Maths and statistics used for bad credit loans

In years gone by, any sort of court judgement or history of a poor credit record would probably exclude you from many types of borrowing. In more recent years lenders have been far more open minded to lend to people with such credit problems.

How can lenders afford to take these risks?

Mathematically, and statistically, a person that has previously defaulted on a credit agreement is far more likely to do so in the future, so why lend to them again.

1  When a loan can be secured on a asset like a home or a car, the risk to the lender is dramatically reduced, and even after the costs of lawyers fees and court fees, most of the lenders money can be retrieved.
2  It would be rare for a lender to offer a sub prime borrower a loan on the same terms as someone with a clean credit record. By adding fees and increasing the rate, more money can be made from each borrower, so statistically when one person defaults; you are making enough money from the other people to cover the losses.
3  If you consider the borrowers personal circumstances at the time of the previous defaulted credit agreement, and then take into consideration the personal circumstances of the person at the time of the new loan application, using mathematical probabilities, you can predict the likelihood of the borrower defaulting on the new loan.

There are many lenders that offer bad credit loans now, especially bad credit secured loans, as the maths does stack up for the money to be leant.