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Facial Recognition and Loan Approval: Human Judgment with AI Information
Last registered on December 06, 2019

Pre-Trial

Trial Information
General Information
Title
Facial Recognition and Loan Approval: Human Judgment with AI Information
RCT ID
AEARCTR-0005125
Initial registration date
December 05, 2019
Last updated
December 06, 2019 10:20 AM EST
Location(s)
Region
Primary Investigator
Affiliation
Peking University
Other Primary Investigator(s)
PI Affiliation
Peking University
PI Affiliation
Peking University
Additional Trial Information
Status
Completed
Start date
2019-05-19
End date
2019-05-28
Secondary IDs
Abstract
Based on some historical data of online microloan application, repaying performance and facial information, we designed a lab experiment to investigate whether AI prediction can help humans in predicting repayment behavior. We aim to answer the following questions: (1) Do facial photos contain information related to repayment behavior? How can algorithm help humans improve accuracy of judgment? (2) Do humans trust and make use of algorithm predictions effectively? How humans weight their own predictions and algorithm predictions?
External Link(s)
Registration Citation
Citation
Chen, Zeyang, Yu-Jane Liu and Juanjuan Meng. 2019. "Facial Recognition and Loan Approval: Human Judgment with AI Information." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.5125-1.0.
Experimental Details
Interventions
Intervention(s)
Subjects may see one of the four types of loan application randomly:
(1) background information
(2) background information + facial photo
(3) background information + facial credit score given by algorithm (not seeing facial photo)
(4) background information + facial credit score given by subject oneself (not seeing facial photo)
Intervention Start Date
2019-05-19
Intervention End Date
2019-05-28
Primary Outcomes
Primary Outcomes (end points)
(1) Subjects' evaluation of repayment likelihood of each loan applicant.
(2) Subjects' decision to reject or accept each loan applicant.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Within-subject design.
Experimental Design Details
Randomization Method
Randomization done in office by a computer
Randomization Unit
experimental rounds
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
250 subjects
Sample size: planned number of observations
30000 lending decisions (each subject makes 120 decisions)
Sample size (or number of clusters) by treatment arms
7500 lending decisions in each treatment (4 treatment in total)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
May 28, 2019, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
May 28, 2019, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
250 subjects
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
30000 lending decisions
Final Sample Size (or Number of Clusters) by Treatment Arms
7500 lending decisions in each treatment (4 treatments in total)
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS