Visual Nudges in Lending

Last registered on September 21, 2025
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Pre-Trial

Trial Information

General Information

Title
Visual Nudges in Lending
RCT ID
AEARCTR-0014536
Initial registration date
October 08, 2024

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 18, 2024, 4:40 PM EDT

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

Last updated
September 21, 2025, 5:21 PM EDT

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

Locations

Country
China
Region
Shenzhen

Primary Investigator

Name
Joon Sang Yoon
Affiliation
Chinese University of Hong Kong, Shenzhen
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Other Primary Investigator(s)

PI Name
Regina Wittenberg-Moerman
PI Affiliation
Kellogg School of Management, Northwestern University
Contact Investigator
PI Name
Tianyu Zhang
PI Affiliation
The Chinese University of Hong Kong, Shenzhen
Contact Investigator
PI Name
Kanyuan Huang
PI Affiliation
The Chinese University of Hong Kong, Shenzhen
Contact Investigator
PI Name
Mengwei Tang
PI Affiliation
The Chinese University of Hong Kong, Shenzhen
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Additional Trial Information

Status
In development
Start date
2025-09-15
End date
2025-12-15
Keywords
Finance & Microfinance
Additional Keywords
Visual nudges, bank lending, access to credit
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this study, we examine whether providing a simple visual nudge by labeling the loan product can change borrowers’ loan choices, potentially helping them make better decisions. We work with a government-backed online lending platform in China. The platform allows borrowers to directly borrow money from banks. Banks will list their loan products on the platform. Any individual with a valid Chinese ID can register with the platform and apply for loans. We randomly assign borrowers into one of the following four groups: 1) a control group with no label; 2) a treatment group where a label is placed on the loan with the lowest interest rate; 3) a treatment group where a label is placed on the loan with the fastest processing time; and 4) a treatment group where a label is placed on the loan with the highest approval rate. By comparing borrowers’ loan choices between the control and treatment groups, we estimate the causal impact of visually salient labels on borrower decision-making in consumer lending.
External Link(s)

Registration Citation

Citation
Huang, Kanyuan et al. 2025. "Visual Nudges in Lending." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.14536-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
We work with a government-sponsored lending platform in China. When borrowers apply for loans on the platform, the platform will prompt a survey asking the borrower to fill in basic background information, such as education and income range, as well as their requested loan amount maturity, and the ability to provide collateral.
Based on the borrower’s loan application, the platform will recommend five loan products to the borrower. The borrower can apply for one or more of those recommended loans. Once the borrower applies, the bank is notified and will start to process the loan application.
Treatment: Once the borrower completes the survey, she will be randomly assigned to one of the following groups:
a. Control group: no label.
b. Treatment 1: Lowest rate label – we place a label on the loan with the lowest interest rate.
c. Treatment 2: Fastest processing time label - we place a label on the loan with the fastest processing time
d. Treatment 3: Highest success rate label - we place a label on the loan with the highest approval rate.
We observe whether the borrower applies for a loan and which loan product the borrower picks.
Intervention (Hidden)
We work with a government-sponsored lending platform in China. When borrowers apply for loans on the platform, the platform will prompt a survey asking the borrower to fill in basic background information, such as education and income range, as well as their requested loan amount maturity, and the ability to provide collateral.
Based on the borrower’s loan application, the platform will recommend five loan products to the borrower. The borrower can apply for one or more of those recommended loans. Once the borrower applies, the bank is notified and will start to process the loan application.
Treatment: Once the borrower completes the survey, she will be randomly assigned to one of the following groups:
a. Control group: no label.
b. Treatment 1: Lowest rate label – we place a label on the loan with the lowest interest rate.
c. Treatment 2: Fastest processing time label - we place a label on the loan with the fastest processing time
d. Treatment 3: Highest success rate label - we place a label on the loan with the highest approval rate.
We observe whether the borrower applies for a loan and which loan product the borrower picks.
Intervention Start Date
2025-09-15
Intervention End Date
2025-12-15

Primary Outcomes

Primary Outcomes (end points)
1. Whether the borrower applies for a loan.
2. The loan products that the borrower selects.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We work with a government-sponsored lending platform in China. When borrowers apply for loans on the platform, the platform will prompt a survey asking the borrower to fill in basic background information, such as education and income range, as well as their requested loan amount maturity, and the ability to provide collateral.
Based on the borrower’s loan application, the platform will recommend five loan products to the borrower. The borrower can apply for one or more of those recommended loans. Once the borrower applies, the bank is notified and will start to process the loan application.
Treatment: Once the borrower completes the survey, she will be randomly assigned to one of the following groups:
a. Control group: no label.
b. Treatment 1: Lowest rate label – we place a label on the loan with the lowest interest rate.
c. Treatment 2: Fastest processing time label - we place a label on the loan with the fastest processing time
d. Treatment 3: Highest success rate label - we place a label on the loan with the highest approval rate.
We observe whether the borrower applies for a loan and which loan product the borrower picks.
Experimental Design Details
We work with a government-sponsored lending platform in China. When borrowers apply for loans on the platform, the platform will prompt a survey asking the borrower to fill in basic background information, such as education and income range, as well as their requested loan amount maturity, and the ability to provide collateral.
Based on the borrower’s loan application, the platform will recommend five loan products to the borrower. The borrower can apply for one or more of those recommended loans. Once the borrower applies, the bank is notified and will start to process the loan application.
Treatment: Once the borrower completes the survey, she will be randomly assigned to one of the following groups:
a. Control group: no label.
b. Treatment 1: Lowest rate label – we place a label on the loan with the lowest interest rate.
c. Treatment 2: Fastest processing time label - we place a label on the loan with the fastest processing time
d. Treatment 3: Highest success rate label - we place a label on the loan with the highest approval rate.
We observe whether the borrower applies for a loan and which loan product the borrower picks.
Randomization Method
We work with the lending platform to implement a dual-randomization design—across both treatment assignment and loan order, which enable us to examine the causal effect of visually salient labels on borrower loan choices.

Treatment assignment randomization: we randomly assign a borrower to the control group or one of the three treatment groups. The randomization is done via a random number generator that generates a number between 1 to 4. The probability of entering each group is 25%.

Loan order randomization: we also randomize the order in which loan products are displayed. This ensures that the labeled loan is equally likely to appear in any position on the loan product list (i.e., first, second, third, etc.)
Randomization Unit
Treatment assignment is randomized at the individual borrower level; loan order randomization is implemented at the loan level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No
Sample size: planned number of observations
About 1,500 borrowers.
Sample size (or number of clusters) by treatment arms
Approximately 1,500 borrowers divided into four groups, with about 375 in the control group, and 375 in each of the treatment arms.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Chinese University of Hong Kong (Shenzhen)
IRB Approval Date
2024-04-01
IRB Approval Number
CUHKSZ-D-2024051
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials