Algorithms for Anomaly Detection of Event Sequence Data [Python/R]
A simple comparison is to use the reconstruction error as the anomaly score.
This can be done instead of, or in addition to, the Local Outlier Factor that you have now.
You can also try other ways of computing the anomaly score from the latent feature vector. Some popular alternatives are:

Mahalanobis distance on the
Fitting a Gaussian Mixture Model, and use the probability density function

A completely different approach would be to use a self-supervised training setup instead of the autoencoder. Such as Skip-Gram or predicting future time-frame.