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Volume 12, Issue 3, 2025

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This paper investigates whether Indonesia Composite Index (IHSG) volatility persistence exhibits statistically significant structural breaks over 2019–2024 and how short-, medium-, and long-term components shift across regimes. Using daily closing prices from the Indonesia Stock Exchange (IDX), realized volatility is modeled via HAR specification with daily, weekly, and monthly components. Structural stability is tested using CUSUM, CUSUMSQ, and Bai–Perron procedures, identifying breaks in April 2020 (COVID-19) and February 2024 (election). Pre-COVID, the weekly component dominates, indicating medium-term persistence; post-COVID, the monthly component leads, reflecting long-horizon uncertainty. Pre-election adjusted drops sharply (0.044), signaling transitory political volatility. Findings demonstrate regime-dependent volatility in emerging markets, showing that ignoring structural breaks biases risk assessment and market monitoring strategies for regulators and investors.

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Corruption represents a significant governance and risk management failure that undermines institutional integrity, weakens internal controls, and erodes trust in both public and private organisations. Existing corruption indices measure prevalence; they provide limited insight into the behavioural and institutional risk drivers that enable corrupt conduct. This study examines corruption through a governance and risk management lens to identify the behavioural, sociological, environmental, and demographic triggers that increase corruption risk and expose weaknesses in control and oversight frameworks. A mixed-methods approach is adopted, combining a systematic review of the literature with quantitative and qualitative analysis of primary data collected through a structured questionnaire administered to 454 respondents across diverse demographic groups. Exploratory factor analysis, reliability testing, non-parametric tests, and multiple linear regression were employed to assess the relative importance of corruption triggers and the influence of demographic characteristics. Thematic analysis was used to contextualise and interpret empirical findings. The results indicate that behavioural risk factors, particularly emotional intelligence, moral rationalisation, and social norms, play a central role in enabling corrupt behaviour. Five dominant categories of corruption triggers were identified: positive emotions, environmental conditions, underlying causes, negative emotions, and economic pressures. The findings further reveal that weak governance structures, inadequate internal controls, and tolerance of unethical behaviour amplify corruption risk and contribute to institutional vulnerability. Demographic characteristics also influence perceptions of corruption and risk exposure. Corruption risk cannot be effectively mitigated solely through legal compliance, highlighting the need for organisations to integrate behavioural risk considerations into corporate governance frameworks, enterprise risk management systems, and internal control structures. By reframing corruption as a behavioural and institutional risk phenomenon, this study contributes to the governance and risk management literature. It provides practical insights for boards, regulators, insurers, and risk professionals seeking to strengthen oversight, ethical culture, and risk mitigation strategies.

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This study explores how people’s perceptions of age, gender, education, and religious beliefs, referred to as perceived demographic mortality differentials, are associated with their decision to purchase life insurance in Lagos State, Nigeria. While financial ability is often seen as the primary factor influencing insurance purchase, this research highlights the significant role of individual beliefs about mortality, shaped by personal and cultural identity. Data were collected from 300 residents across three diverse communities in Lagos State using a structured questionnaire, with responses rated on a Likert scale. Regression analysis showed that all four demographic perceptions were significantly associated with life insurance purchase decisions. Religious beliefs exhibited the strongest explanatory strength (β = 0.618, = 0.382), closely followed by education (β = 0.614, = 0.376), while gender (β = 0.557, = 0.310) and age (β = 0.449, = 0.202) also played meaningful roles. These findings suggest that people’s perceptions influence how they assess risk and make financial decisions, including the decision to purchase life insurance. The study concludes that efforts to boost life insurance participation in Nigeria should go beyond pricing or access and instead focus on culturally relevant messaging, financial education, and trust-building strategies that speak to people’s beliefs and lived experiences. These insights are valuable for insurers, policymakers, and development practitioners working to expand financial inclusion in diverse and complex societies.

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