Nos derniers articles

Proposes a set of novel modeling mechanisms to regulate the size of banks' macroprudential capital buffers by using market-based estimates of systemic risk combined with a structural framework for credit risk assessment. It applies the model to the European banking sector and finds differences with the capital buffers currently assigned by national regulators, which have substantial implications for systemic risk in the EEA.

This study reveals how operational risk events affect US bank CEO compensation from 1992-2016. Results indicate that compensation committees take operational risk into account & that recent regulations have enhanced this process. Additionally, operational risk events have a detrimental effect on options-based compensation.

"We aim to analyze strategies for assessing and managing new risks that affect the insurance industry, considering the regulatory requirements that the company must follow. To this end, the open-source software Climada was examined. This software uses stochastic forecasting models such as ARCH, GARCH, and ARIMA. Through real data obtained during an internship at E&Y, it was determined that these models can be a useful tool for insurance companies when dealing with extreme risks. This includes their exposure and solvency. Additionally, the study explores issues related to climate change"

"Bayesian estimates from experimental data can be influenced by highly diffuse or "uninformative" priors. This paper discusses how practitioners can use their own expertise to critique and select a prior that (i) incorporates our knowledge as experts in the field, and (ii) achieves favorable sampling properties. I demonstrate these techniques using data from eleven experiments of decision-making under risk, and discuss some implications of the findings."

"... we study the behavior of the asymptotic tail distribution of independent sums of heavy-tailed random vectors under the paradigm of multivariate regular variation. Assessment of such tail probabilities are of interest in risk management for many finance, insurance, queueing, and environmental applications. Multidimensional tail events are often characterized by at least one variable exceeding a high threshold, and the asymptotic probability of such events follow the so-called “one large jump” principle..."

"... new risks—and the intensification of longstanding risks—are pressure-testing the agility and resilience of corporate strategies, risk management systems and practices."

"We propose here an analysis of the database of the cyber complaints filed at the Gendarmerie Nationale.We perform this analysis with a new algorithm developed for non-negative asymmetric heavy-tailed data, which could become a handy tool in applied fields. This method gives a good estimation of the full distribution including the tail. Our study confirms the finiteness of the loss expectation, necessary condition for insurability."

"While stress testing has modernized banks’ internal risk management by spurring the acquisition of highly skilled risk management talent, recent changes to the tests could erode its efficacy."

"Using data on credit scores matched with unique information on firm level commercial insurance purchases, we find that financing constraints lead to higher insurance spending. We adopt a regression discontinuity design and show that financially constrained firms spend 5–14% more on insurance than otherwise similar unconstrained firms. "

"... an overview of how machine learning can help in categorizing textual descriptions of operational loss events into Basel II event types. We apply PYTHON implementations of support vector machine and multinomial naive Bayes algorithms to precategorized Öffentliche Schadenfälle OpRisk (ÖffSchOR) data to demonstrate that operational loss events can be automatically assigned to one of the seven Basel II event types with very few costs and satisfactory accuracy."