Sales forecasting for life insurance on primary and supplementary policies using seasonal and trend methods

被引:0
|
作者
Boonsom, Panrawe [1 ]
Wongyai, Chanin [2 ]
Srimoon, Duang-arthit [2 ]
机构
[1] Rangsit Univ, Coll Engn, Student Master Elect & Comp Engn Program, 52-347 Muang Ake,Phaholyothin Rd, Pathum Thani 12000, Thailand
[2] Rangsit Univ, Coll Engn, Fac Comp Engn, 52-347 Muang Ake,Phaholyothin Rd, Pathum Thani 12000, Thailand
关键词
Forecasting; Holt Winters' Additive; Holt Winters' Multiplicative; Simple Exponential Smoothing and Double Exponential Smoothing;
D O I
10.1109/APPEEC57400.2023.10561992
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Sales of insurance are collected monthly or yearly as statistics which most insurance companies haven't estimated the sales for the next year. The current sales of insurance make it difficult to evaluate the market and organize various campaigns for customers. Therefore, this research has collected sales of life insurance from the website of the Office of Insurance Commission from the year 2018 - 2022. The forecasting of sales for life insurance using 4 forecasting methods which are Holt Winters' Additive, Holt Winters' Multiplicative, Simple Exponential Smoothing, and Double Exponential Smoothing. These forecasting methods are used to forecast insurance premiums one year ahead from the year 2021. The computation of total sales for 3 insurance types which are Primary-General, Primary, and Additional found that the Holt Winters' Multiplicative method is the best forecasting method with an accuracy percentage for forecasting methods of 97.56%.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] LIFE-INSURANCE SALES POLICIES OF AMERICAN COLLEGES AND UNIVERSITIES
    HERSHBARGER, RA
    JOURNAL OF RISK AND INSURANCE, 1977, 44 (01) : 133 - 140
  • [2] Using neural networks for sales forecasting: A comparison of methods
    Ong, E
    Flitman, A
    PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2, 1998, : 1305 - 1308
  • [3] A Comparison Forecasting Methods for Trend and Seasonal Indonesia Tourist Arrivals Time Series
    Subanar
    Sulandari, Winita
    INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020, 2021, 2329
  • [4] Forecasting oil futures markets using machine learning and seasonal trend decomposition
    Kim, Ahhyun
    Ryu, Doojin
    Webb, Alexander
    INVESTMENT ANALYSTS JOURNAL, 2024,
  • [5] DESIGN LIFE INSURANCE PARTICIPATING POLICIES USING OPTIMIZATION TECHNIQUES
    Aguilar, Perla Rocio Calidonio
    Xu, Chunhui
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2010, 6 (04): : 1655 - 1666
  • [6] MODEL OF LIFE INSURANCE POLICIES USING MARKOV CHAINS WITH REWARDS
    Sitar, Milan
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE QUANTITATIVE METHODS IN ECONOMICS (MULTIPLE CRITERIA DECISION MAKING XII), 2004, : 179 - 186
  • [7] Studies in Practical Life Insurance. An Examination of the Principles of Life Insurance as Applied in the Policies, Reports, Agency and Office Methods of the New York Life Insurance Company
    Price, William H.
    AMERICAN ECONOMIC REVIEW, 1912, 2 (03): : 689 - 690
  • [8] The selection of life insurance sales representatives training program by using the AHP and GRA
    Fan, Chiang Ku
    Tsai, Hui-Yin
    Lee, Yu Hsuang
    JOURNAL OF GREY SYSTEM, 2008, 20 (02): : 149 - 160
  • [9] Secular Seasonality and Trend Forecasting of Tuberculosis Incidence Rate in China Using the Advanced Error-Trend-Seasonal Framework
    Wang, Yongbin
    Xu, Chunjie
    Ren, Jingchao
    Wu, Weidong
    Zhao, Xiangmei
    Chao, Ling
    Liang, Wenjuan
    Yao, Sanqiao
    INFECTION AND DRUG RESISTANCE, 2020, 13 : 733 - 747
  • [10] Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales
    Efat, Md. Iftekharul Alam
    Hajek, Petr
    Abedin, Mohammad Zoynul
    Azad, Rahat Uddin
    Al Jaber, Md.
    Aditya, Shuvra
    Hassan, Mohammad Kabir
    ANNALS OF OPERATIONS RESEARCH, 2024, 339 (1-2) : 297 - 328