2021 Volume 57 Issue 12 Pages 552-562
In a policy simulation for the life planning of elderly, the possibility of future asset depletion is analyzed based on clusters generated from specific attributes and segments. However, a room for improvement exists in the detailed understanding of the attributes that branch the simulation re-sults and comparative examination of possible metrics. In this study, we propose a life planning support system that combines the existing method with social simulation log analysis. This system has the following steps: I) Performs simulations based on clusters generated from the feature analy-sis of individual data. II) Grasps the overall pattern of possible results by comprehensive simula-tions based on the individual data and hierarchical classification of the obtained simulation logs. III) Considers the possible measures by comparing the results of I) and II). The main results of this study are as follows: a) Ability to grasp the threshold of the attribute that separates asset depletion and non-depletion. b) Ability to specify countermeasures that can be taken for each cluster along with numerical goals comprehensively and semiautomatically. The proposed system enables de-tailed advice from financial institutions by providing knowledge directly linked to life planning, which leads to an improvement in the effectiveness of industrial applications.