Abstract: The present invention discloses a method for building a self-learning evidential reasoning system from examples. In this invention a hierarchical model structure for the self-learning evidential reasoning system is defined. After the model structure has been defined examples are supplied by experts. The examples are entered directly into example spreadsheets and then used to train the model structure. The model structure is then trained to minimize error between model output and the desired output. The error is minimized by using a gradient descent optimization. The model structure is then put into production and then used to make a recommendation. The self-learning evidential reasoning system can be used in various fields, such as analyzing the risk of financial service applications.