Recommending Personalized Asset Investments through Case-Based Reasoning: the SMARTFASI system

Personalized financial advisory systems based on Case-Based Reasoning and on historical user activity are an emerging trend. In the present paper, we report the experience related to the development of a case-based recommendation module in a project called SMARTFASI, where the knowledge about past experiences is exploited, in order to suggest suitable asset investments to the final user. We present a solution aimed at personalizing the asset picking phase, by taking into consideration choices made by customers who have a financial and personal data profile "similar" to the current one. We discuss the notion of distance-based similarity adopted in our system and how to actually implement an asset recommendation strategy integrated with the other software modules of SMARTFASI. We finally discuss the impact such a strategy may have both from the point of view of private investors and professional users.