AI-Powered Customer Personalization in Banking: A Study of Predictive Analytics and User Experience

Background: The use of Artificial Intelligence (AI) in banking has changed the way customer care is delivered by providing tools for predictive analytics and personalised engagement. AI-driven personalisation has become a crucial way for banks to improve the user experience as they try to keep up with changing client expectations in the digital age. Objective: This study looks at how AI-powered predictive analytics may help personalise the experience for customers and how it affects their experience in digital banking settings. Methods: We used a quantitative study design and a structured questionnaire to ask 200 banking clients who use AI-based digital services. We used SPSS to look at the data. We used reliability testing (Cronbach's Alpha), Pearson correlation, and regression analysis to figure out how predictive analytics, personalisation, and user experience are related. Findings: With a Cronbach's Alpha of 0.908, we could be sure that the instrument was reliable. The findings of a simple linear regression showed that predictive analytics has a big effect on consumer personalisation (R² = 0.737, p < 0.001). The Pearson correlation study showed that there is a strong positive link between personalisation and user experience (r = 0.850, p < 0.01). Also, multiple regression analysis showed that predictive analytics and personalisation together account for 75.9% of the differences in user experience (R² = 0.759, F = 310.264, p < 0.001), which supports all three research hypotheses. Conclusion: The results show how important it is for banks to incorporate predictive analytics in their services to improve customer interactions and satisfaction. Personalisation powered by AI not only makes service better, but it also develops trust and long-term relationships with customers. This study adds to both academic literature and banking practice by showing how important AI is for determining the future of digital consumer interactions.

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Publication Details

Journal
International Journal of Environmental Sciences
Published
2025-04-15
DOI
https://doi.org/10.64252/y5dfee81
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
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article

AI-Powered Customer Personalization in Banking: A Study of Predictive Analytics and User Experience

Davinder Walia
International Journal of Environmental Sciences
Impact of AI and Big Data on Business and Society
article

AI-Powered Customer Personalization in Banking: A Study of Predictive Analytics and User Experience

Davinder Walia
article en

Abstract

Background: The use of Artificial Intelligence (AI) in banking has changed the way customer care is delivered by providing tools for predictive analytics and personalised engagement. AI-driven personalisation has become a crucial way for banks to improve the user experience as they try to keep up with changing client expectations in the digital age. Objective: This study looks at how AI-powered predictive analytics may help personalise the experience for customers and how it affects their experience in digital banking settings. Methods: We used a quantitative study design and a structured questionnaire to ask 200 banking clients who use AI-based digital services. We used SPSS to look at the data. We used reliability testing (Cronbach's Alpha), Pearson correlation, and regression analysis to figure out how predictive analytics, personalisation, and user experience are related. Findings: With a Cronbach's Alpha of 0.908, we could be sure that the instrument was reliable. The findings of a simple linear regression showed that predictive analytics has a big effect on consumer personalisation (R² = 0.737, p < 0.001). The Pearson correlation study showed that there is a strong positive link between personalisation and user experience (r = 0.850, p < 0.01). Also, multiple regression analysis showed that predictive analytics and personalisation together account for 75.9% of the differences in user experience (R² = 0.759, F = 310.264, p < 0.001), which supports all three research hypotheses. Conclusion: The results show how important it is for banks to incorporate predictive analytics in their services to improve customer interactions and satisfaction. Personalisation powered by AI not only makes service better, but it also develops trust and long-term relationships with customers. This study adds to both academic literature and banking practice by showing how important AI is for determining the future of digital consumer interactions.

International Journal of Environmental SciencesVol. 11(2s)
Openalex Percentile: Top 81%
Impact of AI and Big Data on Business and Society
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AI-Powered Customer Personalization in Banking: A Study of Predictive Analytics and User Experience — Davinder Walia · International Journal of Environmental Sciences (2025) | TGRS Research Map | TGRS