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𝗘𝗜𝗢𝗣𝗔 has issued new guidance on supervising 𝗺𝗮𝘀𝘀-𝗹𝗮𝗽𝘀𝗲 𝗿𝗲𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 and 𝗿𝗲𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 𝘁𝗲𝗿𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻 clauses. This guidance, provided in two annexes to its 2021 Opinion on risk-mitigation techniques, aims to standardize supervisory approaches across Europe.
The first annex focuses on 𝗺𝗮𝘀𝘀-𝗹𝗮𝗽𝘀𝗲 𝗿𝗲𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲, offering detailed guidance for supervisors on its prudential treatment. It emphasizes ensuring a common European approach, particularly in light of recent high lapse risks in various markets. The guidance helps supervisors evaluate how elements like the measurement period, exclusions, or termination clauses affect risk transfer effectiveness and the 𝗦𝗼𝗹𝘃𝗲𝗻𝗰𝘆 𝗖𝗮𝗽𝗶𝘁𝗮𝗹 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁 (𝗦𝗖𝗥). A 12-month measurement period is generally expected, aligning with the SCR time horizon.
The second annex addresses 𝘁𝗲𝗿𝗺𝗶𝗻𝗮𝘁𝗶𝗼𝗻 𝗰𝗹𝗮𝘂𝘀𝗲𝘀 𝗶𝗻 𝗿𝗲𝗶𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 agreements that could undermine effective risk transfer. It highlights provisions that release the reinsurer from responsibility for legitimate losses during the treaty period and scrutinizes contracts where reinsurers can unconditionally retain transferred premiums and assets upon termination while being freed from obligations. These annexes promote supervisory convergence and fair competition within the market.

Lack of high-quality public cyber incident data hinders empirical research and predictive modeling for cyber risk. Companies' reluctance to disclose incidents, fearing reputational damage, perpetuates this challenge. Actuarial solutions focus on enhancing existing datasets and employing advanced modeling. A new InsurTech framework is proposed to enrich cyber incident data with entity-specific attributes, addressing the gap in publicly available information. Machine learning models predict incident types and estimate frequencies, demonstrating improved robustness when incorporating InsurTech-derived features. This framework aims to generate transparent, entity-specific cyber risk profiles, supporting tailored underwriting and proactive risk mitigation for insurers and organizations.

For years, "continuous monitoring" in cybersecurity lacked a clear definition, forcing improvised security practices. This paper introduces QUARC, a formal model that quantifies cybersecurity risk and links it to precise detection and response times. QUARC provides a robust, weight-free probabilistic risk function, translating this risk into concrete operational cadences using hazard and queue theories. This model offers a universal standard, allowing regulators to enforce testable compliance, security teams to monitor real-time conformance, and insurers to price risk accurately. QUARC transforms a vague policy into a measurable, enforceable reality, closing a critical loophole exploited by attackers.

A structured IT outsourcing risk management policy is crucial for navigating third-party service complexities. This study proposes a framework integrating IT outsourcing principles with COBIT standards, covering risk identification, analysis, mitigation, and ongoing monitoring. Implementing this policy enhances organizational asset protection, operational continuity, and minimizes outsourcing risks. It improves information security and business process efficiency. This framework provides practical guidance for organizations to effectively manage risks and optimize IT outsourcing value.

#regulators recently issued #cybersecurity #disclosure guidelines to enhance #transparency and #accountability among firms. A study analyzed cybersecurity disclosure practices among a sample of Toronto Stock Exchange firms over seven years. Findings indicate a notable increase in disclosure after 2017 guidance by #canadian Securities Administrators. However, improvements are needed, especially in #governance and #riskmitigation disclosure. This study sheds light on policy's impact on cybersecurity transparency.

The article delves into #ethical concerns with #aitools in #legal and #tax research, addressing #output #quality, #bias, #verifiability, #liability, and #privacy #risks. It explores #regulatory, #tech, and professional solutions, offering practical advice for tax professionals to safely navigate AI's challenges with #riskmitigation.

This study investigates the #riskmitigation and #internalcontrols organizations implement in their Robotic Process Automation (#rpa) deployments in #accounting. RPA #governance models range from being fully centralized to being entirely decentralized. RPA #risk and #control oversight includes unique #riskassessments for the RPA accounting environment.

Corporate #riskmanagement encompasses both financial hedging and #operationalrisk #riskmitigation. This study investigates how #laborlaw #breaches during surprise inspections impact supplier choices in major #us firms.

#bayesian data imputation is a technique used to fill in missing data in a variety of fields, including #riskmanagement. By employing imputation techniques to fill in the gaps, #riskmanagers can obtain a more comprehensive and reliable understanding of the underlying #risk factors, enabling them to make informed decisions and develop effective strategies for #riskmitigation.

"... its ability to provide relevant #riskmitigation strategies was identified as its strongest aspect. However, the research also revealed that #chatgpt's consistency in #riskassessment and prioritization was the least effective aspect. This research serves as a foundation for future studies and developments in the field of #ai-driven #riskmanagement, advancing our theoretical understanding of the application of #aimodels like ChatGPT in #realworld #risk scenarios."