Credit risk assessment is the groundwork of the
individual housing loans. However, what banks really care about
is how to make the most money with least risk. The most difficult
problem of the credit risk management for the banks is that they
both have to encourage loans, but also they need to avoid bad
debt. This paper proposes a new risk assessment system of the
individual housing loans by integrating traditional Analytic
Hierarchy Process and Grey System Theories into Data Mining
and applies the new hybrid method to assess the individual credit
risk. It is proved that this new credit risk assessment method is
easy to calculate, and provides an effective foundation for credit
risk assessment.