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Selective Attention in Consumer Finance: Evidence from a Randomized Intervention in the Credit Card Market
Last registered on June 05, 2018


Trial Information
General Information
Selective Attention in Consumer Finance: Evidence from a Randomized Intervention in the Credit Card Market
Initial registration date
June 03, 2018
Last updated
June 05, 2018 11:21 AM EDT
Primary Investigator
Texas A&M University
Other Primary Investigator(s)
Additional Trial Information
Start date
End date
Secondary IDs
In partnership with a Personal Finance Platform in Brazil, I implement a randomized intervention to measure the effect of reminders for timely payment of credit card bills. While I find a 13% reduction in the cost of late fees paid, 31% of the users that avoid credit card late payments, incur instead overdraft fees on their checking accounts. This leads to heterogeneous gains from the intervention with some users saving 15% in total fees paid, and others incurring increased fees of 5%. I interpret these results using theories of salience-driven selective attention, and argue that informational nudges may inflate the perceived importance of the target task. The results of this experiment suggest that when designing policy interventions, one size may not fit all, and targeting nudges to those who are more likely to benefit from them has the potential to significantly increase the gains from the intervention.
External Link(s)
Registration Citation
Medina, Paolina. 2018. "Selective Attention in Consumer Finance: Evidence from a Randomized Intervention in the Credit Card Market." AEA RCT Registry. June 05. https://doi.org/10.1257/rct.3034-1.0.
Former Citation
Medina, Paolina. 2018. "Selective Attention in Consumer Finance: Evidence from a Randomized Intervention in the Credit Card Market." AEA RCT Registry. June 05. http://www.socialscienceregistry.org/trials/3034/history/30331.
Experimental Details
For this intervention, five messages were defined to be sent at different moments of the credit card billing cycle. Three of these messages were designed to be sent early in the billing cycle, to encourage planning. In an attempt to strengthen individuals' mental accounts for credit card payments, the messages encourage users to set some money aside for their next credit card payment. These messages are referred to as "Planning" messages. Two more messages were designed to be sent close to the credit card due date, to invite consumers to make their credit card payment on time. This last set of messages is referred to as "DD Alert" messages.

Treatment Group 1 received both Planning and DD Alert messages and is referred from now on as the Full-Treatment Group. Treatment Group 2 received only DD Alert messages and is referred to as the DD Alert Group from now on. Finally, the Control Group received no messages. All users in the experimental pool were removed from regular message lists sent by the Partner, and therefore received no additional messages.

In addition to the main experimental design, I set aside six thousand randomly selected users as part of a Robustness Treatment Group. Users in this group received different placebos in each of the treated billing cycles. In the first treated billing cycle, they received only the first planning message (24-27 days before the
DD). In the second treated billing cycle, they received five messages from the pool of messages regularly sent by the Partner. These messages were chosen for having the same login rates as the main treatment
messages, but contain no information about late payment fees or credit card due dates.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Late payment fees (extensive and intensive margin);
Overdraft fees (extensive and intensive margin);
Delinquency in other types of credits;
Balances in credit card and checking account;
Transactions per spending category;
Login activity.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
To run the experiment, the Partner company agreed to provide access to the information of 26,069 users, to send them push notifications containing information on credit card due dates and late payment fees over two billing cycles (September 25, 2015 to December 13, 2015), and to send each participant a survey ten days after receiving the last push notification.

The experimental pool corresponds to the universe of users that were charged a late payment fee between August 2014 and April 2015, and whose last login was on or after May 2015. Access is granted for available transactions taking place between August 1, 2015 and January 31, 2016.

The main design consists of randomly assigning 26,069 users into four groups: one Control Group, two main Treatment Groups, and one additional Robustness or alternative-control Treatment Group. This last group is used to investigate explanations alternative to the main limited attention channel proposed in this paper.

The sample is stratified according to the following variables: a dummy variable indicating whether the user had enough balance in his checking accounts at the time when he was charged a late payment fee, a dummy variable indicating whether or not the user receives periodic paychecks, a discrete variable indicating the due date (DD from now on) on the main credit card of every user, and another dummy variable indicating whether or not the gap between DD and paycheck date is between 0 and 15.

Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
26,069 individuals
Sample size: planned number of observations
26,069 individuals over 5 billing cycles.
Sample size (or number of clusters) by treatment arms
Treatment Group 1 received 5,987 users, Treatment Group 2 received 4,038 users, the Robustness Treatment Group received 5,954, and finally the Control Group received 10,090 users.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Northwestern University
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)