The FinRec Workshop

Introduction

Personalization and recommendation technologies can broadly be defined as systems that aim to support users in decision making by suggesting and offering relevant content, and have been well-studied in a variety of domains, such as movies, music, and news. While the application of recommender systems and related technologies in the domain of financial services is less well-developed, there is a clear rising commercial interest around these technologies from companies and startups alike. Recently, financial-services firms have begun to use recommender systems to provide investor alerts about key market events in which they might be interested. According to a Bloomberg Business news report on March 2015, funds run by intelligent agents now account for 400 billion US dollars.

At the same time, the use of AI applications in the financial services industry, such as recommender systems, is considered high-risk by the European Commission, as automation here can directly impact people's lives. In this light, the rise of AI-assisted decision-making in the financial services industry should be met with caution. Predatory loan targeting, for instance, is a commonly-used example application area in AI ethics and fairness literature.

We feel the prevalence and rise of personalization and recommender systems technology in financial services calls for a central forum where researchers and practitioners alike can study and discuss the domain-specific aspects, challenges, and opportunities of RecSys and other related technology. The aim of this workshop is to bring together researchers and practitioners working in financial services-related areas in order to: (1) understand and discuss open research challenges, (2) provide an overview of existing technologies using recommender systems in the financial services domain, and (3) provide an interactive platform for information exchange between industry and academia.

We welcome any related topics in the following two categories of domains or applications:
  • Recommendation of financial products and/or services, such as loans, insurance plans, pension plans, real estate, funds and stocks, investment, micro-finance, etc. This includes related aspects, such as explanations, ethical aspects, multi-stakeholder fairness, and awareness and sustainability.
  • Broadly speaking, we also welcome submissions related to more general industry perspectives (not limited to the financial industries), such as the joint optimizations between recommendation relevance and the profits, business strategies, the balance between costs and gains, the view from different stakeholders in the industries. For example, the topic of joint optimization between profits and relevance in any domains (e.g., movies, music, etc) would also be relevant for our workshop. The topic of considering budgets as inputs in the hotel recommendation models may still be relevant as the submissions.

History

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