The article discusses the use of #deeplearning and #datamining in business intelligence protocols to optimize data-driven decision-making and improve efficiency. The authors focus on the use of Graph Neural Network and Autoencoders Models to process large amounts of data and model #fraud behaviors. They suggest that deep learning can be used to control #moneylaundering in financial institutions and improve visibility and transparency in businesses.
“... we provide evidence that setting the risk-weighted ratio at 15\% and the simple leverage ratio at 10% would significantly decrease the probability of default without hampering banks' activities.”
The study investigated how ChatGPT and Bard categorize investor risk profiles compared to financial advisors. While there were no significant differences in the risk scores assigned by the chatbots an
The paper suggests that companies developing high-risk AI systems should demonstrate their safety before deployment, arguing for proactive risk management. It proposes a risk management approach where