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Table 4 Parameters and criteria adopted to classify borrowers according to banks’ experience

From: To supervise or to self-supervise: a machine learning based comparison on credit supervision

Parameters Description
Banks 20 biggest loan portfolios in financial system at the starting date (June/2019)
Extraction dates December/ 2016; December, 2017; December 2018
Good borrowers Rated as AA, A or B (LLP inferior to 3%) in each one of the last seven months previously to the dates chosen for extractions
Bad borrowers Rated as F, G or H (LLP equal or higher than 50%) in each one of the last three months previously to the dates chosen for extractions. A bad borrower was excluded from the dataset if, in the 6-month period after extraction dates: (1) the debt was paid; (2) the debt was reduced; (3) the rating assigned by the bank improved
Materiality Loans in excess of R$ 200,000a
  1. aApproximately US$ 40,000