Scoring for microfinance institutions

Assessment of the probability of default on a short-term loan of a microfinance institution, based on the data from the borrower’s credit history

Short-term loans have their own specifics and target audience. A highly specialized model allows microfinance institutions to more accurately predict risks for their products.

Contents
Identification
Borrower’s current ID data and the history of changes made to it.
Scoring
A value from 0 to 300 that determines the probability of late payments of over 100 UAH that are at least 30 days past due within a 6-month period on a credit by a microfinance institution.
Model
Target function
Late payment of over 100 UAH at least 30 days past due within a 6-month period on a credit from a microfinance institution.
Predictors
Credit history characteristics
Method
Gradient boosting
0.84
ROC-AUC
0.51
KS
Default probability based on scoring
Report processing

After the Agreement-Application has been signed, and login and password have been obtained, a report can be requested through:

XML
This method of reporting enables the automated processing of requests, and provides reports in the format of your choice.
 
General structure of interaction:
 
Http Method
 
POST
 
Request URL
 
 
Test URL
 
 
Request   
 
 
Response
 

 Requesting a report is possible only subject to the individual’s consent

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