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This research explores how enterprise risk management (ERM) can be modernized to combat the rising financial threat of insurance fraud. By integrating artificial intelligence and machine learning into traditional frameworks like Basel II, insurers can shift from reactive investigations to proactive prevention. The author emphasizes the use of data analytics and Principal Component Analysis (PCA) to simplify complex claims data into clear, actionable risk categories. These advanced visualization techniques, such as confidence ellipses and heat maps, allow executives to identify fraudulent patterns and anomalies more efficiently. Ultimately, the paper provides a data-driven roadmap for casualty insurers to strengthen their operational resilience while maintaining regulatory compliance.

There is an increasing AI use in insurance—50% in non-life, 24% in life. To address emerging risks, undertakings must clarify supervisory responsibilities, maintain full accountability, and implement proportionate governance. Risk managers should conduct impact-based assessments, emphasizing data sensitivity, consumer impact, and financial exposure. Strong governance includes fairness, data quality, transparency, cybersecurity, and human oversight. Oversight extends to third-party providers, with contractual safeguards required. AI systems must align with existing frameworks like ERM and POG, ensuring traceability, explainability, and resilience throughout their lifecycle. Supervisory convergence across the sector remains a key regulatory goal.

The banking industry faces complex financial risks, including credit, market, and operational risks, requiring a clear understanding of the aggregate cost of risk. Advanced AI models complicate transparency, increasing the need for explainable AI (XAI). Understanding risk mathematics enhances predictability, financial management, and regulatory compliance in an evolving landscape.

The #covid19 #pandemic challenged every aspect of business and forced organizations to shift into #crisismode. The pandemic re-exposed issues associated with #siloedthinking in #riskmanagement. For organizations with inadequate #erm policies, plans, or procedures, this is a crucial time to reflect on improving their ERM processes through the capture and transfer of Covid-related lessons. This study explores how concept #riskmapping can be a valuable tool to structure lessons learned capture, ensure risk information is considered, and focus on ERM practice improvements.

The study finds that entrepreneurs view #riskmanagement as a mindset focused on asset preservation, competitive advantages, and local talent development. Risk management practices in #smes are mainly informal yet deliberate and fully integrated into the organization's fabric. In-house #accountants help entrepreneurs with #erm, while external accountants do not systematically contribute to risk management. The study contributes to both the theory and practice of risk management by providing empirical insights into SME owners' perceptions, sense-making, and risk management practices.

"... compares two industries where legislative requirements differ, but it finds the same pattern: the ideals of enterprise risk management are being not implemented in practice."

"Despite its relevance, forward-looking information is still a confusing topic, in terms of contents and applications, especially in the context of ESG, where there is a need for greater clarity and standardization of the definitions of the ESG indicators."

"We believe our paper adds to the important body of cybersecurity literature that explores the roles of government and business, particularly corporate directors, in the governance of data security."

"... the appointment of a female risk officer is not sufficient to reduce risk-taking by banks."

"... we find the difference in decision-makers’ probability assessments between operational and non-operational risk factors is greater when assessing a proximate rather than a remote target. We contribute to the accounting literature by demonstrating how spatial distance affects probability judgments."