ML Scenario
step aside it's tImE for bicc boi's worK.
ML Scenario
Credit-card approving is a good machine learning scenario. Banks earn from late payment fees, overdraft, and interest if a credit-card owner pays late, but does not default. Hence, it could be lucrative if the bank can put a model to this. Running through the pointers as discussed previously
There is likely to be a pattern or trend of the type of people (demographics, lifestyle, and etc.) defaulting in credit-card payments
There is no straightforward mathematical formula to tell if a person will be defaulting in the future (sorry )
A bank is likely to store a lot of historic data of credit-card holders whom have defaulted (and not)
Data Set
In a blatantly fictitious data set,
Name | Age | Gender | Salary | Debt | Default |
Alice | 23 | Female | 24000 | - | 1 |
Bob | 32 | Male | 30000 | 10000 | 0 |
Charlie | 34 | Male | 36000 | 5000 | 0 |
Danielle | 25 | Female | 33000 | 5000 | ??? |
would we know if Danielle is likely to default in her credit-card payment? Stay-tuned.
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