Evaluating Customer Satisfaction and Trust in Autonomous AI Banking Systems

Author:

Kasinathan Aruna1ORCID,Sampath Shrilatha2ORCID,Sampath Hemalatha3

Affiliation:

1. Karunya Institute of Technology and Science, India

2. Christian Medical College, India

3. University of Maryland, USA

Abstract

The study aims to assess customer satisfaction and trust in autonomous artificial intelligence (AAI) systems within the banking sector. Its primary objectives include exploring factors contributing to customer trust in AAI, investigating preferences for AI-driven features in banking, and determining the impact of AAI on perceived service quality. The research, adopting a descriptive design, employs both qualitative and quantitative methods. A survey, distributed to customers of leading banks in India, particularly in Tamil Nadu, with a sample size of 213, utilizes simple random and convenient sampling. Results highlight customer preferences for customized services, financial advice, and automation in banking. The implementation of AAI is perceived positively, especially in terms of transparency in processes like loans, account management, and more. Practical implications include helping banks understand customer expectations, identify weaknesses in AAI features, and enhance service quality in Tamil Nadu.

Publisher

IGI Global

Reference19 articles.

1. Using data mining and neural networks techniques to propose a new hybrid customer behaviour analysis and credit scoring model in banking services based on a developed RFM analysis method

2. Barriers in adoption of internet banking: A structural equation modeling - Neural network approach

3. Neural network survival analysis for personal loan data

4. Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers

5. Artificial intelligence technologies are increasingly integral to the world we live in, and banks need to deploy these technologies at scale to remain relevant. Success requires a holistic transformation spanning multiple layers of the organization.Larson, E.J. 2021. The myth of artificial intelligence;S.Biswas;The Myth of Artificial Intelligence,2023

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