This report uses UK fire statistics to model insurance claims for a company next year. It estimates the total sum of claims by modeling both the number and size of fires as random variables from statistical distributions. Monte Carlo simulations in R are used to predict the probability distribution of total claim costs.
Financial institutions must enhance cyber defenses and regulatory frameworks must adapt to new risks. International agencies are creating coherent cybersecurity standards, exemplified by the EU's Digital Operational Resilience Act (DORA). Effective defense also requires robust institutional governance and sector-led standards.
“... we argue there are good reasons for skepticism, as many of its key operative provisions delegate critical regulatory tasks to AI providers themselves, without adequate oversight or redress mechanisms. Despite its laudable intentions, the AI Act may deliver far less than it promises.”
“... we analyse the regulatory necessity in introducing a coercive regulatory framework, and second, present the regulatory concept of the AI Act with its fundamental decisions, core provisions and risk typology. Lastly, a critical analysis points to shortcomings, tensions and watered down assessments of the Act.”
"the typical organization loses 5% of revenues yearly because of fraud. Businesses are subject to fraud risk, and it is critical for organizations to put in place effective control mechanisms to prevent fraud".
“... a greater focus on ESG risks is more in line with banks characterized by traditional activities.”
“... the paper analyses (i) how the AI Act should be applied and implemented according to its original intention of a risk-based approach, (ii) how the AI Act should be complemented by sector-specific legislation in the future to avoid inconsistencies and over-regulation, and (iii) what lessons legislators around the world can learn from the AI Act in regulating AI.”
This paper refines wildfire risk assessment methodologies for the European Central Banks, focusing on the Fire Weather Index, land cover types, and climate data. Using logistic regression and xgboost models, it projects a 12% increase in high-risk areas by 2050, emphasizing advanced models' importance for accurate financial risk evaluation.
"We study the general properties of robust convex risk measures as worst-case values under uncertainty on random variables. We establish general concrete results regarding convex conjugates and sub-differentials. We refine some results for closed forms of worstcase law invariant convex risk measures under two concrete cases of uncertainty sets for random variables: based on the first two moments and Wasserstein balls."
This paper introduces Natural Language Processing (NLP) concepts, text mining, and model design principles, detailing text preprocessing and feature extraction. Empirical research shows the model's excellent performance in risk identification and prediction, enhancing financial risk management accuracy and efficiency.