research-article

A Data Mining Framework for Valuing Large Portfolios of Variable Annuities

Authors:

Jimmy Xiangji HuangAuthors Info & Claims

KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Pages 1467 - 1475

https://doi.org/10.1145/3097983.3098013

Published: 13 August 2017 Publication History

Abstract

A variable annuity is a tax-deferred retirement vehicle created to address concerns that many people have about outliving their assets. In the past decade, the rapid growth of variable annuities has posed great challenges to insurance companies especially when it comes to valuing the complex guarantees embedded in these products.

In this paper, we propose a novel data mining framework to address the computational issue associated with the valuation of large portfolios of variable annuity contracts. The data mining framework consists of two major components: a data clustering algorithm which is used to select representative variable annuity contracts, and a regression model which is used to predict quantities of interest for the whole portfolio based on the representative contracts. A series of numerical experiments are conducted on a portfolio of synthetic variable annuity contracts to demonstrate the performance of our proposed data mining framework in terms of accuracy and speed. The experimental results show that our proposed framework is able to produce accurate estimates of various quantities of interest and can reduce the runtime significantly.

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Cited By

Nguyen HSherris MVillegas AZiveyi J(2024)Scenario selection with LASSO regression for the valuation of variable annuity portfoliosInsurance: Mathematics and Economics10.1016/j.insmatheco.2024.01.006Online publication date: Feb-2024
https://doi.org/10.1016/j.insmatheco.2024.01.006
Sun TWang HWang D(2024)Robust Prediction Intervals for Valuation of Large Portfolios of Variable Annuities: A Comparative Study of Five ModelsComputational Economics10.1007/s10614-024-10574-9Online publication date: 15-Mar-2024
https://doi.org/10.1007/s10614-024-10574-9
Gweon HLi S(2023)A hybrid data mining framework for variable annuity portfolio valuationASTIN Bulletin10.1017/asb.2023.26(1-16)Online publication date: 28-Jul-2023
https://doi.org/10.1017/asb.2023.26
Show More Cited By

Index Terms

A Data Mining Framework for Valuing Large Portfolios of Variable Annuities
1. Information systems
  1. Information systems applications
    1. Data mining
2. Mathematics of computing
  1. Probability and statistics
    1. Nonparametric statistics

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cover image ACM Conferences

KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 2017

2240 pages

ISBN:9781450348874

DOI:10.1145/3097983

General Chairs:
Stan Matwin
Dalhousie University
,
Shipeng Yu
LinkedIn
,
Faisal Farooq
IBM

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 13 August 2017

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KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 13 - 17, 2017

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KDD '17 Paper Acceptance Rate 64 of 748 submissions, 9%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Nguyen HSherris MVillegas AZiveyi J(2024)Scenario selection with LASSO regression for the valuation of variable annuity portfoliosInsurance: Mathematics and Economics10.1016/j.insmatheco.2024.01.006Online publication date: Feb-2024
https://doi.org/10.1016/j.insmatheco.2024.01.006
Sun TWang HWang D(2024)Robust Prediction Intervals for Valuation of Large Portfolios of Variable Annuities: A Comparative Study of Five ModelsComputational Economics10.1007/s10614-024-10574-9Online publication date: 15-Mar-2024
https://doi.org/10.1007/s10614-024-10574-9
Gweon HLi S(2023)A hybrid data mining framework for variable annuity portfolio valuationASTIN Bulletin10.1017/asb.2023.26(1-16)Online publication date: 28-Jul-2023
https://doi.org/10.1017/asb.2023.26
Temelcan GKöçken HAlbayrak İ(2022)Fuzzy Complex System of Linear EquationsEncyclopedia of Data Science and Machine Learning10.4018/978-1-7998-9220-5.ch118(1979-1992)Online publication date: 14-Oct-2022
https://doi.org/10.4018/978-1-7998-9220-5.ch118
Gan G(2022)Metamodeling for Variable Annuity Valuation: 10 Years Beyond Kriging2022 Winter Simulation Conference (WSC)10.1109/WSC57314.2022.10015284(915-926)Online publication date: 11-Dec-2022
https://doi.org/10.1109/WSC57314.2022.10015284
Feng RGan GZhang N(2022)Variable annuity pricing, valuation, and risk management: a surveyScandinavian Actuarial Journal10.1080/03461238.2022.20496352022:10(867-900)Online publication date: 28-Mar-2022
https://doi.org/10.1080/03461238.2022.2049635
Luo WMashrur ARobles-Kelly ALi G(2020)Bias-regularised Neural-Network Metamodelling of Insurance Portfolio Risk2020 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN48605.2020.9207375(1-8)Online publication date: Jul-2020
https://doi.org/10.1109/IJCNN48605.2020.9207375
Gweon HLi SMamon R(2020)AN EFFECTIVE BIAS-CORRECTED BAGGING METHOD FOR THE VALUATION OF LARGE VARIABLE ANNUITY PORTFOLIOSASTIN Bulletin10.1017/asb.2020.2850:3(853-871)Online publication date: 8-Sep-2020
https://doi.org/10.1017/asb.2020.28
Cheng XLuo WGan GLi G(2019)Fast Valuation of Large Portfolios of Variable Annuities via Transfer LearningPRICAI 2019: Trends in Artificial Intelligence10.1007/978-3-030-29894-4_57(716-728)Online publication date: 26-Aug-2019
https://dl.acm.org/doi/10.1007/978-3-030-29894-4_57
Cheng XLuo WGan GLi G(2019)Deep Neighbor Embedding for Evaluation of Large Portfolios of Variable AnnuitiesKnowledge Science, Engineering and Management10.1007/978-3-030-29551-6_42(472-480)Online publication date: 28-Aug-2019
https://dl.acm.org/doi/10.1007/978-3-030-29551-6_42
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