AI-Driven UX/UI Design: Empirical Research and Applications in FinTech

Authors

  • Yang Xu Interactive Telecommunications Program, New York University, NY, USA
  • Yingchia Liu Parsons School of Design, MFA Design and Technology, NY, USA
  • Haosen Xu Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
  • Hao Tan Computer Science and Technology, China University of Geosciences, Bejing, China

Keywords:

AI-driven UX/UI, FinTech, Personalization, Ethical AI

Abstract

This study explores the transformative impact of AI-driven UX/UI design in the FinTech sector, examining current practices, user preferences, and emerging trends. Through a mixed-methods approach, including surveys, interviews, and case studies, the research reveals significant adoption of AI technologies in FinTech UX/UI design, with 78% of surveyed companies implementing such solutions. Personalization emerges as a dominant trend, with 76% of FinTech apps utilizing AI for tailored user interfaces. The study demonstrates a strong correlation between AI-enhanced features and improved user engagement, with apps incorporating advanced AI features showing a 41% increase in daily active users. Ethical considerations, including data privacy and algorithmic bias, are addressed as critical challenges in AI implementation. The research contributes a conceptual framework for AI-driven UX/UI design in FinTech, synthesizing findings from diverse data sources. Future trends, including emotional AI and augmented reality integration, are explored. The study concludes that while AI-driven UX/UI design offers significant potential for enhancing user experiences in FinTech, balancing innovation with ethical considerations is crucial for responsible implementation and user trust.

References

W. Xu, "AI in HCI design and user experience," arXiv, 2023. Available from: https://doi.org/10.48550/arXiv.2301.00987

Y. Li and H. Cheng, "Bridging the gap between UX practitioners’ work practices and AI-enabled design support tools," ACM Transactions on Computer-Human Interaction, vol. 29, no. 3, Article 18, 2022. Available from: http://dx.doi.org/10.1145/3491101.3519809

S. Kim and J. Park, "Sketch-based video storytelling for UX validation in AI design for applied research," Proceedings of the ACM Conference on Human Factors in Computing Systems, pp. 1234-1245, 2021. Available from: http://dx.doi.org/10.1145/3334480.3375221

Q. Chen and S. Dai, "Development and practice of intelligent financial products supported by big data and AI platforms," Software Guide, vol. 20, no. 02, pp. 31–39, 2021. Available from: http://dx.doi.org/10.47191/ijcsrr/V7-i1-07

J. Ma and G. Li, "AI empowers continuous innovation in financial technology," China Public Security, vol. 324, no. 09, pp. 141-143, 2019. Available from: https://doi.org/10.1109/ICACTM.2019.8776741

S. Luo and Y. Pan, "Progress in research on the theory, technology, and application of sensibility imagery in product design," Journal of Mechanical Engineering, no. 03, pp. 8-13, 2007. Available from:http://dx.doi.org/10.1080/00140139.2022.2127919

X. Zhan, C. Shi, L. Li, K. Xu, and H. Zheng, "Aspect category sentiment analysis based on multiple attention mechanisms and pre-trained models," Applied and Computational Engineering, pp. 71, 21–26, 2024. Available from: http://dx.doi.org/10.54254/2755-2721/71/2024MA0055

B. Wu, J. Xu, Y. Zhang, B. Liu, Y. Gong, and J. Huang, "Integration of computer networks and artificial neural networks for an AI-based network operator," arXiv preprint arXiv:2407.01541, 2024. Available from: http://dx.doi.org/10.13140/RG.2.2.12618.99523

P. Liang, B. Song, X. Zhan, Z. Chen, and J. Yuan, "Automating the training and deployment of models in MLOps by integrating systems with machine learning," Applied and Computational Engineering, vol. 67, pp. 1-7, 2024. Available from: https://doi.org/10.48550/arXiv.2405.09819

A. Li, T. Yang, X. Zhan, Y. Shi, and H. Li, "Utilizing Data Science and AI for Customer Churn Prediction in Marketing," Journal of Theory and Practice of Engineering Science, vol. 4, no. 05, pp. 72–79, 2024. Available from: http://dx.doi.org/10.53469/jtpes.2024.04(05).10

B. Wu, Y. Gong, H. Zheng, Y. Zhang, J. Huang, and J. Xu, "Enterprise cloud resource optimization and management based on cloud operations," Applied and Computational Engineering, vol. 67, pp. 8–14, 2024. Available from: http://dx.doi.org/10.54254/2755-2721/67/20240667

Y. Zhang, B. Liu, Y. Gong, J. Huang, J. Xu, and W. Wan, "Application of machine learning optimization in cloud computing resource scheduling and management," Applied and Computational Engineering, vol. 64, pp. 9–14, 2024. Available from: https://doi.org/10.48550/arXiv.2402.17216

J. Huang, Y. Zhang, J. Xu, B. Wu, B. Liu, and Y. Gong, "Implementation of seamless assistance with Google Assistant leveraging cloud computing," Applied and Computational Engineering, vol. 64, pp. 169-175, 2024. Available from http://dx.doi.org/10.54254/2755-2721/64/20241383

T. Yang, Q. Xin, X. Zhan, S. Zhuang, and H. Li, "Enhancing financial services through big data and AI-driven customer insights and risk analysis," Journal of Knowledge Learning and Science Technology, vol. 3, no. 3, pp. 53–62, 2024. ISSN: 2959–6386 (online). Available from:http://dx.doi.org/10.60087/jklst.vol3.n3.p53-62

X. Zhan, Z. Ling, Z. Xu, L. Guo, and S. Zhuang, "Driving efficiency and risk management in finance through AI and RPA," Unique Endeavor in Business & Social Sciences, vol. 3, no. 1, pp. 189–197, 2024. Available from: http://dx.doi.org/10.20944/preprints202407.0083.v1

Y. Shi, J. Yuan, P. Yang, Y. Wang, and Z. Chen, "Implementing intelligent predictive models for patient disease risk in cloud data warehousing," Applied and Computational Engineering, vol. 77, pp. 271-277, 2024. Available from: http://dx.doi.org/10.54254/2755-2721/67/2024MA0059

T. Zhan, C. Shi, Y. Shi, H. Li, and Y. Lin, "Optimization techniques for sentiment analysis based on LLM (GPT-3)," arXiv preprint arXiv:2405.09770, 2024. Available from: https://doi.org/10.48550/arXiv.2405.09770

Y. Lin, A. Li, H. Li, Y. Shi, and X. Zhan, "GPU-optimized image processing and generation based on deep learning and computer vision," Journal of Artificial Intelligence General Science (JAIGS), vol. 5, no. 1, pp. 39–49, 2024. ISSN: 3006–4023. Available from:http://dx.doi.org/10.60087/jaigs.v5i1.162

Z. Chen et al., "Application of cloud-driven intelligent medical imaging analysis in disease detection," Journal of Theory and Practice of Engineering Science, vol. 4, no. 05, pp. 64–71, 2024. Available from: http://dx.doi.org/10.53469/jtpes.2024.04(05).09

B. Wang, H. Lei, Z. Shui, Z. Chen, and P. Yang, "Current state of autonomous driving applications based on distributed perception and decision-making," 2024.

P. Yang, Z. Chen, G. Su, H. Lei, and B. Wang, "Enhancing traffic flow monitoring with machine learning integration on cloud data warehousing," Applied and Computational Engineering, vol. 67, pp. 15-21, 2024. Available from:http://dx.doi.org/10.21203/rs.3.rs-4646015/v1

C. Fan, Z. Li, W. Ding, H. Zhou, and K. Qian, "Integrating artificial intelligence with SLAM technology for robotic navigation and localization in unknown environments." Available from:http://dx.doi.org/10.13140/RG.2.2.13091.67360

L. Guo, Z. Li, K. Qian, W. Ding, and Z. Chen, "Bank credit risk early warning model based on machine learning decision trees," Journal of Economic Theory and Business Management, vol. 1, no. 3, pp. 24–30, 2024. Available from:https://doi.org/10.5281/zenodo.11627011

C. Fan, W. Ding, K. Qian, H. Tan, and Z. Li, "Cueing flight object trajectory and safety prediction based on SLAM technology," Journal of Theory and Practice of Engineering Science, vol. 4, no. 05, pp. 1–8, 2024. Available from:http://dx.doi.org/10.53469/jtpes.2024.04(05).01

H. Zheng, J. Wu, R. Song, L. Guo, and Z. Xu, "Predicting financial enterprise stocks and economic data trends using machine learning time series analysis," 2024. Available from: http://dx.doi.org/10.20944/preprints202407.0895.v1

R. Song, Z. Wang, L. Guo, F. Zhao, and Z. Xu, "Deep belief networks (DBN) for financial time series analysis and market trends prediction," 2024. Available from: Available from: http://dx.doi.org/10.1109/CCDC.2017.7978707

Z. Xu, L. Guo, S. Zhou, R. Song, and K. Niu, "Enterprise supply chain risk management and decision support driven by large language models," Applied Science and Engineering Journal for Advanced Research, vol. 3, no. 4, pp. 1–7, 2024. Available from: http://dx.doi.org/10.4018/JGIM.335125

X. Bai, S. Zhuang, H. Xie, and L. Guo, "Leveraging generative artificial intelligence for financial market trading data management and prediction," 2024. Available from: http://dx.doi.org/10.20944/preprints202407.0084.v1

L. Guo, R. Song, J. Wu, Z. Xu, and F. Zhao, "Integrating a machine learning-driven fraud detection system based on a risk management framework," 2024. Available from: http://dx.doi.org/10.55248/gengpi.5.0524.1135

Z. Ling, Q. Xin, Y. Lin, G. Su, and Z. Shui, "Optimization of autonomous driving image detection based on RFAConv and triplet attention," arXiv preprint arXiv:2407.09530, 2024. Available from:http://dx.doi.org/10.54254/2755-2721/67/2024MA0067

Z. He, X. Shen, Y. Zhou, and Y. Wang, "Application of K-means clustering based on artificial intelligence in gene statistics of biological information engineering," in Proceedings of the 2024 4th International Conference on Bioinformatics and Intelligent Computing, pp. 468-473, January 2024. Available from: http://dx.doi.org/10.13140/RG.2.2.28241.95843

Y. Gong, M. Zhu, S. Huo, Y. Xiang, and H. Yu, "Utilizing deep learning for enhancing network resilience in finance," in 2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE), pp. 987–991, March 2024, IEEE. Available from: https://doi.org/10.48550/arXiv.2402.09820

J. Tian, H. Li, Y. Qi, X. Wang, and Y. Feng, "Intelligent medical detection and diagnosis assisted by deep learning," Applied and Computational Engineering, vol. 64, pp. 121-126, 2024. Available from:http://dx.doi.org/10.13140/RG.2.2.11413.95200

Q. Xin, Z. Xu, L. Guo, F. Zhao, and B. Wu, "IoT traffic classification and anomaly detection method based on deep autoencoders," 2024. Available from:http://dx.doi.org/10.20944/preprints202407.0530.v1

T. Yang, A. Li, J. Xu, G. Su, and J. Wang, "Deep learning model-driven financial risk prediction and analysis," 2024. Available from: http://dx.doi.org/10.54254/2755-2721/67/2024MA0064

Y. Zhou, T. Zhan, Y. Wu, B. Song, and C. Shi, "RNA secondary structure prediction using transformer-based deep learning models," arXiv preprint arXiv:2405.06655, 2024. Available from: https://doi.org/10.48550/arXiv.2405.06655

B. Liu, G. Cai, Z. Ling, J. Qian, and Q. Zhang, "Precise Positioning and Prediction System for Autonomous Driving Based on Generative Artificial Intelligence," Applied and Computational Engineering, vol. 64, pp. 42–49, 2024. Available from:http://dx.doi.org/10.13140/RG.2.2.26989.40161

Z. Cui, L. Lin, Y. Zong, Y. Chen, and S. Wang, "Precision Gene Editing Using Deep Learning: A Case Study of the CRISPR-Cas9 Editor," Applied and Computational Engineering, vol. 64, pp. 134-141, 2024. Available from: http://dx.doi.org/10.54254/2755-2721/64/20241357

B. Wang, Y. He, Z. Shui, Q. Xin, and H. Lei, "Predictive Optimization of DDoS Attack Mitigation in Distributed Systems using Machine Learning," Applied and Computational Engineering, vol. 64, pp. 95-100, 2024. Available from:http://dx.doi.org/10.54254/2755-2721/64/20241350

X. Zhang, "Machine learning insights into digital payment behaviors and fraud prediction," Applied and Computational Engineering, vol. 67, pp. 61–67, 2024. Available from: http://dx.doi.org/10.54254/2755-2721/67/2024MA0066

X. Zhang, "Analyzing Financial Market Trends in Cryptocurrency and Stock Prices Using CNN-LSTM Models," 2024. Available from: http://dx.doi.org/10.20944/preprints202407.1119.v1

B. Liu, G. Cai, Z. Ling, J. Qian, and Q. Zhang, "Precise Positioning and Prediction System for Autonomous Driving Based on Generative Artificial Intelligence," Journal of Computer Technology and Applied Mathematics, 2024. Available from:http://dx.doi.org/10.13140/RG.2.2.26989.40161

Q. Xin, R. Song, Z. Wang, Z. Xu, and F. Zhao, "Enhancing Bank Credit Risk Management Using the C5.0 Decision Tree Algorithm," Journal of Financial Technology and Risk Management, 2024. Available from: https://jest.com.pk/index.php/jest/article/view/169

Downloads

Published

2024-07-29

How to Cite

[1]
Y. Xu, Y. Liu, H. Xu, and H. Tan, “AI-Driven UX/UI Design: Empirical Research and Applications in FinTech”, IJIRCST, vol. 12, no. 4, pp. 99–109, Jul. 2024.

Issue

Section

Articles

Similar Articles

You may also start an advanced similarity search for this article.