City Research Online

Smart defaults: Determining the number of default funds in a pension scheme

Blake, D. ORCID: 0000-0002-2453-2090, Duffield, M., Tonks, I., Haig, A., Blower, D. and MacPhee, L. (2021). Smart defaults: Determining the number of default funds in a pension scheme. The British Accounting Review,

Abstract

We propose a new methodology for the smart design of the default investment fund(s) in occupational defined contribution pension schemes based on the observable characteristics of scheme members. Using a unique dataset of member risk attitudes and characteristics from a survey of a large UK pension scheme, we apply factor analysis to identify single factors for risk aversion, risk capacity and ethical investment preferences, and then apply cluster analysis to these factors to identify two distinct groups of members across age cohorts. We find membership of these clusters depends on a number of personal characteristics, with the principal differentiating feature being that one group had previously engaged with the pension scheme, while the other had not. These identified characteristics can be utilised in the design of smart default funds, including appropriate engagement strategies.

Publication Type: Article
Additional Information: © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0. This article has been accepted for publication in British Accounting Review.
Publisher Keywords: defined contribution pension schemes, investment choices, default investment funds, cluster analysis, risk attitude, risk capacity.
Subjects: H Social Sciences > HG Finance
Departments: Bayes Business School > Finance
Date available in CRO: 26 Aug 2021 13:31
Date deposited: 26 August 2021
Date of acceptance: 22 August 2021
Date of first online publication: August 2021
URI: https://openaccess.city.ac.uk/id/eprint/26664
[img] Text - Accepted Version
This document is not freely accessible due to copyright restrictions.
Available under License Creative Commons Attribution Non-commercial No Derivatives.

To request a copy, please use the button below.

Request a copy

Export

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login