Artificial Intelligence Technologies within the Risk-based Audit Approach – A Categorization and Classification Method

“This study proposes a comprehensive method (with representative AI-Technologies as a data basis) for the structured and targeted categorization and classification of AI under the risk-based audit approach. Initial feedback received by AI-Experts regarding the design and development of the artifact is collected. With the developed method, the study contributes to the descriptive and prescriptive knowledge […]

Using multimodal learning and deep generative models for corporate bankruptcy prediction

“The empirical results in this research show that the classification performance of our proposed methodology is superior compared to that of a large number of traditional classifier models. We also show that our proposed methodology solves the limitation of previous bankruptcy models using textual data, as they can only make predictions for a small proportion […]

HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction

“Despite that some attention or self-attention based models with time-aware or feature-aware enhanced strategies have achieved better performance compared with other temporal modeling methods, such improvement is limited due to a lack of guidance from global view. To address this issue, we propose a novel end-to-end Hierarchical Global View-guided (HGV) sequence representation learning framework. “ Lire

Deep Learning in Business Analytics: A Clash of Expectations and Reality

“… DL [deep learning] does not outperform traditional ML [machine learning] models in the case of structured datasets with fixed-length feature vectors. Deep learning should be regarded as a powerful addition to the existing body of ML models instead of a one size fits all solution.” Lire