||A connection between monetary policy and financial stability belongs to one of the most discussed topics of monetary economics in the recent years. One of the strands of this research focuses on the augmented Taylor rules with financial variables. As current studies show, a direct incorporation of financial variables into the Taylor rule can bring macroeconomic benefits in terms of lower volatility of inflation and output, and can also contribute to a more accurate setting of a policy interest rate. A new research possibility in this area appears with an emergence of mathematical methods that can solve DSGE models with non-linear characteristics. As it has been shown in several studies, non-linear models are able to better reflect present asymmetries in the dynamics of economic variables than linear models. Therefore, it is expected that the results implied from the augmented Taylor rules in a linear environment can be different from those of the models accounting for non-linearities. This project aims to combine two modelling techniques: a DSGE model with a banking sector and its non-linear solution using non-linear techniques. Such a combination should better reflect reality, and thus help to understand a performance of the augmented Taylor rule with financial variables.