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

页码：119 / 145

页数：27

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