FinPathlight: Framework for an multiagent recommender system designed to increase consumer financial capability

摘要

In consideration of the general lack of trust in human professional financial advisors due to conflicts of interest, and given inadequacies in terms of the utility of FinTech alternatives for financial goal recommendations, this study establishes a framework for an ontology-based, multiagent recommender system designed to improve financial capability through the recommendation of financial goals, called FinPathlight. The FinPathlight framework provides an architecture for a personal financial recommender system designed to identify and recommend specific, achievable financial goals appropriate to a wide range of financially situated users. This framework contributes principles of implementation for a novel financial technology (FinTech) application aimed at addressing a pervasive lack of trust surrounding traditional financial advisory services, as well as utility inadequacies within the current landscape for FinTech applications, providing a comprehensive set of practical and explicit financial goal recommendations. Considering the importance of users' adoption of an innovation, this study empirically tests its utility in terms of trust and perceived usefulness. The experimental evaluation results show that an application built using this framework would likely be perceived as trustworthy and useful to users for identification and selection of financial capability enhancing objectives.