: The necessity of addressing privacy legislation and ensuring "equal opportunity" to mitigate algorithmic bias in credit decisions.
Replaced human bias with statistical algorithms capable of processing high volumes of applications instantly. credit scoring and its applications by l c thomas hot
Moving beyond simple default prediction, the authors champion . Instead of just asking "Will they default?", this approach asks "How much profit will this customer generate?" This integrates marketing costs, interest margins, and operational costs into the scoring model. : The necessity of addressing privacy legislation and
: Deciding whether to give a loan to a new customer. credit scoring and its applications by l c thomas hot
Thomas distinguishes clearly between different types of scoring:
The text separates quantitative retail lending into two primary phases based on the customer lifecycle: