80 citations · 111 across the 4 of their papers we have counts for
4 papers
Learning Sampling in Financial Statement Audits using Vector Quantised Autoencoder Neural Networks
Marco Schreyer, Timur Sattarov, Anita Gierbl +2
The audit of financial statements is designed to collect reasonable assurance that an issued statement is free from material misstatement 'true and fair presentation'. Internationa…
Adversarial Learning of Deepfakes in Accounting
Marco Schreyer, Timur Sattarov, Bernd Reimer +1
Nowadays, organizations collect vast quantities of accounting relevant transactions, referred to as 'journal entries', in 'Enterprise Resource Planning' (ERP) systems. The aggregat…
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks
Marco Schreyer, Timur Sattarov, Christian Schulze +2
The detection of fraud in accounting data is a long-standing challenge in financial statement audits. Nowadays, the majority of applied techniques refer to handcrafted rules derive…
Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks
Marco Schreyer, Timur Sattarov, Damian Borth +2
Learning to detect fraud in large-scale accounting data is one of the long-standing challenges in financial statement audits or fraud investigations. Nowadays, the majority of appl…