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              <text>An Improved Artificial Intelligence based Service Quality to Increase Customer Satisfaction and Customer Loyalty in Banking Sector</text>
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              <text>AISAQUAL Banking; BANQUAL; SERQUAL; Service; Tangibility</text>
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              <text>This study clarifies and determines how service quality affects customer loyalty and reliability. The support of quality in the open and private financial sphere and understanding of its connection to customer loyalty and conduct goal Utilizing an upgraded SERVQUAL (BANQUAL) tool with 26 items, the review was conducted among 802 bank customers. The social goal battery was used to estimate the clients' expected conduct. The expert used a seven-point Likert scale to assess the standard and saw service quality (implementation), as well as the social expectations of the clients. The most reliable tool to quantify the conceptualization of the differentiation score is the BANQUAL instrument. It is used to evaluate gaps in service between assumptions and perceptions of service quality. The SERVQUAL instrument is modified to make it suitable in the banking industry. Questions on parking at the bank, the variety of things and programmes available, and the banks' genuine efforts to address customer grievances are added to the instrument (Responsiveness). The writing audit was sufficiently compiled from many sources, reflecting both an Indian and foreign environment. The postulation included several hypotheses then examined using structural equation modelling. To meet the exploration goals, the views were tested using the products AMOS and SISS. The data were analysed using corroborative and explorative element research to confirm the BANQUAL instrument's dependability and legitimacy of the financial business execution and service quality aspects. The resulting CFA model value exhibits excellent psychometric qualities. Professional businesses and clients increasingly use artificial intelligence support specialists (AISA) for management. However, no measure measuring the support quality can fully capture the essential factors affecting AISA service quality. By developing a scale for evaluating the quality of AISA service, this study seeks to solve this deficiency(AISAQUAL).   2023 IEEE.</text>
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              <text>Shunmugasundaram M.; Ganesh K.S.; Gnanapragash T.J.; John E.P.; Raj J.P.; Smitha V.</text>
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              <text>2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023 - Proceedings, pp. 433-439.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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          <name>Date</name>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICSCDS56580.2023.10105048" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICSCDS56580.2023.10105048&lt;/a&gt;
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              <text>ISBN: 978-166549199-0</text>
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              <text>Shunmugasundaram M., Scad College of Eng. &amp;amp; Tech, Tamilnadu, Tirunelveli, India; Ganesh K.S., Lead College of Management, Kerala, Palakkad, India; Gnanapragash T.J., Christ Deemed to Be University, School of Business &amp;amp; Management, Bangalore, India; John E.P., Srm Institute of Science and Technology, Chennai, India; Raj J.P., Christ University, School of Business and Management, India; Smitha V., Lead College of Management, Kerala, Palakkad, India</text>
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