Self‑Governance as a Pillar of Fraud Prevention: A Comprehensive Examination and Practical Recommendations

“ Through an analysis of self-governance practices, including internal controls, ethical conduct, transparency, compliance, board oversight, risk management, auditing, and whistleblower protection, the article elucidates how organizations can effectively combat fraudulent activities.”

Climate Risk, Insurance Retreat, and State Response

"Private businesses are making actuarial decisions, assessing that some locations are just too vulnerable to insure. At the same time, this insurance retreat also poses a policy challenge for states as they react to the mounting insurance gaps left by exiting private insurers."

Estimation of Generalized Tail Distortion Risk Measures with Applications in Reinsurance

New estimators for generalized tail distortion (GTD) risk measures are proposed, based on first-order asymptotic expansions, offering simplicity and comparable or better performance than existing methods. A reinsurance premium principle using GTD risk measure is tested on car insurance claims data, suggesting its effectiveness in embedding safety loading in pricing to counter statistical uncertainty.

The Changing Landscape of Cyber Risk: An Empirical Analysis of Frequency, Severity, and Tail Dynamics

Cyber risk presents significant challenges to society, yet its statistical behavior remains insufficiently understood. This paper analyzes three databases to study cyber risk dynamics. It identifies increasing frequency and severity, particularly in malicious events since 2018. Persistent heavy-tailedness across risk categories implies lower insurance demand and potentially heightened risk levels for firms.

Combining AI and Domain Expertise to Assess Corporate Climate Transition Disclosures

Effective transition to a sustainable economy requires robust emission reduction plans from companies, crucial for capital allocation and risk management. Transition disclosures serve as a market compass towards net-zero goals, mitigating financial risks. Despite various frameworks, inconsistencies persist, prompting a proposed set of 64 indicators for comprehensive assessment using natural language processing.

Dissonance in Climate Disclosure: the SEC, EU, California, and ISSB Regimes

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Major financial centers introduced varied climate disclosure rules, notably Scope 3 mandates. EU and California led with mandates, while the SEC proposed but later removed them in 2024. Challenges include accuracy, standardization, and compliance costs. EU provides institutional support, but the U.S. lacks it, raising reporting stakes.

Strengthening Cybersecurity Resilience: the Importance of Education, Training, and Risk Management

“The financial impact of cybercrime paints a concerning picture. According to the FBI's Internet Crime Complaint Center (IC3), cybercrime complaints in 2023 reached record highs, with reported losses exceeding $10 billion (IC3, 2023). Furthermore, IBM's 2023 Cost of a Data Breach Report estimates the average global cost of a data breach to be a staggering $4.5 million (IBM, 2023). These statistics highlight the immense financial burden cybercrime places on individuals, organizations, and governments.”

An Integrated Bayesian Network and Geographic Information System (Bn‑Gis) Approach for Flood Disaster Risk Assessment.

The study presents an innovative approach for flood disaster risk assessment and ecological monitoring using Bayesian networks (BNs) and geographic information systems (GIS). By integrating diverse data sources, the BN-GIS model provides a holistic risk profile of flood-prone urban ecosystems in Yinchuan, China. This approach allows for mapping vulnerable hotspots, quantifying uncertainties, and informing sustainable urban planning and disaster resilience efforts.

A Bayesian Audit Assurance Model Incorporating Monetary Unit Sampling

The modern auditing process aligns with Bayesian methods, enabling auditors to use tools and techniques for targeted audit procedures and assurance modeling. This approach integrates sampling results and supports intuitive, easy-to-implement models for field use. The model generalizes the audit risk model, applying Bayesian techniques and the Stringer posterior.