Harnessing AI for Behavioral Insights Unlocking the Potential of Transactional Data

13^th Global Summit on Artificial Intelligence and Neural Networks

March 14, 2025 | Webinar

Arunkumar Paramasivan

Senior Lead Software Engineer, USA

Scientific Tracks Abstracts: J Comput Sci Syst Biol

Abstract :

In today's data-driven economic landscape propels businesses toward determining the real value of transactional information to truly understand consumer spending behavior. This article reviews how AI technologies, machine learning, and predictive analytics can leverage big volumes of transactional data into detailed insights on customer spending habits, preferences, and emerging trends. AI transforms raw data into actionable intelligence that enables organizations to personalize marketing strategies in ways that really can speak to each consumer individually, which drives better engagement and brand loyalty. Moving on to risk management, AI will allow for behavioral insights that can help a business recognize fraud attempts, more precisely assess creditworthiness, and proactively reduce risks.AI is opening a new frontier in customer engagement by catering strategies to individual behaviors and anticipating future needs, which will truly enrich the customer experience. The paper now proceeds with the description of methodologies-AI-driven transactional data analysis: clustering algorithms, anomaly detection, and predictive modeling-hand in hand comprehensively present the view of consumer behaviors and preferences. The paper further underlines the business growth implications of these AI-driven insights for strategic decision-making and highlights how deeper behavioral understanding might lead to effective product development, targeted marketing, and resource allocation. The practical applications along with various real-world case studies from industries like retail, banking, and e-commerce will demonstrate the measurable outcomes achieved by enhancements in behavioral insights using AI. It further makes recommendations on ethical considerations, including issues to do with data privacy and the use of transparent AI models in a bid to engender consumer confidence. This paper, in conclusion, shows that AI has transformative prospects in making transactional data an asset, enabling businesses to converge with prospects for growth in the competitive markets through service to customers and sustainability of earnings.

Biography :

Arunkumar Paramasivan is a Senior Lead Software Engineer at a leading financial institution, renowned for my groundbreaking contributions to financial technology and healthcare systems. With over twenty peer reviewed publications in top industry journals, he has established myself as an influential researcher and thought leader. His work spans critical areas such as cognitive artificial intelligence (AI), smart card technology applications in banking, and block-chain implementations, all of which have shaped security protocols adopted by financial institutions globally.A key focus of my research has been AI applications in card payment systems and healthcare supply chain optimization. In addition to his academic contributions, Arunkumar has spearheaded innovative projects integrating behavioral health analytics and digital twin technology. Through his combination of technical expertise, strategic vision, and practical implementation, He continue to drive progress in both the financial and healthcare industries, shaping the future of digital technology with a focus on security, efficiency, and accessibility.