There has been a lot said about the application of AI, ML and Neural Networks in trading for predictive modelling. I was unable to find any relevant examples that prove a credible output based on these applications.
AI, ML and NNs are generic algorithms or methods which leverage data agnostically. In other words, they can be deployed with data of any type be it digital, economic, financial, whatever. That said, most of the good examples are proprietary, hence your difficulty in identifying specific models.
1) Estimating risk is an essential element in finance. This paper Deep Learning for Mortgage Risk is a good example of that: https://arxiv.org/pdf/1607.02470.pdf
2) Kaggle has had some financial challenges: https://www.kaggle.com/tags/finance
3) Didier Sornette's Financial Crisis Observatory has links to his market bubble predictor model which is, to a large extent, automated. http://www.er.ethz.ch/financial-crisis-observatory.html
4) Google has many tools for ML including Sibyl: Google’s system for Large Scale Machine Learning (https://www.kdnuggets.com/2014/08/sibyl-google-system-large-scale-machine-learning.html) and Tensorflow (https://www.tensorflow.org/).
5) Ufora.com was a good example, but it appears to be out of business. It's business model could be a template for future efforts of a similar nature. http://time.com/money/3890808/hedge-funds-data-analysis-ufora/
did you try to search SSRN or anything else like this? https://arxiv.org/abs/1807.02787