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Success Case by Tekne

Credit Documentation Project

Financial Fintech Industry

Problematic

  • Credit applications with a high probability of not completing the necessary documentation requirements cannot be detected in time, which leads to the sale of a financial product not being completed.

Objective

Establish with an acceptable degree of certainty, considering the history reflected in the database, the probability that a credit application file is on the way to completing 80% progress.

Models

Construction and implementation of a Machine Learning solution for:

  • Identify the key variables
  • Predict which cases are more likely to not complete the requirements for the credit application
  • Profile customers to offer other financial products

Results

  • It was possible to identify in time the files with a low probability of progress, allowing better management of the cases
  • The variables that most influence the credit application process were defined
  • An increase in successfully completed applications was recorded

Initial Situation

Without model

26%

of requests did not reach 80% progress

Final Situation

With model

97.3%

effectiveness in predicting cases with a low probability of progress

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