Nudging Consumers to Invest their Tax Returns: Evidence from FinTech

Last registered on September 15, 2023

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Pre-Trial

Trial Information

General Information

Title

Nudging Consumers to Invest their Tax Returns: Evidence from FinTech

RCT ID

AEARCTR-0012021

Initial registration date

September 06, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

September 15, 2023, 5:28 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Germany

Region

Primary Investigator

Name

Emanuel Renkl

Affiliation

Technical University of Munich

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Moritz Nardini

PI Affiliation

Technical University of Munich

Contact Investigator

Additional Trial Information

Status

In development

Start date

2023-09-06

End date

2024-03-31

Keywords

Behavior, Finance & Microfinance

Additional Keywords

FinTech, Household Finance, Saving Behavior

JEL code(s)

D14, G11, G40, G51

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Research has shown that tax refunds are usually spent on consumption instead of being saved or invested. In an email experiment, we inform (prospective) customers of a roboadvisor about the deadline for filing the 2022 tax return, promote a special partner offer to file it, and nudge them to invest the refund with the roboadvisor. To increase the motivation of filing and investing the return against the control group, we test a graphical nudge in the otherwise identical treatment group. The graph illustrates the expected wealth accumulation when investing the average tax return each year for the average working life in one of the roboadvisor's portfolios. We expect more filings, manual transfers, and assets under management in the treatment group, because customers have a higher motivation to file and invest the tax return. Moreover, we expect more prospective customers to become customers of the roboadvisor in the treatment group, because of a higher motivation to use the tax return to start investing with the roboadvisor.

External Link(s)

Registration Citation

Citation

Nardini, Moritz and Emanuel Renkl. 2023. "Nudging Consumers to Invest their Tax Returns: Evidence from FinTech." AEA RCT Registry. September 15. https://doi.org/10.1257/rct.12021-1.0

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2023-09-08

Intervention End Date

2023-12-31

Primary Outcomes

Primary Outcomes (end points)

The key outcome of interest is if and how the intervention influences a customer's decision to file and invest the tax return. Consequently, the key outcome variables are (i) number of redeemed partner vouchers, (ii) number and amount of manual transfers to the roboadvisor, and (iii) assets under management at the roboadvisor. Finally, we are also interested in whether a prospective customer became a customer at the roboadvisor and intend to measure this with the variable onboarding status.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary outcomes are if a customer (i) viewed the email (yes/ no), (ii) clicked on the call to action in the email (yes/no), as well as (iii) his/her regular saving rate, and (iv) the number of his/her saving pots.

Secondary Outcomes (explanation)

Experimental Design

In an email experiment, we inform (prospective) customers of a roboadvisor about the deadline for filing the 2022 tax return, promote a special partner offer to file it, and nudge them to invest the refund with the roboadvisor. To increase the motivation of fling and investing the return against the control group, we test a graphical nudge in the otherwise identical treatment group. The graph illustrates the expected wealth accumulation when investing the average tax return each year for the average working life in one of the roboadvisor's portfolios.

Experimental Design Details

Randomization Method

The randomization is done in the office by a computer.

Randomization Unit

The unit of randomization is at the individual level.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

There are no planned clusters, as the unit of randomization is at the individual level.

Sample size: planned number of observations

The planned number of observations is between 4,000-5,000 (prospective) roboadvisor customers. Background is that the sample size depends on the time and date of the sample selection which is executed by the project partner just a few days before the intervention.

Sample size (or number of clusters) by treatment arms

Accordingly, the planned sample size by treatment arm is between 2,000-2,500 (prospective) roboadvisor customers, i.e. 2,000-2,500 (prospective) roboadvisor customers in the control group and 2,000-2,500 (prospective) roboadvisor customers in the treatment group.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

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