Skip to main navigation menu Skip to main content Skip to site footer

Vol. 5 No. 1 (2024)
2024 Edition

Articles

Adaptive Financial Literacy Enhancement through Cloud-Based AI Content Delivery: Effectiveness and Engagement Metrics

Published 2024-05-23

  • Maoxi Li
    • ,
  • Wenbo Liu
    • ,
  • Chen Chen

Maoxi Li
Business Analytics, Fordham University, NY, USA

Wenbo Liu
Northeastern University, Software Engineering, MA, USA

Chen Chen
Communication and Information Systems, Nanjing University of Aeronautics and Astronautics, Nan Jing, China

Abstract

This paper investigates the effectiveness of adaptive financial literacy enhancement through cloud-based artificial intelligence content delivery systems. Despite technological advancements in educational methodologies, financial literacy rates remain persistently low globally. The research implements a comprehensive framework integrating recurrent neural networks with cloud infrastructure to deliver personalized financial education across diverse user populations. The adaptive system employs sophisticated user profiling mechanisms to create tailored learning pathways, utilizing multidimensional assessment of knowledge acquisition, engagement patterns, and longitudinal behavioral changes. Empirical evaluation across multiple deployment contexts demonstrates significant improvements in financial knowledge acquisition (+37.8%) compared to traditional approaches (+19.2%), with substantial behavioral impacts on savings rates (+24.3%), investment diversification (+31.7%), and debt reduction (-18.6%) at 12-month follow-up. Sequential pattern analysis identified distinct engagement profiles predicting knowledge acquisition success with 78.3% accuracy. The research contributes to financial inclusion initiatives by addressing ethical considerations in algorithm design and implementing inclusive design principles that accommodate diverse accessibility needs. The findings demonstrate the efficacy of AI-driven adaptive approaches in enhancing financial literacy across socioeconomic boundaries, with implications for policy development and financial education program design in both developed and emerging markets.

Keywords

Financial literacy, adaptive learning, cloud-based AI, personalized content delivery, engagement metrics

View PDF

References

  1. Mandal, A., Saxena, A., & Mittal, P. (2022, March). Financial literacy and digital product use for financial inclusion: A GETU model to develop financial literacy. In 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 1614-1619). IEEE.
  2. Thangarasu, G., & Alla, K. R. (2023, August). Recurrent Neural Network on Revolutionizing Multimedia Systems and Empowering User Experience With Dynamic Content Delivery. In 2023 Second International Conference On Smart Technologies For Smart Nation (SmartTechCon) (pp. 1382-1387). IEEE.
  3. Labhane, S., Patel, R., Khan, S., Mashankar, A., Shukla, A., & Tode, S. (2024, November). The Future of Learning: AI-guided Content Creation and Automated Delivery Mechanisms. In 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI) (pp. 1-6). IEEE.
  4. Fahlevi, M., Dandi, M., Dahlan, S. P., & Dahlan, O. P. (2024, May). The Impact of Digital Financial Literacy on Savings, Expenditure, and Prospective Financial Behavior: An Exploratory Inquiry. In 2024 9th International Conference on Business and Industrial Research (ICBIR) (pp. 1425-1430). IEEE.
  5. Rani, S., & Mittal, A. (2023, September). The Role of Financial Literacy As A Mediator: Assessing The Impact of Financial Inclusion on Individual Financial Outcomes. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 2356-2360). IEEE.
  6. Xu, K., & Purkayastha, B. (2024). Integrating Artificial Intelligence with KMV Models for Comprehensive Credit Risk Assessment. Academic Journal of Sociology and Management, 2(6), 19-24.
  7. Xu, K., & Purkayastha, B. (2024). Enhancing Stock Price Prediction through Attention-BiLSTM and Investor Sentiment Analysis. Academic Journal of Sociology and Management, 2(6), 14-18.
  8. Shu, M., Liang, J., & Zhu, C. (2024). Automated Risk Factor Extraction from Unstructured Loan Documents: An NLP Approach to Credit Default Prediction. Artificial Intelligence and Machine Learning Review, 5(2), 10-24.
  9. Shu, M., Wang, Z., & Liang, J. (2024). Early Warning Indicators for Financial Market Anomalies: A Multi-Signal Integration Approach. Journal of Advanced Computing Systems, 4(9), 68-84.
  10. Liu, Y., Bi, W., & Fan, J. (2025). Semantic Network Analysis of Financial Regulatory Documents: Extracting Early Risk Warning Signals. Academic Journal of Sociology and Management, 3(2), 22-32.
  11. Zhang, Y., Fan, J., & Dong, B. (2025). Deep Learning-Based Analysis of Social Media Sentiment Impact on Cryptocurrency Market Microstructure. Academic Journal of Sociology and Management, 3(2), 13-21.
  12. Zhou, Z., Xi, Y., Xing, S., & Chen, Y. (2024). Cultural Bias Mitigation in Vision-Language Models for Digital Heritage Documentation: A Comparative Analysis of Debiasing Techniques. Artificial Intelligence and Machine Learning Review, 5(3), 28-40.
  13. Zhang, Y., Zhang, H., & Feng, E. (2024). Cost-Effective Data Lifecycle Management Strategies for Big Data in Hybrid Cloud Environments. Academia Nexus Journal, 3(2).
  14. Wu, Z., Feng, E., & Zhang, Z. (2024). Temporal-Contextual Behavioral Analytics for Proactive Cloud Security Threat Detection. Academia Nexus Journal, 3(2).
  15. Ji, Z., Hu, C., Jia, X., & Chen, Y. (2024). Research on Dynamic Optimization Strategy for Cross-platform Video Transmission Quality Based on Deep Learning. Artificial Intelligence and Machine Learning Review, 5(4), 69-82.
  16. Zhang, K., Xing, S., & Chen, Y. (2024). Research on Cross-Platform Digital Advertising User Behavior Analysis Framework Based on Federated Learning. Artificial Intelligence and Machine Learning Review, 5(3), 41-54.
  17. Xiao, X., Zhang, Y., Chen, H., Ren, W., Zhang, J., & Xu, J. (2025). A Differential Privacy-Based Mechanism for Preventing Data Leakage in Large Language Model Training. Academic Journal of Sociology and Management, 3(2), 33-42.
  18. Xiao, X., Chen, H., Zhang, Y., Ren, W., Xu, J., & Zhang, J. (2025). Anomalous Payment Behavior Detection and Risk Prediction for SMEs Based on LSTM-Attention Mechanism. Academic Journal of Sociology and Management, 3(2), 43-51.
  19. Liu, Y., Feng, E., & Xing, S. (2024). Dark Pool Information Leakage Detection through Natural Language Processing of Trader Communications. Journal of Advanced Computing Systems, 4(11), 42-55.
  20. Chen, Y., Zhang, Y., & Jia, X. (2024). Efficient Visual Content Analysis for Social Media Advertising Performance Assessment. Spectrum of Research, 4(2).
  21. Wu, Z., Wang, S., Ni, C., & Wu, J. (2024). Adaptive Traffic Signal Timing Optimization Using Deep Reinforcement Learning in Urban Networks. Artificial Intelligence and Machine Learning Review, 5(4), 55-68.
  22. Chen, J., & Zhang, Y. (2024). Deep Learning-Based Automated Bug Localization and Analysis in Chip Functional Verification. Annals of Applied Sciences, 5(1).
  23. Zhang, Y., Jia, G., & Fan, J. (2024). Transformer-Based Anomaly Detection in High-Frequency Trading Data: A Time-Sensitive Feature Extraction Approach. Annals of Applied Sciences, 5(1).
  24. Zhang, D., & Feng, E. (2024). Quantitative Assessment of Regional Carbon Neutrality Policy Synergies Based on Deep Learning. Journal of Advanced Computing Systems, 4(10), 38-54.
  25. Ju, C., Jiang, X., Wu, J., & Ni, C. (2024). AI-Driven Vulnerability Assessment and Early Warning Mechanism for Semiconductor Supply Chain Resilience. Annals of Applied Sciences, 5(1).
  26. Zhang, C. (2017, April). An overview of cough sounds analysis. In 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017) (pp. 703-709). Atlantis Press.
  27. Wan, W., Guo, L., Qian, K., & Yan, L. (2025). Privacy-Preserving Industrial IoT Data Analysis Using Federated Learning in Multi-Cloud Environments. Applied and Computational Engineering, 141, 7-16.
  28. Wu, Z., Zhang, Z., Zhao, Q., & Yan, L. (2025). Privacy-Preserving Financial Transaction Pattern Recognition: A Differential Privacy Approach. Applied and Computational Engineering, 146, 30-40.
  29. Rao, G., Zheng, S., & Guo, L. (2025). Dynamic Reinforcement Learning for Suspicious Fund Flow Detection: A Multi-layer Transaction Network Approach with Adaptive Strategy Optimization. Applied and Computational Engineering, 145, 1-11.
  30. Yan, L., Weng, J., & Ma, D. (2025). Enhanced TransFormer-Based Algorithm for Key-Frame Action Recognition in Basketball Shooting.
  31. Wang, Y., Wan, W., Zhang, H., Chen, C., & Jia, G. (2025). Pedestrian Trajectory Intention Prediction in Autonomous Driving Scenarios Based on Spatio-temporal Attention Mechanism.