In a context of imperfect risk protection, households may protect against the impact of a health shock by employing various financial and non-financial coping mechanisms, such as foregoing or reducing needed medical care, labor substitution, consumption reduction, borrowing money, dissaving, and selling assets. However, leveraging certain coping mechanisms may reduce future productivity, potentially trapping households in chronic or persistent poverty. Resources and risk are not necessarily shared equitably within a household; the ability and willingness of (...) the household to leverage coping mechanisms, or the choice of coping mechanism may depend on the social protection policy context, household socioeconomic status, and type of intrahousehold risk sharing. Vietnam has been making policy changes aimed towards achieving Universal Health Coverage for the past several decades, culminating in a 2015 change mandating universal insurance coverage. This can potentially influence both providers in making decisions around service delivery and households around financing care. This research aims to contribute to the literature exploring the relationships among direct and indirect health care costs, potentially maladaptive coping mechanisms, and household living standards, within the particular health financing and social protection environment in Vietnam. (shrink)

As part of their digital transformation, financial service companies can greatly benefit from the implementation of a microservice architecture. We can build a service-oriented architecture (SOA) application using the architecture to enhance its overall performance and maintainability. This enables the application to consist of several smaller components that operate independently and simultaneously. In the financial services industry, the accuracy of artifact states holds immense significance. Given that an inaccurate artifact state or anomalous artifact operation(s) could potentially ruin the (...) entire application, it is crucial to conduct an analysis of the artifact operations within each microservice during the design process. In this study, we present a technique for identifying anomalies through the characteristics of artifacts associated with the microservice architecture. Following this, we identify the properties of artifacts. As a result of technological improvements and shifting client expectations, the financial sector is currently going through a tremendous upheaval. Among these advancements, microservices architecture has emerged as a key enabler of agility, scalability, and innovation in banking systems. This paper delves into the relationship between microservices and banking security, emphasizing the use of microservices to strengthen financial systems in the face of growing cyber security risks. The microservices architecture simplifies the development, deployment, and scalability of big financial applications by separating them into smaller, self-contained services. This modular approach not only makes the system more reliable and helps separate problems, but it also makes continuous integration and delivery (CI/CD) easier, which lets you respond quickly to changes in the market and new rules. However, the implementation of microservices introduces new security challenges, such as controlling inter-service communication, ensuring data integrity, and safeguarding against attack detection and protection. (shrink)

Common mental health disorders are rising globally, creating a strain on public healthcare systems. This has led to a renewed interest in the role that digital technologies may have for improving mental health outcomes. One result of this interest is the development and use of artificial intelligence for assessing, diagnosing, and treating mental health issues, which we refer to as ‘digital psychiatry’. This article focuses on the increasing use of digital psychiatry outside of clinical settings, in the following sectors: education, (...) employment, financial services, social media, and the digital well-being industry. We analyse the ethical risks of deploying digital psychiatry in these sectors, emphasising key problems and opportunities for public health, and offer recommendations for protecting and promoting public health and well-being in information societies. (shrink)

Variations in people’s perceptions of investment risk and financial literacy have been linked in studies. More specifically, Diacon (2016) discovered significant differences between less financially savvy non-experts and financial professionals. Lay people therefore have a larger propensity for association bias (i.e., they give suppliers and salesmen a higher level of credibility than laypeople) and are often less risk-tolerant than financial professionals. The method of sampling that the researcher chose is known as purposeful sampling. According to (...) Easton & McColl, it is a fundamental sampling strategy where the researcher chooses a smaller group of people (a sample) from a larger group (a population) to study. The responders of the survey included both commissioned and non-commissioned PNP members. There were 67 non-commissioned individuals and 33 commissioned personnel. These individuals are at work while this study is being done. Because they think mutual funds can invest in a variety of assets in the future, think savings account interest is higher than that on fixed deposit accounts, and even budget their monthly income for expenses, savings, and investments, survey participants can be inferred to rate their level of financial knowledge as extremely high. Additionally, people learn about investments from their peers and think that growing costs will limit purchasing power. They also get banking advice from dependable friends. Because they want to make sure that they are not concerned about loans as long as their savings are protected and they refrain from purchasing non-essentials, police responders are persuaded that they have a very high attitude toward their finances. They also believe that investing in a business is a better use of their money than spending it now, that saving money over time is more satisfying than spending it now, and that their financial status is a big problem or a source of stress. The poll participants believe that their level of financial conduct is pretty high since the separate their needs and wants, have begun saving for their retirement, and consistently save money each pay period. They also budget their money, regulate their spending, and always pay their bills on time. (shrink)

After the 2008 crisis, there were several debates on the bail-out and the lack of accountability of financial institutions; this supposedly affects politica l values such as equality and responsibility: it implies transferring resources from the public (for instance, poor people) to specific economic agents who have chosen to incur certain risks. On the other hand, it is arguable that it would not be up to the regulators to protect investors’ interests, and that there would be more efficient and (...) less burdensome instruments associated with prudential regulation. Our goal is to provide a justification for the bail-out and for holding bankers accountable. In section 2, we present a brief description of the problem in the context of the crisis, followed by a justification for the bail-out through the incentives argument, based on Rawls’s difference principle. In section 3, we provide an ethical discussion over the corresponding moral hazards, and investigate how to mitigate it through coercive measures. (shrink)

The goal of achieving Universal Health Coverage (UHC) can generally be realized only in stages. Moreover, resource, capacity and political constraints mean governments often face difficult trade-offs on the path to UHC. In a 2014 report, Making fair choices on the path to UHC, the WHO Consultative Group on Equity and Universal Health Coverage articulated principles for making such trade-offs in an equitable manner. We present three case studies which illustrate how these principles can guide practical decision-making. These case studies (...) show how progressive realization of the right to health can be effectively guided by priority-setting principles, including generating the greatest total health gain, priority for the worse off, and financial risk protection. They also demonstrate the value of a fair and accountable process of priority setting. (shrink)

This chapter explores two questions in detail: How should we determine the threshold for costs that individuals are asked to bear through insurance premiums or care-related out-of-pocket costs, including user fees and copayments? and What is an adequate relationship between costs and benefits? This chapter argues that preventing impoverishment is a morally more urgent priority than protecting households against income fluctuations, and that many health insurance plans may not adequately protect individuals from health care costs that threaten to drop their (...) financial status below a decent minimum. A design that places greater emphasis on preventing impoverishment and finances the achievement of that goal by reducing unnecessary subsidies to better-off households would better accord with a sufficientarian approach to health care. -/- . (shrink)

The main aim of this project is to detect fraudulent credit card transactions by utilizing credit card details. As financial transactions grow in volume and complexity, it becomes increasingly critical for credit card companies to identify fraudulent activities to protect customers from unauthorized charges. Although instances of fraud are relatively infrequent, they present substantial financial risks to both consumers and financial institutions. This research employs three machine learning techniques—One-Class SVM, Local Outlier Factor, and Isolation Forest—to analyse transaction (...) data in real-time, addressing the challenges posed by imbalanced datasets and the sophistication of fraud schemes. By implementing a comprehensive detection system using these models on a credit card transaction dataset, the study aims to enhance the accuracy of fraud detection and provide timely alerts to prevent financial losses. Key results indicate that the proposed methodology significantly improves the identification of fraudulent transactions, ultimately leading to more secure credit card usage for consumers. The conclusions drawn from this research emphasize the necessity for ongoing innovation in fraud detection methodologies to keep pace with the ever- changing landscape of financial fraud. (shrink)

This paper provides a comprehensive review of the Vasicek model and its applications in finance, categorizing the literature into four key areas: Vasicek model applications, Monte Carlo simulations, negative interest rates and risk, and deep learning for financial time series. To provide deeper insights, a synthesis chart and chronological analysis are included to highlight significant trends and contributions. Building upon this foundation, we employ Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to generate synthetic future interest rate data. (...) These generated projections are then integrated as inputs into the Vasicek model, dynamically adjusting its parameters with the support of AI-driven synthetic data. Additionally, we propose the use of publicly available financial information, gathered via public-facing large language models (LLMs) like ChatGPT, to assess whether the models project trends in line with real-world data. Specifically, we will query ChatGPT to analyze 50 key questions related to interest rates, risk management strategies, inflation, and economic indicators from institutions like the Federal Reserve and banks. Our approach also leverages publicly available information to refine model outputs, reducing reliance on assumptions and emphasizing the alignment of AI-generated noise with observable market behaviors. By integrating these real-world insights, we aim to ensure that our models remain both innovative and grounded in current economic realities. Ultimately, this framework combines advanced generative AI models, such as GANs and VAEs, with human oversight and economic data, providing a robust, adaptable, and forward-thinking approach to financial risk modeling. Keywords: GANs, VAEs, Vasicek, GenAI, Financial Risk Modeling. (shrink)

Since the global financial crisis in 2008, corporations have faced a crisis of trust, with growing sentiment against ‘elites and ‘big business’ and a feeling that ‘something ought to be done’ to re-establish public regard for corporations. Trust and trustworthiness are deeply moral significant. They provide the ‘glue or lubricant’ that begets reciprocity, decreases risk, secures dignity and respect, and safeguards against the subordination of the powerless to the powerful. However, in deciding how to restore trust, it is (...) difficult to determine precisely what should be done, by whom, and who will bear the cost, especially if any action involves a risk to overall market efficiency and corporate profitability. The paper explores whether corporations have a moral duty to be trustworthy, to bear the cost of being so and thus contribute to resolving the current crisis of trust. It also considers where the state and other social actors have strong reason to protect and enforce such moral rights, while acknowledging that other actors have similar obligations to be trustworthy. It outlines five ‘salient factors’ that trigger specific rights to trustworthiness and a concomitant duty on corporations to be trustworthy: market power, subordination (threat and intimidation), the absence of choice, the need to preserve systemic trust, and corporate political power which might undermine a state’s legitimacy. Absent these factors and corporations do not have a general duty to be trustworthy, since a responsible actor in fair market conditions should be able to choose between the costs and benefits of dealing with generally trustworthy corporations. (shrink)

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, (...) reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies. (shrink)

This paper aims to study the impact of Crowdfunding financial attributes on entrepreneurship risk taking. This study was applied on Arabic Crowdfunding platforms from all crowdfunding models. The population of the study consists of individuals, entrepreneurs, investors, employees at electronic-crowd funding Arabic platforms. According to last statics at (2018), there are (12) legit Arabic platforms working in this field. Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation using Cronbach’s alpha, “ANOVA”, Simple Linear (...) Regression. The overall findings of the current paper show that there is a significant statistical impact for financial properties on entrepreneurship and this effect around (25%). Furthermore, the current paper is unique by topic and population as it is the first study on Arabic crowdfunding platforms. (shrink)

Currently, under the conditions of permanent financial risks that hamper the sustainable economic growth in the financial sector, the development of evaluation and risk management methods both regulated by Basel II and III and others seem to be of special importance. The reputation risk is one of significant risks affecting reliability and credibility of commercial banks. The importance of reputation risk management and the quality of their assessment remain relevant as the probability of decrease in (...) or loss of business reputation influences the financial results and the degree of customers’, partners’ and stakeholders’ confidence. By means of imitating modeling based on Bayesian Networks and the fuzzy data analysis, the article characterizes the mechanism of reputation risk assessment and possible losses evaluation in banks by plotting normal and lognormal distribution functions. Monte-Carlo simulation is used to calculate the probability of losses caused by reputation risks. The degree of standardized histogram similarity is determined on the basis of the fuzzy data analysis applying Hamming distance method. The tree-like hierarchy based on the OWA-operator is used to aggregate the data with Fishburne's coefficients as the convolution scales. The mechanism takes into account the impact of criteria, such as return on equity, goodwill value, the risk assets ratio, the share of the productive assets in net assets, the efficiency ratio of interest bearing liabilities, the risk ratio of credit operations, the funding ratio and reliability index on the business reputation of the bank. The suggested methods and recommendations might be applied to develop the decision-making mechanism targeted at the implementation of reputation risk management system in commercial banks as well as to optimize risk management technologies. (shrink)

This paper examines how predictive analytics enhances risk management in financial institutions. Advanced tools like machine learning and statistical modeling help predict risks, identify trends, and implement strategies to prevent losses by analyzing historical and real-time data. It covers the use of predictive analytics for credit risk, market risk, operational risk, and fraud detection, with practical case studies. Additionally, it discusses challenges, ethical issues, and prospects in this field.

Most people are completely oblivious to the danger that their medical data undergoes as soon as it goes out into the burgeoning world of big data. Medical data is financially valuable, and your sensitive data may be shared or sold by doctors, hospitals, clinical laboratories, and pharmacies—without your knowledge or consent. Medical data can also be found in your browsing history, the smartphone applications you use, data from wearables, your shopping list, and more. At best, data about your health might (...) end up in the hands of researchers on whose good will we depend to avoid abuses of power.2 Most likely, it will end up with data brokers who might sell it to a future employer, or an insurance company, or the government. At worst, your medical data may end up in the hands of criminals eager to commit extortion or identity theft. In addition to data harms related to exposure and discrimination, the collection of sensitive data by powerful corporations risks the creation of data monopolies that can dominate and condition access to health care. -/- This chapter aims to explore the challenge that big data brings to medical privacy. Section I offers a brief overview of the role of privacy in medical settings. I define privacy as having one’s personal information and one’s personal sensorial space (what I call autotopos) unaccessed. Section II discusses how the challenge of big data differs from other risks to medical privacy. Section III is about what can be done to minimise those risks. I argue that the most effective way of protecting people from suffering unfair medical consequences is by having a public universal healthcare system in which coverage is not influenced by personal data (e.g., genetic predisposition, exercise habits, eating habits, etc.). (shrink)

This research paper delves into the realm of Financial Network Analytics, unraveling the opportunities and challenges it presents in the domains of systemic risk management and investment analysis. The study navigates the intricate web of interconnected financial entities, employing advanced analytics techniques to uncover meaningful insights. Through a comprehensive exploration, the paper identifies opportunities for leveraging financial network data to enhance systemic risk detection mechanisms and refine investment strategies. Simultaneously, it addresses the inherent challenges, such (...) as data complexity and dynamic network structures, offering nuanced perspectives on their implications. The findings contribute to the evolving landscape of financial analytics, providing a foundation for the development of robust tools and methodologies that can aid financial institutions and investors in navigating the complexities of modern financial networks. (shrink)

The Unified Theory of Free Will: The Three Universal Laws, Systemic Imbalance, and Nature’s Self-Correction -/- By Angelito Malicse -/- Introduction -/- For centuries, the concept of free will has been debated, with perspectives ranging from determinism to compatibilism and libertarianism. However, these traditional views fail to acknowledge the natural laws that govern human decision-making. By synthesizing the Universal Law of Balance in Nature, the Universal Feedback Loop Mechanism, and the Error-Free System, we establish a unified theory of free will—a (...) structured approach to human choices within the constraints of natural order. -/- Additionally, it is crucial to recognize the tolerance limits of hierarchical systems—both natural and man-made. When human decisions exceed these limits and imbalances persist, nature will automatically step in to restore equilibrium. This natural correction often manifests in disruptive ways, such as natural disasters, economic collapses, or social upheavals. Understanding these dynamics is essential to ensuring stability across all systems. -/- Furthermore, human emotions, which have evolved as essential survival mechanisms, play a dual role in maintaining or disrupting balance. Emotions influence decision-making, motivation, and social interactions. When properly regulated, they help individuals and societies adapt to challenges and maintain systemic harmony. However, when emotions exceed their tolerance limits—such as excessive fear leading to panic or unchecked anger causing conflict—they contribute to systemic imbalance and dysfunction. -/- The Three Universal Laws and Their Role in Decision-Making -/- 1. Universal Law of Balance in Nature -/- Every system—biological, social, and technological—operates within specific tolerance limits. Decisions that align with natural balance maintain stability, while those that exceed these limits lead to disruption. If humans fail to correct imbalances, nature will forcefully restore equilibrium, often through unpredictable and catastrophic means. -/- Examples of Balance, Systemic Imbalance, and Natural Correction: -/- Personal Health: A balanced diet sustains physical well-being, while excessive consumption leads to obesity and related diseases. If ignored, the body self-corrects through metabolic disorders and immune system responses. -/- Economic Stability: A balanced economy fosters growth, while financial mismanagement leads to economic crashes. Recessions and inflation serve as corrective mechanisms for financial excesses. -/- Environmental Sustainability: Responsible resource management ensures long-term survival, whereas overexploitation leads to climate change and natural disasters such as droughts and hurricanes, which force societies to adapt. -/- Ecosystem Regulation: Overfishing disrupts marine populations, but nature counters with species migration and ecological shifts that eventually restore stability. -/- Energy Consumption: Overuse of fossil fuels accelerates climate change, prompting extreme weather events and necessitating the shift to renewable energy sources. -/- 2. Universal Feedback Loop Mechanism -/- Decision-making must incorporate continuous feedback to ensure adaptation and refinement. Ignoring or distorting feedback results in inefficiencies and systemic collapse. -/- Examples of Feedback, Systemic Imbalance, and Nature’s Response: -/- Business Adaptation: Companies that respond to consumer feedback thrive, while those that ignore it collapse due to declining market relevance. -/- Political Governance: Leaders who suppress public concerns foster unrest, often leading to revolutions or government overhauls. -/- Technological Development: AI systems trained on biased or incomplete data develop flawed decision-making patterns, necessitating retraining and regulation. -/- 3. Error-Free System -/- Every decision has consequences, and ensuring 100 percent correct information is essential to maintaining systemic balance. Errors in data, assumptions, or implementation can trigger unintended disruptions. -/- Examples of Cause and Effect, Misinformation, and Systemic Collapse: -/- Academic Success: Proper study methods enhance learning, while reliance on ineffective strategies results in poor educational outcomes. -/- Industrialization and Environmental Impact: Sustainable practices protect ecosystems, while reliance on false environmental data accelerates degradation. -/- Global Resource Consumption: Inaccurate assessments of resource availability lead to economic and geopolitical instability. -/- The Evolution and Purpose of the Duality of Human Emotions -/- Human emotions have evolved as critical mechanisms for survival, adaptation, and social cohesion. They function as regulatory signals that guide decision-making, helping individuals and societies maintain equilibrium. However, emotions also possess a dual nature, where their misalignment or overexpression can lead to instability and dysfunction. -/- Positive Role of Emotions in Systemic Balance: -/- Empathy and Cooperation: Emotions such as compassion and trust foster social cohesion, strengthening communities and enhancing cooperation. -/- Fear and Caution: A moderate level of fear helps individuals assess risks and avoid dangerous situations, ensuring personal and collective safety. -/- Motivation and Ambition: Positive emotions such as enthusiasm and joy drive personal growth, innovation, and societal progress. -/- Negative Role of Emotions in Systemic Imbalance: -/- Excessive Fear and Panic: When fear surpasses a system’s tolerance limit, it leads to irrational decision-making, paranoia, and social instability. -/- Unchecked Anger and Conflict: Intense anger without regulation contributes to violence, political unrest, and societal fragmentation. -/- Despair and Apathy: Chronic negative emotions, such as depression and hopelessness, reduce individual productivity and can weaken societal resilience. -/- Examples of Emotional Duality in Decision-Making: -/- Public Health Responses: Balanced fear leads to precautionary health measures, while excessive panic results in chaos (e.g., misinformation-fueled reactions during pandemics). -/- Leadership and Governance: A compassionate leader fosters unity, while an authoritarian leader driven by anger and paranoia destabilizes societies. -/- Market Behavior: Optimistic investors drive economic growth, while fear-driven panic selling causes financial crashes. -/- Effects of Systemic Imbalances and Nature’s Automatic Correction -/- When human decisions disrupt equilibrium and corrective actions are not taken, nature enforces balance through forceful interventions. -/- Examples of Human-Induced Imbalances and Nature’s Response: -/- Healthcare Systems: Overuse of antibiotics results in drug-resistant bacteria, increasing disease severity and forcing new medical advancements. -/- Economic Systems: Financial bubbles burst, leading to recessions that correct speculative excesses. -/- Political Systems: Corrupt governance leads to revolutions, shifts in power, and societal restructuring. -/- Environmental Systems: Deforestation causes soil erosion and desertification, forcing human migrations and altering agriculture. -/- Overpopulation: Excessive growth strains resources, leading to food shortages, pandemics, and natural events that regulate population levels. -/- Urban Expansion: Overcrowding leads to declining infrastructure, pollution, and social conflicts, often prompting mass relocations and policy reforms. -/- Conclusion -/- Free will is not an arbitrary concept but a structured system governed by natural laws. By understanding the Universal Law of Balance in Nature, the Universal Feedback Loop Mechanism, and the Error-Free System, we can align human decisions with nature’s equilibrium. -/- Additionally, recognizing the evolution and duality of human emotions is essential for maintaining stability in personal and societal decision-making. If humanity fails to correct imbalances, nature will automatically restore equilibrium, often in ways that are catastrophic and beyond human control. -/- By integrating these principles into education, governance, and AI development, we pave the way for a rational, ethical, and self-correcting society. -/- . (shrink)

The Advantages of Self-Sufficient Countries with Manageable Populations and Minimal Import Dependence -/- Introduction -/- In a world where globalization has connected economies, many nations remain highly dependent on imports for essentials such as food, energy, and industrial materials. While trade brings benefits, over-reliance on imports exposes nations to risks such as supply chain disruptions, inflation, and geopolitical pressures. However, some countries have successfully built self-sufficient economies, allowing them to thrive with minimal reliance on foreign resources. -/- Self-sufficient countries benefit (...) from economic stability, enhanced national security, environmental sustainability, and a higher quality of life. Examples such as Norway, Switzerland, New Zealand, Iceland, Bhutan, and Uruguay demonstrate that strategic resource management, energy independence, and population control contribute to long-term success. -/- This essay will explore the key advantages of self-sufficiency, examine the strategies employed by these nations, and highlight the broader implications of reducing import dependence. -/- 1. Economic Stability and Resilience -/- One of the primary benefits of self-sufficiency is economic stability. Nations that produce essential goods locally are less vulnerable to global economic downturns, inflation, and trade disruptions. -/- Trade Surplus and Financial Security -/- Countries like Norway and Switzerland have built strong economies by focusing on industries that generate trade surpluses. -/- Norway: A leading exporter of oil, gas, and seafood, Norway earns more from exports than it spends on imports, ensuring a strong national economy. -/- Switzerland: With a diverse economy—banking, pharmaceuticals, and precision manufacturing—Switzerland remains stable despite global financial fluctuations. -/- Local Industry Growth and Job Creation -/- By minimizing imports, self-sufficient nations stimulate local industries, creating jobs and ensuring wealth stays within national borders. -/- New Zealand: Its agricultural sector produces dairy, meat, and fruit for both local consumption and global export, strengthening the workforce and financial stability. -/- Uruguay: The country invests in local renewable energy industries, reducing dependence on imported fossil fuels while creating green jobs. -/- Protection from Global Economic Shocks -/- When economies rely heavily on imports, external crises like wars, pandemics, or financial recessions can cause severe economic disruptions. Self-sufficient nations are more resilient: -/- Switzerland’s banking sector thrives regardless of external turmoil due to its strong internal financial policies. -/- Iceland’s geothermal energy independence protects it from global oil price fluctuations. -/- 2. National Security and Political Independence -/- A country that depends heavily on imports is vulnerable to trade restrictions, geopolitical tensions, and supply chain disruptions. Self-sufficient nations reduce foreign dependencies, strengthening national security and political stability. -/- Energy and Resource Security -/- Self-sufficient countries avoid dependence on foreign energy sources, making them less vulnerable to political blackmail or economic manipulation. -/- Iceland generates 100% of its electricity from geothermal and hydro energy, eliminating its reliance on oil imports. -/- Uruguay produces 98% of its energy from renewable sources, reducing its need for foreign energy supplies. -/- Reduced Geopolitical Vulnerability -/- Countries that rely heavily on imports can be pressured by foreign powers through trade restrictions or embargoes. -/- Switzerland’s economic neutrality allows it to trade freely while maintaining independence from global conflicts. -/- Bhutan discourages foreign consumerism to maintain sovereignty and control over its economy. -/- 3. Environmental Sustainability and Climate Resilience -/- Reducing import dependence directly benefits the environment. Long-distance shipping, mass production, and over-reliance on fossil fuels all contribute to global pollution. Self-sufficient countries focus on local production and sustainability, lowering their environmental impact. -/- Renewable Energy Leadership -/- Norway: Nearly 100% of Norway’s electricity comes from hydropower, making it a leader in green energy. -/- Iceland: Geothermal and hydroelectric plants generate all of Iceland’s electricity, eliminating fossil fuel imports. -/- Bhutan: The country exports excess hydropower to India, reducing the need for fossil fuels regionally. -/- Sustainable Agriculture and Land Management -/- Food self-sufficiency is essential for sustainability. Countries that prioritize local food production ensure long-term food security and reduce carbon emissions from imported food transportation. -/- New Zealand’s farming industry provides dairy, beef, and fruits for domestic consumption and export. -/- Bhutan promotes organic farming, making it one of the most sustainable agricultural economies in the world. -/- 4. Social Stability and Quality of Life -/- Countries with well-managed populations and self-sufficient economies enjoy higher living standards, better infrastructure, and lower poverty rates. -/- Population Management and Resource Allocation -/- Self-sufficient nations carefully regulate population growth to match available resources, ensuring sustainable development. -/- Iceland and Bhutan have small, manageable populations, allowing them to provide high-quality healthcare, education, and infrastructure. -/- Switzerland’s strict immigration policies ensure that economic growth does not outpace resource availability. -/- Resilient Social Systems -/- Strong social welfare programs are more effective in self-sufficient countries because resources are distributed efficiently. -/- Norway: High-quality education, healthcare, and pension systems ensure a high standard of living. -/- Switzerland: The government reinvests economic surplus into public services, benefiting all citizens. -/- 5. Crisis Preparedness and Resilience -/- Global crises such as pandemics, wars, and economic recessions highlight the dangers of import dependence. Self-sufficient nations can respond effectively to crises without relying on external aid. -/- Pandemic and Food Security -/- During the COVID-19 pandemic, supply chain disruptions left many countries struggling to import essential goods. However, self-sufficient nations remained stable. -/- New Zealand’s strong food production ensured that its citizens had uninterrupted access to food supplies. -/- Switzerland’s well-stocked food reserves allowed it to manage shortages without external dependence. -/- War and Trade Embargo Resilience -/- Countries that produce their own essential goods are less affected by global conflicts. -/- Iceland’s fishing industry and energy independence keep its economy stable regardless of international instability. -/- Norway’s oil reserves and food security ensure long-term resilience against economic disruptions. -/- 6. Minimal Import Dependence: The Path to Sustainable Growth -/- While some level of trade is beneficial, excessive import dependence weakens a nation’s economic and political stability. The countries examined here have taken strategic steps to limit imports while maximizing domestic production. -/- Lessons from Self-Sufficient Nations -/- 1. Invest in Renewable Energy – Iceland, Norway, and Uruguay have shown that countries can function without fossil fuel imports through hydropower, geothermal, and wind energy. -/- 2. Prioritize Food Security – Switzerland, New Zealand, and Bhutan ensure food independence through agriculture and local food production. -/- 3. Control Population Growth – Iceland and Bhutan demonstrate that sustainable population sizes lead to better economic planning and quality of life. -/- 4. Develop Strong Local Industries – Norway and Switzerland focus on high-value goods that allow them to export more than they import. -/- 5. Encourage Sustainable Practices – Bhutan and New Zealand promote environmentally friendly farming and renewable energy, ensuring long-term stability. -/- Conclusion -/- Self-sufficient countries with manageable populations and minimal reliance on imports enjoy numerous advantages, including economic stability, national security, environmental sustainability, and a high quality of life. Nations such as Norway, Switzerland, New Zealand, Iceland, Bhutan, and Uruguay demonstrate that renewable energy, food production, and population control lead to long-term prosperity. -/- As the world faces increasing economic and environmental uncertainties, adopting self-sufficiency principles can help nations become more resilient, independent, and sustainable. While globalization has its benefits, balancing local production with strategic trade is the key to securing a stable and prosperous future. -/- . (shrink)

This article presents a new model for valuing financial contracts subject to credit risk and collateralization. Examples include the valuation of a credit default swap (CDS) contract that is affected by the trilateral credit risk of the buyer, seller and reference entity. We show that default dependency has a significant impact on asset pricing. In fact, correlated default risk is one of the most pervasive threats in financial markets. We also show that a fully collateralized (...) CDS is not equivalent to a risk-free one. In other words, full collateralization cannot eliminate counterparty risk completely in the CDS market. (shrink)

An increasing number of financial services (FS) companies are adopting solutions driven by artificial intelligence (AI) to gain operational efficiencies, derive strategic insights, and improve customer engagement. However, the rate of adoption has been low, in part due to the apprehension around its complexity and self-learning capability, which makes auditability a challenge in a highly regulated industry. There is limited literature on how FS companies can implement the governance and controls specific to AI-driven solutions. AI auditing cannot be performed (...) in a vacuum; the risks are not confined to the algorithm itself, but rather permeates the entire organization. Using the risk of unfairness as an example, this paper will introduce the overarching governance strategy and control framework to address the practical challenges in mitigating risks AI introduces. With regulatory implications and industry use cases, this framework will enable leaders to innovate with confidence. (shrink)

This article presents a generic model for pricing financial derivatives subject to counterparty credit risk. Both unilateral and bilateral types of credit risks are considered. Our study shows that credit risk should be modeled as American style options in most cases, which require a backward induction valuation. To correct a common mistake in the literature, we emphasize that the market value of a defaultable derivative is actually a risky value rather than a risk-free value. Credit value (...) adjustment (CVA) is also elaborated. A practical framework is developed for pricing defaultable derivatives and calculating their CVAs at a portfolio level. (shrink)

Risk assessment is one of the prerequisites for understanding its causes and possible consequences. We base our risk assessment on the principles described in the European standard EN 31000 - Risk Management Process. This standard comprehensively describes the continuous activities that are necessary in managing risks and minimizing their possible adverse effects on the operation of the system under investigation. In this activity, it is necessary to first identify the existing risks, then analyze and evaluate the identified (...) risks. In the analysis of existing risks, it is possible to use both qualitative and quantitative analytical methods, or combine them. We use qualitative methods in cases where we do not have a sufficient amount of input information, these are more subjective. Quantitative methods are more accurate, but also more demanding on input information and time. The choice of a suitable analytical method is a basic prerequisite for knowledge of risks and their evaluation. The values of individual risks obtained in this way are the basis for determining the measures that are ecessary to minimize them, i.e., to adjust them to an acceptable level. The draft measures are always based on the value of the individual components used to calculate the risk number, as well as on the value of the asset , which needs to be protected. Appropriately chosen analytical methods are one of the basic prerequisites for the consistent application of the principles of risk management, as a continuous process aimed at increasing the overall security of the system under study. In the article, the author describes the procedures used in risk assessment, as well as specific analytical methods that can be used in working with risks. The aim of identifying risk factors is to create a list of events that could cause undesirable disruption to ongoing processes. At this stage, we define all the risks that will be subsequently analyzed and evaluated. When identifying, we can use methods such as, e.g. SWOT, PHA (Preliminary Hazard Analysis) or CA (Checklist Analysis). Methods suitable for determining the causes and creating scenarios for the course of a risk event are ETA (Event Tree Analysis) or FTA (Fault Tree Analysis). The basic analysis of the system can be performed using the FMEA method (Failure Mode and Effect Analysis), which provides a numerical risk assessment. By comparison with the numerical value of the risk that we are willing to accept, we obtain 2 groups of risks. Acceptable, which will be given regular attention and unacceptable, which we will focus on in risk management and we will try to minimize its negative affect on the functioning of the system under study. (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep (...) Learning. The dataset was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

Identity-protective reasoning---motivated reasoning driven by defending a social identity---is often dismissed as a paradigm of epistemic vice and a key driver of democratic dysfunction. Against this view, I argue that identity-protective reasoning can play a positive epistemic role, both individually and collectively. Collectively, it facilitates an effective division of cognitive labor by enabling groups to test divergent beliefs, serving as an epistemic insurance policy against the possibility that the total evidence is misleading. Individually, it can correct for the distortions that (...) arise from taking ideologically skewed evidence at face value. This is particularly significant for members of marginalized groups, who frequently encounter evidence that diminishes the value of their identities, beliefs, and practices. For them, identity-protective reasoning can counter dominant ideological ignorance and foster resistant standpoint development. While identity-protective reasoning is not without risks, its application from marginalized and counter-hegemonic positions carries epistemic benefits crucial in democracies threatened by elite capture. Against dominant views in contemporary political epistemology and psychology, identity-protective reasoning should be reconceived as a resource to be harnessed and not a problem to be eradicated. (shrink)

An extended analysis compared to observations shows that modern “globalised” world civilisation has passed through the invisible “complexity threshold”, after which usual “spontaneous”, empirically driven kind of development (“invisible hand” etc.) cannot continue any more without major destructive tendencies. A much deeper, non-simplified understanding of real interaction complexity is necessary in order to cope with such globalised world development problems. Here we introduce the universal definition, fundamental origin, and dynamic equations for a major related quantity of (systemic) risk characterising (...) real complex system development tendencies at any level of dynamics. Practically important conclusions are derived, opening further detailed applications in economy, finance and development practice. (shrink)

In addition to protecting agents’ autonomy, consent plays a crucial social role: it enables agents to secure partners in valuable interactions that would be prohibitively morally risk otherwise. To do this, consent must be observable: agents must be able to track the facts about whether they have received a consent-based permission. I argue that this morally justifies a consent-practice on which communicating that one consents is sufficient for consent, but also generates robust constraints on what sorts of behaviors can (...) be taken as consent- communicating. (shrink)

The study aimed to determine the personal financial management practices among selected personnel of the Bureau of the Treasury – Central Office. It used the descriptive method of gathering data. The respondents of the study consisted of 183 personnel from 35 divisions of the Bureau and selected through simple random probability sampling technique. The study shown that most of the respondents aged 26 to 35 years old, female, single, bachelor’s degree holder, rank and file workers, permanent employees, have been (...) in the agency for 5 years and below and with monthly compensation ranging from P15,001 – P30,000. In terms of financial planning, most of the respondents set their short and long-term financial goals. In terms of money management, most of the respondents saved so that they do not need to borrow from others. In terms of income and asset protection, most of the respondents considered uncertainties for their future. And in terms of investments, most of the respondents purchased government securities. The researcher recommended to utilize various social media platforms as an avenue for financial planning, start considering the use of credit management in the acquisition of their needs, understand the need of acquiring non-life insurance and start familiarizing themselves in the concept of the derivatives market. Also, the Bureau of the Treasury should initiate seminars/webinars about how to start writing a financial plan, effective ways in managing finances, the vital role of insurance and estate planning, and possible ways in earning money when investing on securities and derivatives. (shrink)

Violence risk assessment tools are increasingly used within criminal justice and forensic psychiatry, however there is little relevant, reliable and unbiased data regarding their predictive accuracy. We argue that such data are needed to (i) prevent excessive reliance on risk assessment scores, (ii) allow matching of different risk assessment tools to different contexts of application, (iii) protect against problematic forms of discrimination and stigmatisation, and (iv) ensure that contentious demographic variables are not prematurely removed from risk (...) assessment tools. (shrink)

Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained and validated, (...) achieving an impressive accuracy of 100% and an average error of 0.000015, indicating its robust predictive capability. Moreover, we conducted feature importance analysis to identify the most influential features for predicting audit risk. The key features found to be critical for classifying fraudulent activities in audit risk prediction are Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, and History_score. This research contributes to the field of audit risk prediction by demonstrating the effectiveness of a neural network-based approach and highlighting the importance of specific features in detecting fraudulent activities. The findings have significant implications for auditors and organizations seeking to enhance their audit risk assessment processes, ultimately leading to improved financial transparency and fraud detection. (shrink)

I argue that epistemic failings are a significant and underappreciated moral hazard in the financial services industry. I argue further that an analysis of these epistemic failings and their means of redress is best developed by identifying policies and procedures that are likely to facilitate good judgment. These policies and procedures are “best epistemic practices.” I explain how best epistemic practices support good reasoning, thereby facilitating accurate judgments about risk and reward. Failures to promote and adhere to best (...) epistemic practices contributed to the 2008 financial crisis. I identify and discuss some of the ways in which best epistemic practices were violated in the events that led to the crisis, with a focus on the role of the credit rating agencies. I go on to discuss some of the ways in which these failings have been redressed. I conclude by observing how proactive regulation for best epistemic practices might help us to anticipate and avoid future crises. (shrink)

Risk communication has been generally categorized as a warning act, which is performed in order to prevent or minimize risk. On the other side, risk analysis has also underscored the role played by information in reducing uncertainty about risk. In both approaches the safety aspects related to the protection of the right to health are on focus. However, it seems that there are cases where a risk cannot possibly be avoided or uncertainty reduced, this (...) is for instance valid for the declaration of side effects associated with pharmaceutical products or when a decision about drug approval or retirement must be delivered on the available evidence. In these cases, risk communication seems to accomplish other tasks than preventing risk or reducing uncertainty. The present paper analyzes the legal instruments which have been developed in order to control and manage the risks related to drugs – such as the notion of “development risk” or “residual risk” – and relates them to different kinds of uncertainty. These are conceptualized as epistemic, ecological, metric, ethical, and stochastic, depending on their nature. By referring to this taxonomy, different functions of pharmaceutical risk communication are identified and connected with the legal tools of uncertainty management. The purpose is to distinguish the different functions of risk communication and make explicit their different legal nature and implications. (shrink)

We investigate the association between controlling shareholders' ownership (CS_Own) and firms' leverage decisions in the Singaporean context. We examine whether the impact of ownership concentration on leverage differs across excess and lower control. We report that shareholders with excess control prefer leverage financing for an optimal capital structure and focus on value maximisation rather using leverage as a tool of minority shareholders' expropriation. Our analysis shows that firms capital structure significantly influences by the coalition of shareholders particularly decisions about leverage (...) financing in addition to the firms' specific characteristics and institutional arrangements. Our empirical evidence shows that controlling shareholders with a lower fraction of equity are more concerned about limited holding thus prefer leverage over equity financing to inflate their equity stake to protect them from the potential takeovers and mergers. We report that capital structure decisions in Singapore are linked with the trade-off between the controlling shareholders' target of mitigating firm risk and their non-dilution entrenchment needs. Further, we found an inverted U-shaped association between control ownership and leverage financing. In terms of moderating effect of family-controlled ownership, our findings exhibit that leverage financing is less pronounced for family firms in Singapore due to the under-diversified investment portfolio. (shrink)

Islamic Banking and Financial Crisis, edited by Habib Ahmed, Mehmet Asutay, and Rodney Wilson, definitely has merit. The book comes at a time when conventional financial institutions face stress and, in many instances, utter failure as a result of the 2008 global financial crisis. While the book is not designed primarily as a retrospective, it does offer an opportunity for reflection.

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network (...) architecture, consisting of three layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

The article discloses the problem of distributing state financial support based on an integrated approach. The study has proved the urgency and necessity of state support for the lowest priority territorial units (regions). It answers the research question of what components need to be included in the methodology for determining state financial support. A comprehensive method for estimating the share of public funds is proposed, taking into account the investment attractiveness of a region (oblast) and the risk (...) of the corresponding region (oblast). To achieve this goal, the following general scientific and special methods and research techniques were used in the work, such as comparative analysis of scientific literature and information sources based on methods of comparison, systematization, and generalization; generalization of the analysis results, as well as logical generation of conclusions and integral assessment. -/- Since the problem of financing the construction and reconstruction of bridges is relevant for a number of countries, this technique was tested using an example of bridge construction. -/- According to the obtained results, territorial units (regions) that are not leaders in priority for the investor and have a high level of riskiness of investing financial resources become eligible for state financial support. The problem of financing such regions can be solved only through state support. The results of calculations show that the distribution of financial resources with the available volume of public finances K=1 allocated for support is carried out proportionally. An integrated approach made it possible to identify 10 territorial units (oblasts) for funding, with the oblasts with the worst priority factors receiving the largest share of state financial support. -/- This study is of practical interest to government agencies in the distribution of public funds, and it is of theoretical importance to researchers dealing with issues of financial security and public administration. (shrink)

The essay title is also the overarching content of the article published in Conservation Letters, August 2023. One of the article’s most notable findings is mentioned as follows: “Specifically, threatened vertebrate fauna with habitat capable of supporting highvalue productive lands received less protection and experienced greater habitat loss.”.

The paper re-expresses arguments against the normative validity of expected utility theory in Robin Pope (1983, 1991a, 1991b, 1985, 1995, 2000, 2001, 2005, 2006, 2007). These concern the neglect of the evolving stages of knowledge ahead (stages of what the future will bring). Such evolution is fundamental to an experience of risk, yet not consistently incorporated even in axiomatised temporal versions of expected utility. Its neglect entails a disregard of emotional and financial effects on well-being before a particular (...) risk is resolved. These arguments are complemented with an analysis of the essential uniqueness property in the context of temporal and atemporal expected utility theory and a proof of the absence of a limit property natural in an axiomatised approach to temporal expected utility theory. Problems of the time structure of risk are investigated in a simple temporal framework restricted to a subclass of temporal lotteries in the sense of David Kreps and Evan Porteus (1978). This subclass is narrow but wide enough to discuss basic issues. It will be shown that there are serious objections against the modification of expected utility theory axiomatised by Kreps and Porteus (1978, 1979). By contrast the umbrella theory proffered by Pope that she has now termed SKAT, the Stages of Knowledge Ahead Theory, offers an epistemically consistent framework within which to construct particular models to deal with particular decision situations. A model by Caplin and Leahy (2001) will also be discussed and contrasted with the modelling within SKAT (Pope, Leopold and Leitner 2007). (shrink)

For decades, the field of system safety has designed safe systems by reducing the risk of physical harm to humans, property and the environment to an acceptable level. Recently, this definition of safety has come under scrutiny by governments and researchers who argue that the narrow focus on reducing physical harm, whilst necessary, is not sufficient to secure the safety of AI systems. There is growing pressure to expand the scope of safety in the context of AI to address (...) emerging harms, with particular emphasis being placed on the ways AI systems can reinforce and reproduce systemic harms. In this paper, we advocate for expanding the scope of conventional safety to include non-physical harms in the context of AI. However, we caution against broadening the scope to address systemic harms, as doing so presents intractable practical challenges for current safety methodologies. Instead, we propose that the scope of safety-related harms should be expanded to include psychological harms. Our proposal is partly motivated by the debates and evidence on social media, which fundamentally reshaped how harm is understood and addressed in the digital age, prompting new regulatory frameworks which aimed to protect users from the psychological risks of the technology. We draw on this precedent to motivate the inclusion of psychological harms in AI safety assessments. By expanding the scope of AI safety to include psychological harms, we take a critical step toward evolving the discipline of system safety into one that is better tuned and equipped to protect users against the complex and emerging harms propagated by AI systems. (shrink)

The financial crisis of 2008–2009 presents us with the opportunity to not only understand what has happened in the markets but also to reflect on the purpose of the marketplace. Drawing from expert economic analyses, we first assess the central lesson of the crisis—the failure of self-regulation by rational self-interest to moderate externalized risk in financial markets. Second, we ask the philosophical question occasioned by the crisis concerning the moral meaning of economic activity: Is market exchange solely (...) for the sake of self-interest? Reflecting on the poetry of Kahlil Gibran and engaging with the recent encyclical of Pope Benedict XVI, we turn our attention from political economy to moral economy: the relationships among market exchange, self-interest, and the common good—and, in particular, the prior conditions of market exchange and their moral significance for the present crisis. (shrink)

By the end of the course students will be able to: - Analyze the issues caused by anonymization and financial virtualization -Develop a clear understanding of Digital Identity and the legal aspects of it - Identify the functioning of cryptocurrencies, blockchain and « digital cash » - Understand the reconfiguration of the balance of power between "traditional" financial actors and new financial players. - Assess the latest developments in cryptocurrency law - Explain new risks in terms of (...) financial security - Develop a prospective analysis on new financial technologies. (shrink)

The incremental risk charge (IRC) is a new regulatory requirement from the Basel Committee in response to the recent financial crisis. Notably few models for IRC have been developed in the literature. This paper proposes a methodology consisting of two Monte Carlo simulations. The first Monte Carlo simulation simulates default, migration, and concentration in an integrated way. Combining with full re-valuation, the loss distribution at the first liquidity horizon for a subportfolio can be generated. The second Monte Carlo (...) simulation is the random draws based on the constant level of risk assumption. It convolutes the copies of the single loss distribution to produce one year loss distribution. The aggregation of different subportfolios with different liquidity horizons is addressed. Moreover, the methodology for equity is also included, even though it is optional in IRC. (shrink)

This very short paper highlights some of my recent and forthcoming work on “good epistemic practices” in the financial services industry. It identifies some epistemic dimensions of risk management in banking and illustrates how managing for good epistemic practices might be helpful.

While there is an extensive literature on how the precautionary principle should be interpreted and when precautions should be taken, relatively little discussion exists about the fair distribution of costs of taking precautions. We address this issue by proposing a general framework for deciding how costs of precautions should be shared, which consists of a series of default principles that are triggered according to desert, rights, and ability to pay. The framework is developed with close attention to the pragmatics of (...) how distributions will affect actual behaviours. It is intended to help decision-makers think more systematically about distributional consequences of taking precautionary measures, thereby to improve decision-making. Two case studies—one about a ban on turtle fishing in Costa Rica, and one about a deep-sea mining project in Papua New Guinea—are given to show how the framework can be applied. (shrink)

The primary responsibility of the US Food and Drug Administration is to protect public health by ensuring the safety of the food supply. To that end, it sometimes conducts risk assessments of novel food products, such as genetically modified food. The FDA describes its regulatory review of GM food as a purely scientific activity, untainted by any normative considerations. This paper provides evidence that the regulatory agency is not justified in making that claim. It is argued that the FDA’s (...) policy stance on GM food is shaped by neoliberal considerations. The agency’s review of a genetically engineered animal, the AquAdvantage salmon, is used as a case study to track the influence of neoliberalism on its regulatory review protocol. After that, an epistemic argument justifying public engagement in the risk assessment of new GM food is outlined. It is because risk evaluations involve normative judgments, in a democracy, layperson representatives of informal epistemic communities that could be affected by a new GM food should have the opportunity to decide the ethical, political or other normative questions that arise during the regulatory review of that entity. (shrink)

The novel coronavirus (COVID-19) has imperatively shaken the behavior of the global financial markets. This study estimated the impact of COVID-19 on the behavior of the financial markets of Europe and the US. The results revealed that the returns of the S&P 500 index have been greatly affected by a lockdown in the US owing to COVID-19. However, the health crisis generated due to the novel coronavirus significantly decreased the stock returns of the Nasdaq Composite index. The results (...) also showed that the economic crisis generated from the pandemic in Spain has had more impact on the IBEX 35 as compared to the health crisis itself. On the other hand, in the long-run, Italy’s stock markets are more affected by the health crisis as contrasted with the economic crisis, while, in the short-run, both lockdown conditions and economic instability lower the stock returns of FTSE MIB. The UK stock markets witnessed that in the short-run, deficiency of health management systems imperatively damaged the stock returns of the London Stock Exchange. The investigation revealed that deficiency of health systems and lockdown conditions have imperatively damaged the structure of financial markets, inferring that sustainable development of these nations is at risk due to COVID-19. The study suggested that governments should allocate more of their budget to the health sector to overcome a health crisis in the future. (shrink)

Current debate and policy surrounding the use of genetic editing in humans often relies on a binary distinction between therapy and human enhancement. In this paper, we argue that this dichotomy fails to take into account perhaps the most significant potential uses of CRISPR-Cas9 gene editing in humans. We argue that genetic treatment of sporadic Alzheimer’s disease, breast- and ovarian-cancer causing BRCA1/2 mutations and the introduction of HIV resistance in humans should be considered within a new category of genetic (...) class='Hi'>protection treatments. We find that if this category is not introduced, life-altering research might be unnecessarily limited by current or future policy. Otherwise ad hoc decisions might be made, which introduce a risk of unforeseen moral costs, and might overlook or fail to address some important opportunities. (shrink)

The Risks of High Birth Rates in Poor Countries Without a Government-Managed Economy -/- In many poor countries, having a large number of children is often seen as a way to secure a family’s future. However, in modern economies where job creation depends primarily on private companies and startups, this strategy becomes highly unsustainable. Without a socialist system managed by the government and its central bank to stabilize employment and provide essential services, rapid population growth can lead to widespread economic (...) and social challenges. -/- The Uncertainty of Private-Sector Job Creation -/- One of the main reasons why having many children in poor countries is not advisable is that job creation relies heavily on private companies and startups, which are highly unstable. Unlike government-managed industries that prioritize long-term economic stability, private companies operate for profit and are subject to market fluctuations. Many businesses, especially startups, fail within a few years, leading to job losses and financial insecurity for workers. Without a strong state intervention to ensure employment stability, large families may struggle to provide for their children. -/- Furthermore, economic recessions can cause mass layoffs, leaving entire families without a source of income. Poor countries often lack sufficient unemployment benefits or social safety nets, making it difficult for parents to support a growing number of children in times of economic downturn. -/- Lack of Government-Controlled Economic Planning -/- In socialist systems, the government and its central bank play a key role in managing the economy by controlling industries, regulating employment, and ensuring economic stability. In contrast, market-driven economies in poor countries often experience economic cycles of booms and busts. During economic downturns, private companies reduce hiring, and job scarcity worsens. -/- Without a government-planned economy, employment opportunities remain unpredictable, making it difficult for large families to secure a stable income. Governments in poor countries typically lack the resources to create enough public-sector jobs, leaving citizens at the mercy of volatile private-sector employment. -/- Strain on Public Services -/- A rapidly growing population increases the demand for essential services such as healthcare, education, and infrastructure. Poor countries often lack the financial resources to expand these services quickly enough to match population growth. As a result, schools become overcrowded, healthcare facilities are overburdened, and infrastructure development lags behind, leading to lower living standards. -/- Without a strong government-backed socialist system to manage resources efficiently, families with many children face limited access to quality education and healthcare. This creates a cycle of poverty, where children grow up without proper education and skills, reducing their chances of securing stable jobs in the future. -/- Wage Suppression and Exploitation of Labor -/- When population growth outpaces job creation, the labor market becomes oversaturated, leading to lower wages. In economies dominated by private companies, employers take advantage of surplus labor to keep wages low. This makes it difficult for large families to earn enough income to support their basic needs. -/- In contrast, a government-managed economy could regulate wages and ensure fair labor conditions, preventing the exploitation of workers. Without such regulations, families in poor countries face the risk of being trapped in a cycle of low wages and poor working conditions, making it increasingly difficult to escape poverty. -/- The Risks of Entrepreneurial Dependence -/- While entrepreneurship is often promoted as a solution to job shortages, startups and small businesses are highly risky, especially in poor countries where access to capital is limited. Many aspiring entrepreneurs lack the financial resources, technical skills, and market access to sustain successful businesses. Without government-backed support, such as low-interest loans, subsidies, or public sector employment, relying on entrepreneurship for job creation remains an uncertain strategy. -/- Conclusion -/- In countries without a socialist system where the government actively manages economic stability and employment, having many children can lead to significant economic and social challenges. The reliance on private companies and startups for job creation is highly risky due to market fluctuations, limited public services, suppressed wages, and the difficulties of entrepreneurship. Without strong government intervention to regulate employment and provide social support, large families in poor countries face higher risks of poverty and economic instability. -/- To ensure a sustainable future, poor countries should focus on balancing population growth with economic development. This requires investment in education, healthcare, and employment programs that provide stable opportunities for all citizens. Without such measures, uncontrolled population growth in market-driven economies will only deepen poverty and inequality. -/- . (shrink)

Results indicate substantial improvements in efficiency, accuracy, and personalized care, but also highlight the challenges of data privacy, ethical considerations, and system scalability. By providing a structured analysis, this research contributes insights into optimizing generative AI deployments for both banking and healthcare, ensuring a balance between innovation and risk management. The study concludes with recommendations for future research directions, including advanced model training, ethical guidelines, and enhanced privacy measures. These insights aim to inform practitioners on the benefits of generative (...) AI, ensuring sustainable integration into banking and healthcare ecosystems. (shrink)