Credit Card Statements: Effects of simplification, anchoring and salience on understanding and on repayment decisions.

Last registered on October 31, 2022


Trial Information

General Information

Credit Card Statements: Effects of simplification, anchoring and salience on understanding and on repayment decisions.
Initial registration date
June 02, 2021

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
June 03, 2021, 12:00 PM EDT

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

Last updated
October 31, 2022, 8:02 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation
The Fletcher School | Tufts University
PI Affiliation
Plano CDE
PI Affiliation
Zayed University

Additional Trial Information

Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This laboratory RCT will investigate how simplifying language and reorganizing information in Credit Card Statements affects the understanding of selected information about credit limits and costs associated to repayment and credit card usage. It will also research how anchoring and salience could play a key role in determining individual repayment decisions.
External Link(s)

Registration Citation

Soki, Erika et al. 2022. "Credit Card Statements: Effects of simplification, anchoring and salience on understanding and on repayment decisions. ." AEA RCT Registry. October 31.
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Experimental Details


The experiment will test if using credit card statements with simplified language and design helps individuals make better financial decisions. The idea is that information conveyed by credit card statements tends to be presented in a technical and confusing way, which limits individuals understanding. Therefore, by simplifying the statements, one expects people understand better the use and risk of utilizing this particular financial product.

To assess this hypothesis individuals will be randomly allocated to a control group or one of two treatment groups. The control group will be shown a statement that is similar to those currently available for a local credit card. Treatment group 1, will view an improved statement that changes the design and wording of the document trying to convey better financial information related to repayment options, costs and fees of credit cards. Treatment 2 incorporates the changes in the improved statement as T1, but highlights the lowest interest payment options (salience). All statements are based on the same information and the same hypothetical fees and charges.

Aside from the main intervention related to credit card statements, we want to test if anchoring can affect financial decision making when paying financial obligations. For this purpose we will randomly allocate half of the participants of the control and treatment groups to different payment screens. The control group for this intervention will see a blank form when deciding the amount of the payment they are willing to make, and the treated group will see a prefilled payment form that shows the total amount.

This second intervention is focused on anchoring and pre-filled payment screens. The idea is that pre-filling amounts to pay can nudge individuals to paying the statement in a way it reduces fees and interests associated with the use of the financial product.

Given this design, the experiment will consist of one pure treatment group and 5 treatment branches as follows:
Intervention 1 - Different credit card statements:
- Control (T0)
- Improved statement design and clearer language (T1)
- Improved statement T1 with focus on low interests (T2).

Intervention 2 - Prefilled payment form:
- Control: blank form (Pure Control - T0.0), Prefilled form (T0.1)
- T1: blank form (T1.0), Prefilled form (T1.1)
- T2: blank form (T2.0), Prefilled form (T2.1)
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1. Survey measures of understanding
2. Time to answer
3. Experimental measures of repayment decisions
Primary Outcomes (explanation)
1. Survey measures of understanding: number of correct answers to factual questions
2. Time to answer
3. Experimental measures of repayment decisions:
- Continuous variable indicating the percentage of the payment amount over the statement total amount (the higher the better)
- Continuous variable indicating the total amount of repayment chosen
- Categorical variable indicating frequency of categories of repayment options deemed correct: “total”, “minimum”, “4x installment”, “6x”, etc.

Secondary Outcomes

Secondary Outcomes (end points)
Survey measures of financial literacy
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants will be randomly allocated into one of the following treatment arms: Pure control(T0.0), Control anchored at total value (T0.1), T1 anchored at zero (T1.0), T1 anchored at total (T1.1), T2 anchored at zero (T2.0) and T2 anchored at total (T2.1). Based on the statement presented, participants will be asked to decide on repayment of the credit card and then proceed to respond to a series of survey questions to test their understanding regarding credit card limits, consequences for each repayment option and card costs.
Experimental Design Details
The online panel system will select a balanced sample based on age, gender, and socioeconomic status quotas. We will then collect experimental measures from those eligible to participate until 3,000 observations are reached.

Participants will provide demographic information at the beginning and end of the survey as well as information on financial literacy and selected financial behavior. Statements will be customized to fit the income level reported by the respondent in the initial demographic information data collected. The scenarios for repayment decisions presented to respondents will also be customized based on reported income. All respondents will be asked to decide on repayment in 2 different contexts: one where it is feasible to repay full amount and another when it is necessary to choose from one of the debt-based repayment options on the statement, either revolving credit or installments.

Anchoring effects will be tested at the repayment decisions screens where participants will be randomly assigned to view the answer box prefilled either with zero (0.00) or with the total amount of the statement. The time participants take to provide each answer will also be measured.

We will test the following hypotheses:
H1| Simplifying the language and reorganizing information on the statement enhance cardholders understanding of important information used on repayment decisions
H2| These modifications reduce the time holders take to find the important information used on repayment decisions
H3| Simplifying the language and reorganizing information improve the quality of repayment decisions. Better repayment decisions would be those that minimize interest payments as much as possible
H3a| Inserting highlights in prioritized information improves the quality of repayment decisions regardless of improving understanding
H4| Anchoring the payment box at total amount of the statement rises the repayment values chosen by respondents

Aside from estimating effects for each treatment branch, we foresee evaluating pooled effects to increase statistical power of our interventions (both improved statements vs. control and blank payment forms vs. prefilled forms).
Randomization Method
Respondents will be randomly assigned to view Control, Treatment 1 and Treatment 2 statements by the panel software. Within each group, participant will also be randomly assigned to one of the anchoring effects screens (Pure Control, T0.1, T1.0, T1.1, T2.0, T2.1).
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
No clusters
Sample size: planned number of observations
3,000 individuals
Sample size (or number of clusters) by treatment arms
500 observations for each treatment arm will be collected, totaling 3,000 respondents.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The study will consist of an online lab experiment targeting a total of at least 3,000 participants (500 participants per treatment arm). This sample size assumes an 85% statistical power, 95% of significance level and 10% effect size on right answers to the questions about understanding and decision making.

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
July 26, 2021, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
July 26, 2021, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
3,022 participants
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
3,022 participants
Final Sample Size (or Number of Clusters) by Treatment Arms
1008 participants were allocated to the Control treatment, 1008 to the Simplification treatment, and 1006 to the Salience treatment
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials