Loan Decision Scenario

Credit applications nowadays are typically assessed by automated systems and often approved or rejected within seconds, without human intervention. This loan scenario simulates such an automated loan decision pipeline in order to explore potential questions one may ask about the pipeline and its decisions.

In this scenario, a credit institution employs a loan application assessment process that relies on the risk factor of the loan application, which is calculated by a machine learning model. The model was trained from historic loan performance data and takes into account a variety of data:

  • the borrower: income, employment length, FICO score, debt-to-income ratio, etc.
  • the loan: the loan amount, loan purpose, loan grade, interest rate

In this demonstrator, a loan dataset was used to build the decision pipeline that provides recommendations on whether to approve or reject a loan application based on the characteristics of the borrower and the loan itself.

Try out the scenario

You can play the role of a customer applying for a loan by following the following steps:

  1. Simulate a loan application: filling in a loan application - the data will be randomly picked from our dataset for you.
  2. Submit the application: the application will go through the automated decision pipeline and a decision will be produced.
  3. Understand the decision: explanations will be offered to answer a number of questions often asked by an applicant in this scenario.

Recent simulations

Loan ID Amount Term Purpose Submitted
638023 $5600.00 36 months credit_card 11 hours, 36 minutes ago
561670 $10000.00 36 months credit_card 1 day, 17 hours ago
760914 $10000.00 60 months debt_consolidation 1 day, 23 hours ago
631412 $5000.00 36 months debt_consolidation 5 days, 3 hours ago
778338 $10000.00 60 months car 6 days, 18 hours ago