The impact of digital business assessment tools on entrepreneurship: experimental evidence from FinTech clients in Brazil

Last registered on August 14, 2024
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Pre-Trial

Trial Information

General Information

Title
The impact of digital business assessment tools on entrepreneurship: experimental evidence from FinTech clients in Brazil
RCT ID
AEARCTR-0014011
Initial registration date
August 11, 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
August 14, 2024, 2:44 PM EDT

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

Locations

Country
Brazil
Region

Primary Investigator

Name
Diego Vera Cossio
Affiliation
Inter-American Development Bank
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Other Primary Investigator(s)

PI Name
Irani Arraiz
PI Affiliation
IDB Invest
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PI Name
Carlos Scartascini
PI Affiliation
Inter-American Development Bank
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PI Name
Maria Laura Lanzalot
PI Affiliation
IDB Invest
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PI Name
Emiliano Diaz Del Valle
PI Affiliation
Busara Center for Behavioral Economics
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PI Name
Cristina Parrilli
PI Affiliation
Wharton Business School, Univeristy of Pennsylvania
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Additional Trial Information

Status
In development
Start date
2024-08-20
End date
2025-12-31
Keywords
Finance & Microfinance, Firms & Productivity
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study the impacts of a business diagnostictool delivered to entrepreneur clients or potential clients of one of Brazil's largest FinTech lender. The intervention consists of an online business assessment tool that identifies areas for improvement, and provides entrepreneurs with educational videos that target those areas of improvement. We use a waitlist design to implement this intervention. The treatment group completes the tool earlier while the control group will complete six months later. We aim at studying the effects of the intervention on two set of outcomes. First, we will focus on the impacts on business practices. Second, we will study the impacts on loan repayment, take up and approval of new loans, and credit scores. The intervention will be implemented on sample of entrepreneurs who are either current clients of the partner financial institution (FI), former clients of the financial institution, or individuals that applied for a loan but were denied a loan from the partner FI. We will analyze heterogeneous effects across these three groups, and across other key dimensions such as gender, age, economic sector, ex-ante credit worthiness, and length of their relationship with the lender.
External Link(s)

Registration Citation

Citation
Arraiz, Irani et al. 2024. "The impact of digital business assessment tools on entrepreneurship: experimental evidence from FinTech clients in Brazil." AEA RCT Registry. August 14. https://doi.org/10.1257/rct.14011-1.0
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Experimental Details

Interventions

Intervention(s)
The intervention consists of an online business diagnostic tool (BDT) that identifies areas for improvement, and provides entrepreneurs with educational videos that target those areas of improvement.

Individuals assigned to the treatment group will receive an email invitatiion from the partner FI to complete the BDT online. Upon completion of the BDT, participants will obtain an score and will be offered taylored recommendations based on the areas that the BDT identifies as needing improvement. The recommendations will be delivered through short videos.
Intervention Start Date
2024-08-20
Intervention End Date
2025-12-31

Primary Outcomes

Primary Outcomes (end points)
self-reported business practices related to the 3 pillars targeted by the BDT: business basics and separation of personal from business accounts, financial planning, and business financing.
Primary Outcomes (explanation)
For each pillar, we will construct an index based on the responses to each of the questions within a pillar. Each pillar has a number of questions about specific concepts. We will generate a score for each pillar based on the number of answers that align with the best business practices within each subgroup. We will then normalize this score so that is comparable across pillars.

Secondary Outcomes

Secondary Outcomes (end points)
Administrative data: debt repayment, applications for new loans, take-up of new loans, terms of new loans, and credit scores.

For all those in the target populations who recently applied for a loan and met pre-qualification requirements (including all current customers), we are able to access a comprehensive credit report. This includes both a numeric risk score as well as data on whether the customer has missed loan payments or is over-indebted.
○ For current customers, we are able to observe loan repayment data.
Secondary Outcomes (explanation)
We will construct dummy variables based on each of the aforementioned indicators.

Experimental Design

Experimental Design
Waitlist design with a pure control group.

1.Intervention group. This group will receive a personalized invitation and ongoing encouragement to utilize the tool at the beginning of the evaluation period.
2. Waitlist control (delayed intervention group). This group will receive the invitation to engage with the intervention after a delay period of 6 months to allow for the impact of the business diagnostic tool to be felt.
3. Pure control. This group will not receive an invitation to use the business diagnostic tool. Instead, we will collect only administrative data on this group, to compare their business success to those who received the tool. However, we expect that some members of this group will utilize the business diagnostic tool if and when it is made available to all Creditas customers, and we will monitor this group's uptake of the treatment to determine (a) the ‘natural’ rate of takeup of the product; and (b) determinants of takeup.

We choose to divide the groups in this way because of a fundamental measurement issue: the self-reported outcome measures are generated through the process of being treated. The pure control group enables us to measure outcomes in the longer term that will be measured with administrative records (debt repayment, loan uptake, and information in the credit bureau).
Experimental Design Details
Not available
Randomization Method
randomization done in office by computer. Stratified by two groups:
1) current clients.
2) previous clients or individuals who applied for a loan but whose application was previously denied.

Within each group we will stratify by gender and region (state).
Randomization Unit
individual-level randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Sample 1: current clients 14,000 individuals

Sample 2: prospective clients 283,000 individuals
Sample size: planned number of observations
297,000 individuals
Sample size (or number of clusters) by treatment arms
Sample is equally split across a treatment group, a waitlist control group, and a pure control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Sample 1 (current clients): MDE survey outcomes 0.19 SD. MDE admin records: 4 percentage points. Assumption: Response rate 0.05. Sample 2 (prospective clients). MDE survey outcomes 0.09SD. MDE admin records: 1.3 percentage points. Assumption: Response rate 0.01
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
HML IRB
IRB Approval Date
2024-06-25
IRB Approval Number
2571
Analysis Plan