Is Bank CEO Pay Sensitive to Operational Risk Event Announcements?

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. Lire

Analysis of New Models of Emerging Risk for Insurance Companies: The Climate Risk

“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, […]

Bayesian Model Selection and Prior Calibration for Structural Models in Economic Experiments: Some Guidance for the Practitioner

“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 […]

Aggregating heavy-tailed random vectors: from finite sums to Lévy processes

“… 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 […]

Risk Management and the Board of Directors

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

Financing Constraints and Risk Management: Evidence From Micro-Level Insurance Data

“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. “ Lire

Machine Learning for Categorization of Operational Risk Events Using Textual Description

“…  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 […]

Strategic Data Access Management

“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 […]

Cyber Risk: Hyperconnectivity and the Political Economy of Uncertainty

“This paper explores the notion of ‘cyber risk’, asking how we might understand it through a sociotechnical lens. It pays specific attention to how we can theorise cyber risk as an assemblage of sociotechnical ‘riskscapes’, in which our understanding of risk goes beyond organisational imperatives of ‘risk management’ and into treating cyber risk as a set of productive knowledges and practices within a […]

HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction

“Despite that some attention or self-attention based models with time-aware or feature-aware enhanced strategies have achieved better performance compared with other temporal modeling methods, such improvement is limited due to a lack of guidance from global view. To address this issue, we propose a novel end-to-end Hierarchical Global View-guided (HGV) sequence representation learning framework. “ Lire

The Government Behind Insurance Governance: Lessons for Ransomware

“This paper analyzes how governments support insurance markets to maintain insurability and limit risks to society. We propose a new conceptual framework grouping government interventions into three dimensions: regulation of risky activity, public investment in risk reduction, and co-insurance.” Lire

Conditional divergence risk measures

“Our paper contributes to the theory of conditional risk measures and conditional certainty equivalents. We adopt a random modular approach which proved to be effective in the study of modular convex analysis and conditional risk measures.” Lire