ABCD Analysis of Voice Biometric System in Banking

Author:

M. K. Amjad Hassan Khan1,Aithal P. S.2

Affiliation:

1. Department of Electronics, Kristu Jayanti College, Bengaluru-560077, India

2. Institute of Engineering & Technology, Srinivas University, Mangalore-575001, India

Abstract

Purpose: This article aims to provide an overview of the voice biometric system in banking and its benefits using the ABCD analytical methodology. Voice biometric systems in banking are pivotal for improving customer experiences, effortlessly integrating into various service channels like call centers and mobile apps. This article provides advantages, benefits, constraints and disadvantages (ABCD) analysis of the voice biometric offerings for banking sector. Design/Methodology/Approach: The research examined published papers through the ABCD analysis framework, employing quantitative analysis within focus group interactions to uncover crucial attributes and variables that impact consumers' intentions to implement voice biometric system in banking system. This process yielded valuable insights. Findings/Result: The ABCD analytical approaches of voice biometric systems in banking indicates the enhanced customer satisfaction and streamline operations through their diverse functionalities. When integrated into the bank's multi-factor authentication framework, voice biometric systems serve as a non-intrusive yet highly secure authentication method. They offer a seamless customer experience by eliminating the need for traditional PINs or passwords, reducing the risk of unauthorized access, and bolstering overall system security. The implementation of voice biometric systems in the banking sector provides several key benefits. Originality/Value: Utilizing the ABCD analysis approach, this research examines the inclination of consumers to activate the voice biometric systems in banking. The investigation delves into consumer behavior and the elements that impact usage decisions, employing determinant issues, key attributes, factor analysis, and elementary analysis. Paper Type: Empirical Analysis

Publisher

Srinivas University

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Tech-Business Analytics in the Circular Economy;International Journal of Management, Technology, and Social Sciences;2024-05-30

2. Tech-Business Analytics in Blue Economy;International Journal of Applied Engineering and Management Letters;2024-05-16

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