The role of big data analytics and management information systems in consumer personalization in U.S. Retail, banking and finance

The increasing reliance on Big Data Analytics (BDA) and Management Information Systems (MIS) has significantly transformed consumer personalization strategies across industries. Businesses are leveraging data-driven insights, artificial intelligence (AI), and predictive analytics to enhance customer experiences, optimize engagement strategies, and tailor services based on individual preferences. However, challenges such as data privacy, ethical concerns, and system integration issues remain critical considerations in the adoption of these technologies. This study aims to examine the role of BDA and MIS in consumer personalization, focusing on how businesses utilize these technologies to enhance customer engagement, predict behavior, and deliver personalized services in the retail, banking, and finance sectors. The study employs a systematic literature review to analyze existing research on BDA and MIS-driven personalization. It synthesizes findings from peer-reviewed journals, conference proceedings, and industry reports to provide a comprehensive understanding of technological advancements and their implications. The results indicate that BDA enhances real-time decision-making, predictive modeling, and hyper-personalization, while MIS enables seamless data integration and customer relationship management (CRM). However, concerns regarding data security, algorithmic bias, and compliance with privacy regulations remain significant challenges. BDA and MIS are critical enablers of consumer personalization, yet businesses must adopt ethical AI practices, strengthen cybersecurity measures, and ensure regulatory compliance to maximize their benefits. Organizations should invest in scalable AI-driven MIS platforms, enhance transparency in data usage, and leverage predictive analytics to create consumer-centric personalization strategies while prioritizing privacy and security.