Reinforcement Learning with Intrinsic Affinity for Personalized Prosperity Management

Effective customer engagement is a requisite for modern financial service providers that are adopting advanced methods to increase the level of personalization of their services [1]. Although artificial intelligence (AI) has become a ubiquitous tool in financial technology [2], research in the field has yet to significantly advance levels of personalization [3]. Asset management is an active research topic in AI for finance; however, the research opportunities presented by the need for personalized services are usually neglected [4]. Whereas personalized investment advice is typically based on questionnaires, we propose the use of micro-segmentation based on spending behavior. Traditionally, customer segmentation has been grounded in demographics which provide only a coarse segmentation [5]; it fails to capture nuanced differences between individuals with the potential for undesirable ramifications, e.g.