RCT in FinTech Lending

Last registered on March 26, 2020
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Pre-Trial

Trial Information

General Information

Title
RCT in FinTech Lending
RCT ID
AEARCTR-0005489
Initial registration date
March 26, 2020

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
March 26, 2020, 1:24 PM EDT

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

Locations

Country
China
Region

Primary Investigator

Name
Steven Xiao
Affiliation
University of Texas at Dallas
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Other Primary Investigator(s)

PI Name
Han Xia
PI Affiliation
University of Texas at Dallas
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PI Name
Xiaoxiao Tang
PI Affiliation
University of Texas at Dallas
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Additional Trial Information

Status
In development
Start date
2020-03-01
End date
2021-12-31
Keywords
Finance & Microfinance
Additional Keywords
FinTech, Consumer Credit
JEL code(s)
G20, G50
Secondary IDs
Abstract
We collaborate with a leading Chinese FinTech lending company, to conduct a randomized controlled trial (RCT) to test for information asymmetry in the FinTech consumer credit market. In the experiment, we plan to manipulate three contract terms: interest rate, loan amount, and time to maturity, and offer randomized contracts to loan applicants. We then observe the impact of various treatments (contracts) on: (1) contract acceptance rate by borrowers, (2) loan default rate among the executed loans, (3) gross and net IRR of the loan. We hypothesize that among the pool of borrowers that share the same level of credit score, those who accept less favorable contract terms (e.g. higher interest rate, lower loan amount, and shorter time to maturity) tend to have higher unobservable credit risk, and have higher default rate that cannot be fully explained by credit score. Further, we hypothesize that there may exist a group of borrowers for whom none of the offered contracts can result in profitable lending (on average) because of the adverse selection problem.
External Link(s)

Registration Citation

Citation
Tang, Xiaoxiao , Han Xia and Steven Xiao. 2020. "RCT in FinTech Lending ." AEA RCT Registry. March 26. https://doi.org/10.1257/rct.5489-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The company will manipulate three contract terms: interest rate, loan amount, and time to maturity.
Intervention Start Date
2020-03-01
Intervention End Date
2020-07-30

Primary Outcomes

Primary Outcomes (end points)
(1) contract acceptance rate by borrowers, (2) loan default rate among the executed loans, (3) gross and net IRR of the loans.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The company will randomly manipulate three contract terms it offers to a loan application: interest rate, loan amount, and time to maturity.
Experimental Design Details
Randomization Method
Randomization done by computer.
Randomization Unit
Individual
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
3 to 6 credit score groups.
Sample size: planned number of observations
4000-5000 customers.
Sample size (or number of clusters) by treatment arms
All customers are treated with different contracts.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Texas at Dallas
IRB Approval Date
2020-03-24
IRB Approval Number
IRB 20-61
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