Portfolio management with the help of AI: What drives retail Indian investors to robo‐advisors?

Sougata Banerjee
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Abstract

Portfolio management is a critical component of financial investments. With the advent of artificial intelligence (AI)‐driven portfolio management, retail investors have the choice to utilize cutting‐edge technology to manage their investment portfolios. This study analyzes and portrays the effects of factors influencing the adoption of financial robo‐advisors (FRAs) among retail investors in India. A framework comprising eight constructs is proposed to understand FRA adoption. Structural equation modeling (SEM) was used to analyze data from 387 respondents among Indian retail investors using the IBM SPSS AMOS version 28 software package. The results indicate that technology readiness and financial literacy are the two strongest predictors of the behavioral intention to adopt FRA. Additionally, this study provides empirical evidence that social influence and investor type are relevant determinants of customers' decisions to adopt FRA. This study provides managers with guidance on the target segment of consumers for FRA and insights into the drivers of adoption. It further highlights the importance of investor profiling beyond just demographics to improve adoption.
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借助人工智能进行投资组合管理:是什么促使印度散户投资者选择机器人顾问?
投资组合管理是金融投资的重要组成部分。随着人工智能(AI)驱动的投资组合管理的出现,散户投资者可以选择利用尖端技术来管理他们的投资组合。本研究分析并描述了影响印度散户投资者采用金融机器人顾问(FRA)的因素。为了解 FRA 的采用情况,本研究提出了一个由八个构件组成的框架。使用 IBM SPSS AMOS 28 版软件包对印度散户投资者中 387 名受访者的数据进行了结构方程建模(SEM)分析。结果表明,技术准备和金融知识是预测采用 FRA 行为意向的两个最有力的因素。此外,本研究还提供了实证证据,证明社会影响和投资者类型是客户决定采用 FRA 的相关决定因素。本研究为管理者提供了关于 FRA 目标消费群体的指导,以及对采用 FRA 的驱动因素的深入了解。它还进一步强调了除人口统计学之外的投资者分析对于提高采用率的重要性。
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