Research on Probability-based Learning Application on Car Insurance Data

DOI

10.2991/macmc-17.2018.14How to use a DOI?

Keywords

Machine learning, Probability-based learning; Insurance risk, R

Abstract

After entering the big data era, there is an increasing demand on data analysis. It is natural for the modern actuary to question tech buzzwords like "machine learning" and "data analytics." In reality, many machine-learning models have a basis in the very concepts, which actuaries have used to assess risk for a long time. We refer to the machine learning techniques that deal most explicitly with probabilities and risks as probability-based learning, and will focus on applying probability-base learning models on a set of car insurance data to create an artificial intelligence to accelerate the underwriting process for property and casualty insurance pricing.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Longhao Jing
AU  - Wenjing Zhao
AU  - Karthik Sharma
AU  - Runhua Feng
PY  - 2018/01
DA  - 2018/01
TI  - Research on Probability-based Learning Application on Car Insurance Data
BT  - Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)
PB  - Atlantis Press
SP  - 59
EP  - 63
SN  - 2352-5401
UR  - https://doi.org/10.2991/macmc-17.2018.14
DO  - 10.2991/macmc-17.2018.14
ID  - Jing2018/01
ER  -