government policies are the major constraint, leading to further conceptual, methodological, and technology-related gaps that create adoption-related challenges. MICMAC analysis complements the ISM findings by categorizing impediments based on their driving and dependence power. The study offers a structured perspective that can inform future research agendas and strategic decision-making to advance neurofinance as a credible interdisciplinary field.

Keywords: Neurofinance, Psychology, Neuroscience, Financial Decision-Making, Human Perception, Interpretive Structural Modelling, MICMAC Analysis