Artificial Intelligence in Financial Services: Customer Chatbot Advisor Adoption

Abstract

The growing sophistication technology has helped us exchange Information at our fingertips, eliminating the need for human support.” A platform designed to understand, learn and converse like a human and answer ad-hoc queries in real time is commonly referred to as a Chabot”. Chabot advisor is Artificial intelligence (AI) computer program that impersonates human communication in its natural format including text or spoken language using a technique such as NLP, image processing or video processing along with the end task completion as instructed by the user [1]. The purpose of the paper was to examine what are the drivers for Chabot advisor services adoption (CBA), focusing on financial services. This study presents the explanatory Chabot advisor services factors by extending the Technology Acceptance Model (TAM). The construct in the research are like perceived privacy, perceived security, enjoyment and social influence. This empirical study was conducted in Pune city in India by collecting primary data from 310 online financial services customers. Data collected was analyzed using structural equation modeling using PLSSEM.The outcome of this study is vital to financial companies like banks, policymakers, technology services adoption literature and provide customer-centric financial services.

Antecedents of generation Z towards digitalisation. A PLS-SEM analysis

“…These findings suggest that both PEoU and ATT are positively related to INT. In other words, H 2 and H 3 are supported in this study which is consistent with previous studies (Schepman & Rodway, 2020;Patil & Mugdha, 2019;Hamid et al, 2016).…”

“…It indicates that the respondents are keen on using the new system if the technology seemed easily understood. Furthermore, Patil and Mugdha (2019) found a significant positive relationship between PeoU and adoption of chatbot services in financial services. This is because the system is a simple drag-and-drop interface and hence respondents are more willing to use it.…”

The complementary effects of bank intangible value binding in customer robo-advisory adoption

“…The utility and usability of a robo-advisor are key determinants of acceptance. Previous research has proposed that perceived usefulness and perceived ease of use have positive effects on the investors' attitude toward robo-advisors (Kulkarni and Patil, 2019; Zheng et al ., 2022).…”

Chatbots in the frontline: drivers of acceptance

“…Customers tend to build their perception of ease of use based on the user-friendly interfaces and compatibility of the technology with various types of devices, which essentially indicates consumers' ability to shop on multiple devices, and absence of that may cause technology confusion (Yang, 2010). Chatbots, for example, should be easy to use and understandable, allowing users to complete their tasks without difficulty (Ashfaq et al, 2020;Patil and Kulkarni, 2019). Furthermore, being able to interact with chatbots as customers interact with human sales staff in a mortar-and-brick store further enhances perceived ease of use.…”