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Quantitative Correlational Analysis of Artificial Intelligence Integration Into the Banking Industry's Customer Relationship Management System.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Quantitative Correlational Analysis of Artificial Intelligence Integration Into the Banking Industry's Customer Relationship Management System./
作者:	Belfguira, Ramzi B.
面頁冊數:	1 online resource (226 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
標題:	Information technology. -
電子資源:	click for full text (PQDT)
ISBN:	9798381188028

Quantitative Correlational Analysis of Artificial Intelligence Integration Into the Banking Industry's Customer Relationship Management System.
Belfguira, Ramzi B.

Quantitative Correlational Analysis of Artificial Intelligence Integration Into the Banking Industry's Customer Relationship Management System. - 1 online resource (226 pages)

Source: Dissertations Abstracts International, Volume: 85-06, Section: B.

Thesis (D.M.)--University of Phoenix, 2023.

Includes bibliographical references

Artificial intelligence (AI) and ChatGPT have changed social and business ecosystems globally, taking the technological arena by storm. Medical, pharmaceutical, retail, e-commerce, tourism, and hotel industries started to use AI capabilities to collect, analyze, and recommend products and services for their customers. Customer Relationship Management (CRM) systems have been developed (in industries besides banking) to allow AI integration to improve customer satisfaction (CS) and retention rates and increase organizational efficiency and productivity. The problem identified in this study was the lack of utilization of AI CRM in the US banking industry, leading to poor CS, retention, and reduced CRM effectiveness. This quantitative non-experimental correlational research attempted to discover if there is any association between the AI CRM usage predictor variable (H1 related to RQ1) and the CRM output effectiveness and CS criterion variables (H2 related to RQ2) in the banking industry. This study examined CS factors, AI CRM usage, and CRM output effectiveness (the three variables of the study) and their associations from customers' and bankers' perspectives. After informed consent was accepted, one hundred fourteen customers and 38 bankers participated randomly and were directed to respond to 23 Likert five-scale survey questions through the Survey Monkey platform. The results were collected and analyzed using the IBM SPSS version 29, illustrating the findings' statistical values. Results showed positive correlations between AI CRM usage, CS, and CRM effectiveness. The recommendations highlighted ways for bankers and decision-makers to effectively integrate and use AI CRM to improve decision-making, CS, and retention.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381188028Subjects--Topical Terms:

559429
Information technology.
Subjects--Index Terms:

Customer Relationship ManagementIndex Terms--Genre/Form:

554714
Electronic books.

Quantitative Correlational Analysis of Artificial Intelligence Integration Into the Banking Industry's Customer Relationship Management System.
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