Mind the Gap - Safely Incorporating Deep Learning Models into the Actuarial Toolkit

63 Pages Posted: 3 Jun 2021

See all articles by Ronald Richman

Ronald Richman

Old Mutual Insure; University of the Witwatersrand

Date Written: April 2, 2021

Abstract

Deep neural network models have substantial advantages over traditional and machine learning
methods that make this class of models particularly promising for adoption by actuaries.
Nonetheless, several important aspects of these models have not yet been studied in detail
in the actuarial literature: the effect of hyperparameter choice on the accuracy and stability
of network predictions, methods for producing uncertainty estimates and the design of deep
learning models for explainability. To allow actuaries to incorporate deep learning safely into
their toolkits, we review these areas in the context of a deep neural network for forecasting
mortality rates.

Keywords: Deep learning, actuarial science

JEL Classification: G22, G23

Suggested Citation

Richman, Ronald, Mind the Gap - Safely Incorporating Deep Learning Models into the Actuarial Toolkit (April 2, 2021). Available at SSRN: https://ssrn.com/abstract=3857693 or http://dx.doi.org/10.2139/ssrn.3857693

Ronald Richman (Contact Author)

Old Mutual Insure ( email )

Wanooka Place
St Andrews Road
Johannesburg, 2192
South Africa

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Do you want regular updates from SSRN on Twitter?

Paper statistics

Downloads
445
Abstract Views
1,206
rank
89,952
PlumX Metrics