Should I (and if yes, how can I) assure channel-dependant temporal accuracy in a filterbank?
Using different filter lengths for different channels is basically what the Wavelet Transform does. I think it basically addresses this issue. Wavelet transforms divide the spectrum up into spectral bins of unequal width. There are efficient options for computing the Wavelet Transform (a tree structured filter bank approach usually).

In the linked Wikipedia Article, you can see a picture comparing the time-frequency tiling of the STFT to that of the Wavelet Transform. It is directly applicable to your question.



I realize that I addressed the "How can I" part of your question, but not the "Should I" part... I'm not sure I can answer the "Should I" part unless I am given more information regarding the target application. So, I will briefly say that Wavelets have found widespread use in compression and image recognition. They are often helpful for multiresolution analysis which (in rough terms) is when one wishes to find something of a certain shape but has no idea how large it will be (for example a pulse of a certain shape that may have been compressed or expanded significantly). If you don't require these types of properties, then a uniform filter bank is often the way to go.