In the literature there are several generalzations of the standard logistic distribution. Most of them are included in the generalized logistic distribution of type 4 or EGB2 distribution. However, this four parameter family fails in modeling skewness absolutly greater than 2 and kurtosis higher than 9. To remove the shortcoming, and additional parameter is introduced. Unfortunately, there is now no closed form for the probability density function of the generalized EGB2, briefely called FEGB2 of generalized logistic distribution of type 5. However it can be approximated numerically, for example by saddlepoint approximation or numerical integration methods. Finally, FEGB2 is used for modeling returns of financial data.