Identify the parameter causing the anomaly in a multivariate dataset
Usually it will not be a single feature value that is responsible for the decision of a ML model. Neural Networks, Random Forests, SVM, etc. intend to transform the input in a more beneficial feature space, where making decisions is more easier for them.

As a draw back, this makes interpratability for humans more intricate. Explainability of ML methods is a whole research field.

You could check out some explainability approaches. For autoencoders for example you could use Layerwise Relevancy Propagation (LRP). https://arxiv.org/pdf/1708.08296.pdf