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Anchors Away! A Large-Scale Trial Testing Approaches to Reducing Credit Card Debt
Last registered on December 21, 2018


Trial Information
General Information
Anchors Away! A Large-Scale Trial Testing Approaches to Reducing Credit Card Debt
Initial registration date
December 18, 2018
Last updated
December 21, 2018 10:32 PM EST
Primary Investigator
Harvard University
Other Primary Investigator(s)
PI Affiliation
Harvard Business School
Additional Trial Information
In development
Start date
End date
Secondary IDs
The aim of the study is to test whether changes to the choice architecture of credit card repayment platforms can encourage customers who have persistently been making very low repayments to increase their average credit card repayments, pay off outstanding balances more quickly, and reduce the interest charges they incur. Specifically, we assess whether adding a "Pay 5%" option to the digital platform provided by a leading bank increases average credit card repayments among these customers. We also assess the effect of removing the "Pay Minimum (2%)" option from the menu provided in the platform. In the first case, the intervention is designed to provide an alternative anchor for customers who cannot pay their full balance, but could pay more than the minimum due. In the second case, the intervention is designed to remove the low anchor altogether and allow customers to make a choice with reference only to the high anchor (the full balance).
External Link(s)
Registration Citation
Buell, Ryan and Michael Hiscox. 2018. "Anchors Away! A Large-Scale Trial Testing Approaches to Reducing Credit Card Debt." AEA RCT Registry. December 21. https://doi.org/10.1257/rct.3414-1.0.
Former Citation
Buell, Ryan, Michael Hiscox and Michael Hiscox. 2018. "Anchors Away! A Large-Scale Trial Testing Approaches to Reducing Credit Card Debt." AEA RCT Registry. December 21. http://www.socialscienceregistry.org/trials/3414/history/39500.
Experimental Details
Customers using the banks smartphone app to make payments on their credit card currently see a choice menu with the following options:Pay closing, Pay minimum, Pay other amount (entered manually). The interventions provide customers with two alternative choice menus:
1. Pay closing, Pay 5%, Pay minimum, Pay other amount
2. Pay closing, Pay other amount
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Aggregated monthly dollar repayment ($)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
• Aggregated monthly repayment as a percentage of monthly balance (%)
• Dollar repayment at transaction level ($)
• Dollar repayment as a percentage of balance at transaction level (%)
• Monthly fees and interest paid ($)
• Whether or not customers pay more than minimum (binary variable, monthly)
• Number of “persistent debt” customers (monthly)
• Whether or not account falls in arrears (binary variable, monthly)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Eligible customers will be randomly allocated to view either the current repayment choice menu or one the two new payment choice menus (the interventions) in their smartphone app when they receive the notification that their monthly payment is due.
Experimental Design Details
Randomization Method
Eligible customers will be randomly assigned by computer algorithm to one of the three experimental groups after blocking on the following baseline covariates: segment (e.g. Persistent Debt, Revolver, All Others), age, product tenure, May 2018 payment, average balance Mar-May 2018, credit limit
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
The total potential sample size is 1,270,481. There will be 74,967 customers in treatment 1, 75,011 customers in treatment 2, and 1,120,503 customers in the control. The intervention will only be seen by customers who choose to pay their credit card via the “Account details” page or the “Statements” page of the bank’s app. This requires the customer to have a transaction account with the bank, in addition to their credit card. Over the previous 12 months approximately 10% of all credit card payments done via the app were done through this channel. We thus expect an effective sample size of approximately 127,000.
Sample size (or number of clusters) by treatment arms
Based on the above we expect effect sample sizes of approximately 7,500 customers in each treatment group and 112,000 in the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Taking into account pre-randomization blocking on key baseline covariates (listed above), the trial is powered to detect a 1% increase payments for the whole sample. For key subgroups (e.g., customers classified in the segments of "persistent debtors" and "revolvers") the trial is powered to detect a 10% increase in payments.
IRB Name
Harvard University-Area Committee on the Use of Human Subjects
IRB Approval Date
IRB Approval Number
Analysis Plan

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Data Publication
Data Publication
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Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)