Rating Models and Validation - Oesterreichische Nationalbank

Rating Models and Validation
Chart 19: Architecture of an Artificial Neural Network
Chart 20: How Neurons Work
This transformed value is passed on to all downstream neurons, which in
turn carry out the same procedure with the output factors from the upstream
neurons. Chart 20 gives a schematic depiction of how a neuron works. In general,
other nonlinear functions can be used instead of the logistic function.
Once the information has passed through the inner layers, it is delivered to
the neuron in the output layer. This information represents the networkÕs output,
or the result generated by the artificial neural network. The inner layers
are also referred to as hidden layers because the state of the neurons in these
layers is not visible from the outside.
Training of Artificial Neural Networks
An artificial neural network learns on the basis of training data sets for which
the actual correct output is already known. In the training process, the artificial
neural network compares the output generated with the actual output and
46 Guidelines on Credit Risk Management