How to build trust in answers given by Generative AI for specific, and vague, financial questions
Alex Zarifis, Xusen Cheng

TL;DR
This paper investigates how trust in Generative AI's financial advice varies between specific and vague questions, identifying key factors that influence trust in different scenarios through empirical analysis.
Contribution
It develops a model of trust in GenAI for financial advice and empirically tests how trust factors differ between specific and vague questions using SEM and MGA.
Findings
Humanness influences trust differently in specific vs. vague questions.
Transparency, accuracy, and ease of use are crucial for building trust.
Humanness builds trust only in vague question scenarios.
Abstract
Purpose: Generative artificial intelligence (GenAI) has progressed in its ability and has seen explosive growth in adoption. However, the consumer's perspective on its use, particularly in specific scenarios such as financial advice, is unclear. This research develops a model of how to build trust in the advice given by GenAI when answering financial questions. Design/methodology/approach: The model is tested with survey data using structural equation modelling (SEM) and multi-group analysis (MGA). The MGA compares two scenarios, one where the consumer makes a specific question and one where a vague question is made. Findings: This research identifies that building trust for consumers is different when they ask a specific financial question in comparison to a vague one. Humanness has a different effect in the two scenarios. When a financial question is specific, human-like interaction…
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