Personalization in Insurance and Banking Services: AI and ML Applications
Keywords:
Personalization, Insurance, Banking, Artificial Intelligence, Machine Learning, Customer Segmentation, Product Recommendations, Dynamic Pricing, Customer Satisfaction, TechnologyAbstract
Personalization in insurance and banking services has become increasingly vital in today's competitive market. This paper delves into the applications of Artificial Intelligence (AI) and Machine Learning (ML) in tailoring insurance and banking services to individual customers. Through the analysis of AI and ML algorithms, this research explores how these technologies are utilized for customer segmentation, product recommendations, and dynamic pricing strategies. By enhancing customer satisfaction and engagement, personalized services contribute significantly to the success and sustainability of insurance and banking institutions. This paper examines the current landscape of personalization in these sectors, discusses key challenges and opportunities, and proposes recommendations for future research and implementation.
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References
Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
Johnson, Emily B. "Machine Learning Techniques for Customer Segmentation in the Insurance Industry." Insurance Science Quarterly, vol. 12, no. 3, 2019, pp. 87-104.
Lee, David C., et al. "Dynamic Pricing Strategies in the Insurance Sector: A Review of AI Applications." Journal of Insurance Technology, vol. 8, no. 4, 2021, pp. 123-140.
Garcia, Maria L. "Personalization in Banking: Challenges and Opportunities." Banking Journal, vol. 18, no. 1, 2018, pp. 34-49.
Kim, Sarah H., et al. "AI-Based Product Recommendations in Insurance: A Case Study." Insurance Technology Review, vol. 6, no. 2, 2017, pp. 56-73.
Patel, Rajesh K. "Ethical Considerations in AI-Based Personalization: Insights from the Banking Industry." Journal of Ethics in Finance, vol. 15, no. 3, 2019, pp. 78-95.
Nguyen, Anna T. "The Impact of Personalization on Customer Satisfaction in Insurance: A Longitudinal Study." Journal of Customer Experience, vol. 4, no. 1, 2022, pp. 102-119.
Wang, Michael L., et al. "AI-Based Customer Segmentation Strategies in Banking: A Comparative Analysis." Banking Technology Review, vol. 10, no. 3, 2023, pp. 67-84.
Brown, Laura M. "Data Privacy and Security in AI-Based Personalization: A Regulatory Perspective." Journal of Data Protection, vol. 7, no. 2, 2021, pp. 45-62.
Chen, Kevin H. "Predictive Modeling for Demand Forecasting in Insurance: A Machine Learning Approach." Journal of Predictive Analytics, vol. 14, no. 4, 2020, pp. 109-126.
Adams, Christopher R., et al. "Challenges and Opportunities of AI in Personalizing Banking Services: A Qualitative Study." Banking Technology Journal, vol. 9, no. 1, 2019, pp. 23-40.
Wilson, Jessica M. "Integration of AI and ML Technologies in Insurance: A Case Study of Pricing Optimization." Journal of Insurance Analytics, vol. 11, no. 2, 2018, pp. 78-95.
Garcia, Maria L. "Customer Satisfaction and Loyalty in Personalized Banking Services: An Empirical Analysis." Journal of Banking Research, vol. 22, no. 3, 2022, pp. 56-73.
Kim, Sarah H., et al. "AI-Based Fraud Detection in Insurance: A Comparative Study." Insurance Fraud Review, vol. 5, no. 4, 2019, pp. 123-140.
Chen, Kevin H. "The Role of AI in Personalizing Insurance Products: A Comparative Analysis." Journal of Insurance Technology, vol. 8, no. 2, 2021, pp. 34-49.
Patel, Rajesh K. "Ethical Considerations in AI-Based Personalization: Insights from the Banking Industry." Journal of Ethics in Finance, vol. 15, no. 3, 2019, pp. 78-95.
Nguyen, Anna T. "The Impact of Personalization on Customer Satisfaction in Insurance: A Longitudinal Study." Journal of Customer Experience, vol. 4, no. 1, 2022, pp. 102-119.
Wang, Michael L., et al. "AI-Based Customer Segmentation Strategies in Banking: A Comparative Analysis." Banking Technology Review, vol. 10, no. 3, 2023, pp. 67-84.
Brown, Laura M. "Data Privacy and Security in AI-Based Personalization: A Regulatory Perspective." Journal of Data Protection, vol. 7, no. 2, 2021, pp. 45-62.
Adams, Christopher R., et al. "Challenges and Opportunities of AI in Personalizing Banking Services: A Qualitative Study." Banking Technology Journal, vol. 9, no. 1, 2019, pp. 23-40.
Alghayadh, Faisal Yousef, et al. "Ubiquitous learning models for 5G communication network utility maximization through utility-based service function chain deployment." Computers in Human Behavior (2024): 108227.
Dutta, Ashit Kumar, et al. "Deep learning-based multi-head self-attention model for human epilepsy identification from EEG signal for biomedical traits." Multimedia Tools and Applications (2024): 1-23.
Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).
Kulkarni, Chaitanya, et al. "Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer." BMC Medical Informatics and Decision Making 24.1 (2024): 92.
Raparthi, Mohan. "Biomedical Text Mining for Drug Discovery Using Natural Language Processing and Deep Learning." Dandao Xuebao/Journal of Ballistics 35
Kumar, Mungara Kiran, et al. "Approach Advancing Stock Market Forecasting with Joint RMSE Loss LSTM-CNN Model." Fluctuation and Noise Letters (2023).
Sati, Madan Mohan, et al. "Two-Area Power System with Automatic Generation Control Utilizing PID Control, FOPID, Particle Swarm Optimization, and Genetic Algorithms." 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, 2024.
Raparthy, Mohan, and Babu Dodda. "Predictive Maintenance in IoT Devices Using Time Series Analysis and Deep Learning." Dandao Xuebao/Journal of Ballistics 35: 01-10.
