SCORING AND PREDICTION OF EARLY RETIREMENT USING MACHINE LEARNING TECHNIQUES: APPLICATION TO PRIVATE PENSION PLANS

被引：1
|
作者：
Salazar, Jose de Jesus Rocha [1 ]
Boado-Penas, Maria del Carmen [1 ]
机构：
[1] Univ Liverpool, Inst Financial & Actuarial Math, Liverpool L69 7ZL, Merseyside, England
来源：
ANALES DEL INSTITUTO DE ACTUARIOS ESPANOLES | 2019年 / 25期
关键词：
Insurance company; machine learning; early retirement; supervised learning; FAMILY-SIZE; EMPLOYMENT; DECISION; HEALTH; WORK;
D O I：
10.26360/2019_6
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Artificial intelligence techniques have become very popular in public and private organizations since they allow a more accurate decision-making process. Private insurance companies have ventured into this field by implementing algorithms that allow a better understanding of available data. The knowledge of retirement decisions allows the insurance companies to detect early retirement at a given time so that they have the adequate budgetary provision in place. In this paper, machine learning algorithms and data from private pension plans are used to predict whether a person retires before or after 65 years old in function of both individual characteristics and macroeconomic factors.
引用
收藏
页码：119 / 145
页数：27
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