Development of advanced customer relationship management systems in private banking

Posted: May 05, 2018

• Dr. Lucas Petrova
• Dr. Lucas Silva
• Dr. Lucas Weber

Abstract

The private banking sector represents a critical component of global financial services, characterized by highly personalized relationships between financial advisors and high-net-worth clients. Traditional customer relationship management systems in this domain have largely failed to capture the nuanced, multidimensional nature of these relationships, relying predominantly on transactional data and static client profiles. This research addresses the fundamental limitations of conventional CRM approaches by introducing a quantum-inspired computational framework that models client relationships as dynamic, probabilistic systems rather than deterministic entities. Private banking relationships are inherently complex, involving not only financial transactions but also emotional connections, trust dynamics, and long-term strategic alignment. Current CRM systems struggle to capture this complexity, leading to suboptimal relationship management and missed opportunities for value creation. The research presented in this paper represents a paradigm shift in how private banking relationships are understood and managed computationally. Our work builds upon emerging research in quantum cognition and behavioral finance, applying these principles to the specific challenges of private banking CRM. We introduce a novel methodology that treats client states as existing in superposition until measured through specific interactions, with relationship outcomes determined by the collapse of these quantum-like probability distributions. This approach allows for more accurate modeling of client decision-making under uncertainty and provides relationship managers with unprecedented insights into client needs and preferences.