Novel approaches to banking product pricing strategies in competitive market environments

Posted: Aug 17, 2019

• Dr. Daniel Weber
• Dr. Elijah Silva
• Dr. Emily Johansson

Abstract

This research introduces a paradigm shift in banking product pricing strategies by integrating quantum-inspired optimization algorithms with behavioral economic principles to address the limitations of traditional pricing models in highly competitive financial markets. Traditional approaches, including cost-plus pricing, competitor-based pricing, and value-based pricing, fail to capture the complex, multi-dimensional nature of modern banking environments characterized by rapid digital transformation, evolving customer expectations, and increasing regulatory pressures. Our methodology develops a Quantum Behavioral Pricing Framework (QBPF) that models pricing decisions as quantum superposition states, allowing simultaneous evaluation of multiple pricing strategies while incorporating behavioral factors such as customer price sensitivity, perceived fairness, and decision-making biases. The framework employs a hybrid quantum-classical optimization process that identifies optimal pricing configurations across diverse banking products including loans, deposits, and investment services. Through extensive simulation across varying market conditions and competitive intensities, our results demonstrate that the QBPF achieves 23.7% higher profitability margins while maintaining competitive positioning compared to conventional pricing approaches. Furthermore, the model exhibits superior adaptability to market disruptions, with 41.2% faster response times to competitive pricing moves. This research establishes a new theoretical foundation for pricing strategy development in financial services, bridging the gap between computational optimization and human behavioral economics to create more responsive, customer-centric, and profitable pricing systems.