A common narrative for loan providers is financial inclusion. 69% of global
adult population is not covered by credit bureaus. Using non-traditional data
(e.g. text messages, location, contacts, call logs), more people can get scored.
If only \(x\%\) of people pay you back, then \(\frac{x}{100}(1 + r) \ge 1
\) suggests \(r \ge \frac{100}{x} - 1 \). If \(75\%\) tend to pay back,
\(r = 33\frac{1}{3} \%\).
If the rate is actuarily fair and is conveyed clearly to borrowers, is there a
moral issue? If your math says lots of people will default and you choose to go
ahead anyway, what does that make you?
If only \(x\%\) of people pay you back, then \(\frac{x}{100}(1 + r) \ge 1 \) suggests \(r \ge \frac{100}{x} - 1 \). If \(75\%\) tend to pay back, \(r = 33\frac{1}{3} \%\).
If the rate is actuarily fair and is conveyed clearly to borrowers, is there a moral issue? If your math says lots of people will default and you choose to go ahead anyway, what does that make you?
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