Mental Accounting in Household Finance: Evidence from FinTech

Last registered on October 31, 2022

Pre-Trial

Trial Information

General Information

Title
Mental Accounting in Household Finance: Evidence from FinTech
RCT ID
AEARCTR-0010069
Initial registration date
October 21, 2022

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
October 31, 2022, 10:45 AM EDT

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

Locations

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Primary Investigator

Affiliation
Ludwig-Maximilians-Universität München

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-08-01
End date
2023-03-04
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We set up a controlled marketing campaign within the mobile app of a European bank. In particular, we nudge treated users to create and use separate sub-accounts to explicitly implement mental accounting in their personal finances: The banks' clients are recommended to create separate banking accounts for their day to day finances, i.e. for things that they "need" to buy and things that they "want" to buy, for their buffer savings, and for their short- and medium-term goals (e.g., a new laptop or a new car). We subsequently measure the effect of using sub-accounts, i.e. adopting mental accounting, on the clients' financial behaviour. This includes changes in income, spending, and saving. We further conduct a survey to measure whether the application of mental accounting has increased the client's subjective financial health.
External Link(s)

Registration Citation

Citation
Federle, Jonathan. 2022. "Mental Accounting in Household Finance: Evidence from FinTech." AEA RCT Registry. October 31. https://doi.org/10.1257/rct.10069-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-11-01
Intervention End Date
2022-12-04

Primary Outcomes

Primary Outcomes (end points)
In general the key outcome of interest is if and how the intervention changes a customers's overall income, spending and saving behaviour compared to the control group. To investigate this we observe in-app behaviour such as usage of main- and sub-accounts, saving goals for sub-accounts, and automatic transfers to sub-accounts. Moreover, we also observe financial behaviour such as financial transactions in the main- and sub-accounts. This way we can observe if and to what extent customers adopt mental accounting principles and how this impacts their income, spending and savings behaviour.

Moreover, customers in both the control and treatment group receive a survey eliciting their subjective financial health according the the Consumer Financial Protection Bureau, financial literacy, app usage and some personal information. Please see Complementary Survey in Docs & Materials for the survey questions.
Primary Outcomes (explanation)
Subjective financial health, or the financial well-being score will be constructed from five survey questions. See CFPB financial well-being scale in Docs & Materials for further information.

Secondary Outcomes

Secondary Outcomes (end points)
In general secondary outcomes of interest are if and how customers engage with the marketing campaign itself. To investigate this we observe in-app behaviour such as clicks on in-app messages and logins. Moreover, we will also observe how customers engage with emails, push-notifications and blogs on the company's website.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Does a consumer’s financial health increase if he/she engages in explicit mental accounting? To answer this question we run a field experiment together with a mobile bank. Treated customers will be informed and educated on “How to manage your financial health using sub-accounts” in a five week marketing campaign. More specifically, they will be will be informed and educated on how to use sub-accounts to manage everyday spendings and savings, how to use automated transfers to budget and save automatically and how to use specific app-setting to further adopt mental accounting. After the campaign we observe customer's objective and subjective financial health to investigate (i) if customers who were exposed to the campaign are more financially healthy than customers who were not, and (ii) if customers who explicitly adopted mental accounting, e.g. are using sub-accounts to manage their finances, are more financially healthy than customers who do not.
Experimental Design Details
Not available
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?
No

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 100,000-200,000 bank 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 50,000-100,000 bank customers, i.e. 50,000-100,000 bank customers in the control group and 50,000-100,000 bank customers in the treatment group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The minimum detectable effect size on the 10% significance level for our main outcomes are the following: Increase in usage of sub-accounts: 0,13-0,18%, 0,3464 (standard deviation) Increase in usage of goals for sub-accounts: 0,13-0,18%, 0,3464 (standard deviation) Increase in usage of automatic transfers to sub-accounts: 0,05-0,07%, 0,1386 (standard deviation) Increase in money saved in sub-accounts: 1,63-2,31€, 444,00€ (standard deviation) Increase in subjective financial health: 0,35-0,49 points, 21 points (standard deviation) Please note that the values are based on results from previous marketing campaigns and surveys run by the project partner. See Power Calculations in Docs & Materials for further information.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia University IRB
IRB Approval Date
2022-10-01
IRB Approval Number
AAAU3701