This research develops the settlement mechanism in the Real Time Gross Settlement
using so called clearing house through a serious game method. In this approach banks are
represented as nodes that do the settlement process according to the simple rules. Moreover, the
graph mining approach is used for predicting the activity networks on those banks. As the result,
for constant nodes indicate that the more the activity networks among banks are available, the
more the activity networks can be identified. Furthermore, the smaller the differences among the
bank health?s level are, the greater the network activities can be identified. This behavior is a
consequence of chosen fixed point assumption.