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Detection of Accounting Anomalies using Deep Autoencoder Neural Networks

An interactive lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The the lab content is based on Python, IPython Notebook, and PyTorch.

The recording of our talk is available via NVIDIA's GTC On-Demand under the following external link.

Running the Notebook

Reference

The lab is inspired by our work "Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks" by Marco Schreyer, Timur Sattarov, Damian Borth, Andreas Dengel and Bernd Reimer.

The publication is available via arXiv under the following link: https://arxiv.org/abs/1709.05254

Questions?

Please feel free to get in touch by opening an issue report, submitting a pull request, or sending us an email.

Disclaimer

Opinions expressed in this work are those of the authors, and do not necessarily reflect the view of PricewaterhouseCoopers (PwC) International Ltd. nor its network firms.