"By identifying research gaps and conceptualizing a research agenda, this paper continues to serve the academia to broaden the research field of risk disclosure, esp. for banks."
"... the AI Act risks delivering insufficient levels of both product safety or fundamental rights protection."
"... we develop a framework based on a combination of a neural network together with a dimensionality reduction technique t-SNE (t-distributed stochastic neighbour embedding)... The obtained results, which are based on real insurance data, reveal a clear contrast between the high and low risk policy holders, and indeed improve upon the actual risk estimation performed by the insurer."
"... if enacted as foreseen, AI liability in the EU will primarily rest on disclosure of evidence mechanisms and a set of narrowly defined presumptions concerning fault, defectiveness and causality."
"... we have applied text analysis methodologies to extract information from descriptions in the OpRisk database. After delicate tasks like data cleaning, text vectorization, and semantic adjustment, we apply methods of dimensionality reduction and several clustering models and algorithms to develop a comparison of their performances and weaknesses. Our results improve retrospective knowledge of loss events and enable to mitigate future risks."
"An employee may be attacked by a potentially sophisticated adversary whose goal is to steal all their data. Therefore, the firm trades off the efficiency benefit of the more permissive data access architecture with the adversarial risk it incurs. We characterize the firm's optimal data access architecture and investigate how it depends both on the adversarial environment and the firm's technology."
"... our findings provide new evidence regarding U.S. banking organizations' exposure to climate risks with implications for risk management practices and supervisory policy."
"... climate change exacerbates financial instability, but adaptation can build resilience to climate impacts."
"We here propose a novel XAI [eXplainable AI] technique for deep learning methods (DL) which preserves and exploits the natural time ordering of the data. Simple applications to financial data illustrate the potential of the new approach in the context of risk-management and fraud-detection."
" The global climate crisis and the economy’s green transition are giving rise to new types of risks for banks. This paper analyses some of the key international bank regulatory standards, namely disclosure, risk management, governance and regulatory capital. "