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"The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of using the tool to solve practical problems of operational financial risk estimation."
"... 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."
"... the methods discussed in this paper can apply to general machine learning classifiers in applications with imbalanced data issues, by using a case study in credit card fraud detection this paper calls practitioners’ attention to the imbalanced data problems therein, where class imbalance is often mistreated and lacks theoretical discussion."
"... we propose an approach to estimate very large losses similar to that used by Fermi and Drake to estimate the existence of extraterrestrial life. It consists of supposing the event of interest is the result of a concatenation of independent factors and estimating the probability of each factor. The problem is that the events in the causal chain might be events that have never been observed, which ties our subject to that of the estimation of probabilities of rare events."
"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. "
"... nothing meaningful for regulation can be determined solely by looking at the data itself. Data is what data does. Personal data is harmful when its use causes harm or creates a risk of harm. It is not harmful if it is not used in a way to cause harm or risk of harm."
"This paper ... documents some of the most prominent cases of misconduct, which it summarizes in terms of operational risk losses (using Turner’s framework for analyzing organizational disasters) and also details some egregious examples of operational risk events ..."
"... 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."