The Impact of Computer-Generated Credit Scoring on Lending in Colombia

Last registered on February 08, 2017


Trial Information

General Information

The Impact of Computer-Generated Credit Scoring on Lending in Colombia
Initial registration date
February 08, 2017

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
February 08, 2017, 7:48 PM EST

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
London School of Economics

Additional Trial Information

Start date
End date
Secondary IDs
We distinguish the impact of information technology adoption on information processing costs and agency costs by conducting a randomized control trial with a bank that adopts a new credit-scoring tool. The availability of scores significantly increases credit committees' effort and output on difficult-to- evaluate loan applications. Output increases almost as much in a treatment where the committee receives no new information, but anticipates the score becoming available after it evaluates a application, which suggests that scores reduce incentive problems inside the credit committee. We also show that scores improve efficiency by decentralizing decision-making and equalizing marginal returns across loans.
External Link(s)

Registration Citation

Paravisini, Daniel and Antoinette Schoar. 2017. "The Impact of Computer-Generated Credit Scoring on Lending in Colombia." AEA RCT Registry. February 08.
Former Citation
Paravisini, Daniel and Antoinette Schoar. 2017. "The Impact of Computer-Generated Credit Scoring on Lending in Colombia." AEA RCT Registry. February 08.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Effects of computer-generated credit scores on small enterprise loans; Impact of information technology adoption on decision-making
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We implement a four-month pilot program with an RCT design in eight urban branches. In each pilot branch we randomly select the treatment applications for which the committee will be able to see the score of the applicant. Randomization occurs in real time when the committee begins to discuss an application. The committee members are informed of the group assignment at the beginning of the discussion.

In the control group, the committee evaluates the application without observing the score. In the first treatment group (T1), the committee receives the score before evaluating the application. This first treatment allows us to measure the overall effect of scores on committee effort, output and productivity. In the second treatment group (T2), the committee evaluates the application and chooses an interim action before receiving the score, receives the score after taking the interim action, and then may revise its choice to take a final action.
Experimental Design Details
Randomization Method
Randomization by computer
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
1,421 individuals
Sample size: planned number of observations
1,421 individuals
Sample size (or number of clusters) by treatment arms
335 individuals in the control group
563 individuals in treatment group 1 (T1)
523 individuals in treatment group 2 (T2)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Intervention Completion Date
May 31, 2011, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
June 30, 2011, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
1,421 individuals
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1,421 individuals
Final Sample Size (or Number of Clusters) by Treatment Arms
335 individuals in the control group, 563 individuals in T1, 523 individuals in T2
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Paravisini, Daniel, and Antoinette Schoar. "The Incentive Effect of IT: Randomized Evidence from Credit Committees." NBER Working Paper No. 19303, August 2013.

Reports & Other Materials