bad.debt state.owned listed revenue net.profit beta debt.ratio
1 0 0 0 7907 378 1.10 0.44
2 0 0 1 2630 194 1.01 0.07
3 0 1 1 2995 313 0.81 0.10
4 0 1 0 4537 476 1.22 0.85
5 0 0 0 7518 441 0.37 0.28
6 0 1 1 3524 598 0.94 0.08
(D2) VinaLoan is a medium-sized state bank, specializing in providing loans to medium/large firms.
The government recently ordered this bank to provide a large loan to one large firm of their choice, from an approved list of firms.
Dataset B contain information about recent large loans of various banks to various firms, as follows:
bad.debt: whether the loan results in a bad debt, 1 means yes, 0 otherwise.
state.owned: whether the borrower company is state owned.
listed: whether the borrower company is listed
revenue: revenue of the borrower company (billion VND)
net.profit: net profit of the borrower company (billion VND)
beta: the beta coefficient of the borrower company
debt.ratio: the debt ratio of the borrower company
VinaLoan has narrowed down their potential borrowing firms into
Firm A: State-owned, listed, 5500 billion VND revenue, -50 billion VND net profit, beta ratio = 0.5, debt ratio = 0.2
Firm B: State-owned, not listed, 6750 billion VND revenue, 400 billion VND net profit, beta ratio = 0.9, debt ratio = 0.6
Firm C: Not state-owned, not listed, 9500 billion VND revenue, 1050 billion VND net profit, beta ratio = 1.9, debt ratio = 0.9
From each of your models, help VinaLoan’s executives decide which firm they should lend money to with the lowest risk of bad debt?