Humans + AI in Commercial Banking

Last registered on July 25, 2025
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Pre-Trial

Trial Information

General Information

Title
Humans + AI in Commercial Banking
RCT ID
AEARCTR-0016412
Initial registration date
July 18, 2025

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
July 25, 2025, 11:30 AM EDT

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

Locations

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Primary Investigator

Name
Yang Su
Affiliation
Chinese University of Hong Kong
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Other Primary Investigator(s)

PI Name
Wu Zhu
PI Affiliation
Tsinghua University
PI Name
Jiaheng Yu
PI Affiliation
Hong Kong University
PI Name
Leifu Zhang
PI Affiliation
Hong Kong University of Science and Technology (Guangzhou)

Additional Trial Information

Status
On going
Start date
2025-07-01
End date
2027-09-30
Keywords
Behavior, Finance & Microfinance
Additional Keywords
AI
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The rapid development of AI has greatly affected the workplace, with even greater potential to be unleashed in the short future. While in simple tasks AI may completely replace humans, in more complicated tasks the approach is more likely to be "AI + Humans", where humans oversee the actions of AI and humans make the final decisions. This approach is based on the assumption that such "AI + Humans" approach can out-perform Humans alone or AI alone. We examine the performance of "AI + Humans" for the credit screening task in the commercial banking sector using randomized controlled trials.
We will first develop an AI assistant by training the popular general AI models using the bank historical lending data. We will then ramdonly open this AI assistant to human loan officers so that these human loan officers can seek advice from the AI assistant. We then examine how this AI-assisted humans perform relative to the AI assistant alone or other human loan officers alone. In particular, in scenarios where AI make more (less) accurate credit risk assessment, whether and when humans follow (ignore) AI's advices? What are the policy implications that can lead to better human uses of AI assistant?
External Link(s)

Registration Citation

Citation
Su, Yang et al. 2025. "Humans + AI in Commercial Banking." AEA RCT Registry. July 25. https://doi.org/10.1257/rct.16412-1.0
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Experimental Details

Interventions

Intervention(s)
We will develop an AI assistant by training the popular general AI models using the bank historical lending data. The intervention would be: a random group of human loan officers will be allowed to use this AI assistant while others cannot.
Intervention Start Date
2025-09-01
Intervention End Date
2026-09-30

Primary Outcomes

Primary Outcomes (end points)
The loan application approval rate and the performance of approved loans.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will open the AI assistant to a subset of human officers. We shall require them to upload relevant loan application information for the AI assistant to process. We will record the human loan officers' assessment, the AI assessment, and the final action taken by the human officers.
Experimental Design Details
Not available
Randomization Method
We will assign the AI assistants to human loan officers with staff ID that ends with an odd number.
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 loan officers.
Sample size: planned number of observations
5000 loan applications.
Sample size (or number of clusters) by treatment arms
100 loan officers control, 50 loan officers with access to AI Assistant Version 1, 50 loan officers with access to AI Assistant Version 2.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan