Generative AI For Personalized Product Bundling In Consumer Banking: A Revenue Optimization Framework

Abstract

Consumer banking institutions encounter significant challenges when attempting to deliver personalized product bundling solutions that maximize revenue potential across different customer segments and financial service categories. Traditional banking approaches depend on fixed product combinations and standardized pricing models that produce limited results when addressing individual customer requirements across various demographic groups and financial situations. This framework presents a generative artificial intelligence system designed specifically for product bundling optimization in consumer banking environments, combining advanced machine learning technologies with customer behavioral analysis capabilities. The suggested structure integrates predictive customer modeling with dynamic pricing engines to create adaptive, context-aware bundling strategies that maintain service reliability while increasing revenue generation potential. Implementation connects with existing banking infrastructure through established data processing frameworks and security procedures that preserve compliance standards. The generative AI method allows the system to handle standard product combinations through automated logic while applying machine learning capabilities for complex customer scenarios requiring personalized bundling decisions. Framework components include customer segmentation engines, product configuration systems, pricing optimization modules, and comprehensive regulatory compliance elements that ensure adherence to banking regulations. Multi-channel deployment techniques support simultaneous customer engagement across distributed banking platforms while maintaining processing efficiency through advanced computational methods. The framework addresses scalability requirements through cloud-based processing approaches integrated with existing infrastructure capabilities. Performance evaluation demonstrates improved revenue generation rates and enhanced customer satisfaction levels across consumer banking environments, establishing a foundation for future developments in generative AI applications within financial service optimization systems.