Leveraging AI and Business Intelligence for Financial Decision-Making in the Age of Deepfakes: Enhancing Consumer Trust and Marketing Resilience

Purpose: This study examines how artificial intelligence (AI) and Business Intelligence (BI) are transforming financial decision-making and risk management, while simultaneously confronting the disruptive rise of deepfake technology in marketing and corporate communication. It aims to understand the mediating role of consumer trust between exposure to synthetic media and financial behaviours, and to propose strategic frameworks to enhance organisational resilience. Design/Methodology/Approach: Using a conceptual-analytical approach, the research synthesises advanced technological insights, behavioural finance perspectives, and real-world cases to explore the dual impact of AI/BI systems. It evaluates the use of forensic AI tools, trust metrics, and blockchain-based content authentication to detect, mitigate, and respond to deepfake-induced threats within financial and marketing ecosystems. Findings: AI and BI systems significantly enhance forecasting accuracy, risk detection, and strategic agility. However, the same technologies also enable deepfake creation, compromising brand integrity and stakeholder trust. Exposure to deepfakes leads to measurable declines in consumer confidence, investment behaviour, and reputational equity. Organisations deploying integrated detection tools, digital twin simulations, and trust-calibrated communication strategies show marked improvements in response efficacy and trust retention. Originality/Value: This study contributes a novel interdisciplinary framework uniting synthetic media forensics, trust analytics, and financial intelligence. Concepts such as Narrative Sovereignty and Synthetic Threat Governance Matrices (STGMs) are introduced to reimagine trust as a quantifiable, algorithmically governed asset, providing strategic guidance for institutions navigating the complexities of post-authenticity digital environments.Keywords: