Risk Management Solutions Research Articles

Research on Innovation of Food Logistics Supply Chain Management

In the context of globalization and constantly changing consumer demand, the management of food logistics supply chains has become increasingly complex and important. This paper mainly studies the problems and innovative methods in food logistics supply chain management, aiming to improve the efficiency and adaptability of the supply chain by optimizing management strategies. This paper adopts literature analysis and case analysis methods to analyze in detail the problems of information asymmetry, cost control, transportation efficiency, and inventory management in the food logistics supply chain. It proposes innovative supplier management models, digital management, modern supply chain management concepts, inter chain cooperation, and risk management solutions. Research has found that adopting information-sharing mechanisms and advanced information technology, as well as strengthening collaboration among various links in the supply chain, can effectively improve management efficiency and reduce operating costs. This study provides some useful references for food logistics enterprises in practical operation, helping them improve service quality and reduce operating costs in a fiercely competitive market environment, enhance market competitiveness, ensure food safety and freshness, and meet the growing needs of consumers.

Risk Management and Software Solutions in Financial Institutions: Move Towards Effective Implementation

Technological advancements and intensified regulatory pressures have led to a new level of the evolution of risk management in financial institutions. The entities have exposure to different categories of risks, such as credit risks, market risks, operational risks, and cybersecurity risks. The growing intensity of these factors makes proper risk management crucial for the stabilization and success of such enterprises. This report analyzes the best practices and software applications adopted by financial institutions for effective risk management. Improved risk identification, assessment, mitigation, and reporting within the organization would be through the integration of advanced analytics, AI, ML, and cloud computing. Based on this, the current paper assesses the part that these technologies play in contributing to compliance, cost savings, and better decision-making skills.

Research on Time Management and Risk Management of Small and Medium-Sized Enterprises

This study aims to explore SME time management and risk management in R & D projects. First, we define project time management and project risk management, and introduce commonly used tools and models. Next, the definition of SMEs and the type of R & D projects are explained, and the problems faced in time management and risk management are analyzed. We also explored the relationship between project risk management and time management in SMEs. Finally, analysis and selection methods for SMEs when selecting project time management and risk management tools. The purpose of this study is to provide effective time management and risk management solutions for SMEs.

The relativity of perspective: exploring the disconnect between Indigenous and Western paradigms of disaster risk perception

PurposeThis article demonstrates how psycho-sociological concepts have a place in disaster risk sciences. It draws attention to the relationship between risk perception and disaster management from Western and traditional viewpoints.Design/methodology/approachThis paper is conceptual and draws from published works. The systematic literature review (SLR) methodology was adopted to analyse existing literature on the subject matter.FindingsRisk perception evolved over centuries and disciplines until it found applicability in modern times. Despite the proliferation of western science-based approaches to risk perception, Indigenous knowledge systems still hold sway over communities’ understanding of risk. These perspectives are enshrined in religious and cultural convictions that become the lenses through which a society assigns cause, effect and remedy to risk events. A deeper understanding of these convictions enables disaster risk management strategies to be better accepted by those at risk and to align with their lived realities.Originality/valueRisk perception becomes the lens through which we better understand the realities and complexities of populations at risk. Indigenous knowledge systems have a strong influence on society’s perception of risk and if they are not harnessed and studied, they will stand in conflict with Western approaches. Hence, the study of the nexus between risk perception and disaster management presents an opportunity for policymakers and practitioners to design risk management solutions that have a higher chance of acceptance and sustainability.

Enhancing Sustainability through Weather Derivative Option Contracts: A Risk Management Tool in Greek Agriculture

This paper investigates the efficacy of weather derivatives as a risk management tool in the agricultural sector of Naousa, Greece, focusing on tree crops sensitive to temperature variations. The specific purpose is to assess how effectively weather derivative options can mitigate financial risks for farmers by providing strategic solutions. The study assesses the strategic application of Heating Degree Days (HDD) index options and their potential to alleviate economic vulnerabilities faced by farmers due to temperatures fluctuations. Employing different strike prices in Long Call and Straddle options strategies on the HDD index, the research offers tailored risk management solutions that cater to varying risk aversions among farmers. Moreover, the study applies the Value at Risk (VaR) methodology to quantify the financial security that weather derivatives can furnish, revealing a significantly reduced probability of severe financial losses in hedged scenarios compared to no-hedge conditions. Results show that all implemented strategies effectively enhance financial outcomes compared to scenarios without hedging, highlighting the exceptional utility of weather derivatives as risk management tools in the agricultural sector. Strategy 4, which exhibits the lowest VaR, emerges as the most effective, providing substantial protection against adverse weather conditions. This research supports the notion that weather derivatives can substantially contribute to the economic sustainability of rural economies, influencing policy decisions toward enhancing financial instruments for risk management in agriculture.

Growth Strategy for Start-Up Businesses: Analysis of Solutions for Scalability, Marketing, and Risk Management

Growth Strategy for Start-Up Businesses: Analysis of Solutions for Scalability, Marketing, and Risk Management

Predictive Methods and AI - Driven Solutions for Risk Management in Organizations

Predictive Methods and AI - Driven Solutions for Risk Management in Organizations

AI-driven financial risk management systems: Enhancing predictive capabilities and operational efficiency

The integration of artificial intelligence (AI) in financial risk management systems has revolutionized traditional approaches, providing enhanced predictive capabilities and operational efficiency. This paper explores the various applications of AI in credit risk assessment, market risk analysis, operational risk management, and regulatory compliance. AI-driven systems leverage advanced machine learning algorithms to analyze vast datasets, including real-time market data and non-traditional sources, improving risk predictions and enabling proactive risk management. Scenario simulations, predictive modeling, real-time data analysis, and automated decision-making are discussed as core components of AI-driven systems. The paper also highlights the benefits of AI in automating routine tasks, enhancing data analytics, and ensuring regulatory compliance. By continuously learning and adapting to new data, AI systems offer dynamic risk management solutions that address evolving market conditions and regulatory requirements. This comprehensive analysis demonstrates how AI-driven financial risk management systems can significantly reduce the incidence of loan defaults, enhance portfolio quality, and improve the overall resilience of financial institutions.

EARLY LANDSLIDE WARNING SYSTEM

Landslides pose significant threats to both human lives and infrastructure, especially in regions prone to geological instabilities. Timely detection of early signs of potential landslides is crucial for mitigating the risks associated with these natural disasters. This project introduces an innovative approach utilizing the NodeMCU platform, integrated with a suite of sensors including accelerometers, gyroscopes, and moisture detectors, to create an early landslide detection system. By continuously monitoring ground conditions, including soil moisture levels and ground vibrations, the system employs real-time data analysis and anomaly detection algorithms to provide early warnings to relevant authorities and communities. The implementation leverages the versatility and connectivity capabilities of C, ensuring seamless data transmission for remote monitoring and rapid response. This project not only showcases the potential of IoT technology in enhancing natural disaster preparedness but also underscores its significance in safeguarding lives and property. The experimental results and performance evaluation demonstrate the effectiveness of the proposed system in detecting early signs of landslides, offering a promising solution for proactive risk management in landslide-prone areas. Keywords: Embedded based,NodeMCU

Advanced risk management solutions for mitigating credit risk in financial operations

Advanced risk management solutions are essential for mitigating credit risk in financial operations, particularly in today's volatile economic environment. This Review explores the innovative approaches and technologies being utilized to enhance credit risk management and safeguard financial institutions against potential losses. Credit risk, the possibility that a borrower will default on their obligations, poses a significant threat to financial stability. Traditional methods of assessing and managing credit risk, such as credit scoring and historical data analysis, are no longer sufficient to address the complexities of modern financial markets. Advanced risk management solutions offer more robust and dynamic tools for identifying, assessing, and mitigating credit risk. One of the key advancements in this field is the integration of big data and machine learning algorithms. By analyzing vast amounts of data from diverse sources, financial institutions can gain deeper insights into borrower behavior, market trends, and economic indicators. Machine learning models can predict default probabilities with greater accuracy, allowing for proactive risk mitigation strategies. Additionally, real-time risk monitoring systems have become increasingly prevalent. These systems provide continuous oversight of credit portfolios, enabling financial institutions to detect early warning signs of potential defaults and take timely action. Advanced analytics and visualization tools facilitate the identification of emerging risks and the implementation of targeted interventions. Another crucial component of advanced risk management solutions is the use of stress testing and scenario analysis. These techniques simulate various economic conditions and assess the impact on credit portfolios, helping financial institutions prepare for adverse scenarios and develop contingency plans. Furthermore, blockchain technology is emerging as a promising tool for enhancing transparency and reducing fraud in credit transactions. By providing a secure and immutable record of credit histories and transactions, blockchain can improve trust and reliability in credit assessments. In conclusion, advanced risk management solutions are transforming the way financial institutions mitigate credit risk. By leveraging big data, machine learning, real-time monitoring, stress testing, and blockchain technology, financial institutions can achieve more accurate risk assessments and implement more effective risk mitigation strategies. These innovations not only enhance the stability and resilience of financial operations but also contribute to a more secure and trustworthy financial system.

Corporate Investment Decisions in Changing Interest Rate Environments

Corporate investment decisions are crucial in shaping the financial landscape of businesses, especially amidst fluctuating interest rates. India Infoline Finance Limited (IIFL), a key player in the Indian financial market, significantly influences corporate investment strategies in such environments. This study analyzes how fluctuating interest rates impact corporate investment behavior, including capital allocation, financing decisions, risk management, and overall financial performance. By examining economic indicators, industry trends, and regulatory frameworks, the research identifies challenges and opportunities for businesses in dynamic interest rate landscapes. It also assesses the effectiveness of IIFL's advisory services, financial products, and risk management solutions. Through real-world scenarios, case studies, and expert insights, the study provides practical recommendations for businesses and financial institutions. This research enhances understanding of interest rate dynamics and their implications for corporate investment decisions, helping businesses strengthen financial resilience and optimize investment strategies for sustained growth.

From object obfuscation to contextually-dependent identification: enhancing automated privacy protection in street-level image platforms (SLIPs)

ABSTRACT Street-level image platforms (SLIPs) employ indiscriminate forms of data collection that include potentially privacy invasive images. Both the scale and the indiscriminate nature of data collection means that significant privacy management requirements are needed. Legal risk management is currently operated through obfuscation techniques involving certain image objects. Current SLIP object obfuscation solutions are an indiscriminate and a blunt solution to a similarly indiscriminate data collection concern. A new contextual approach to obfuscation is required that goes beyond object obfuscation. Contextually-dependent identification would seek to identify the contexts, including captured objects, which can give rise to privacy concerns. It is technically more challenging for automated solutions as it requires an assessment of the contextual situation to understand privacy risk. Context-sensitive privacy detection, combined with context-sensitive privacy-by-design processes, potentially offer a risk management solution that better situates and addresses the concerns arising from SLIP data collections.

Cardiovascular Risk Management In Patients With Rheumatoid Arthritis: A Systematic Review.

Rheumatoid arthritis (RA) is an autoimmune chronic inflammatory joint disease associated with pain, swelling, and morning stiffness. It not only affects the joints but also exhibits many extra-articular manifestations. It is recognized as an independent risk factor for cardiovascular (CV) abnormalities. The possibility of cardiovascular disease (CVD) risk in patients with RA is about twofold higher compared to non-RA individuals. Therefore, early risk assessment and management of risk factors are crucial to reduce the CV morbidity and mortality associated with RA. This systematic literature review summarizes the data available on the management of CVD risk factors in RA. A total of 61 articles from the most reputable journals published between 2013 and 2023 were reviewed, of which seven papers were selected for in-depth analysis. We tried to eliminate bias using various bias-eliminating tools. This analysis considers the proposed solution for CV risk prevention and management in RA patients. Optimal control of disease activity and persistent monitoring of other factors responsible for increased CV events in RA patients is the ultimate management of CV abnormalities. This study summarizes the recommendations for the management of CV risk factors in patients with RA.

The importance of technology and cold chain logistics in Vietnam's preservation of harvested seafood

Vietnam has been experiencing significant economic growth in recent years, making it an attractive destination for foreign investors. With globalization and the expansion of trade relationships, logistics management has become crucial for domestic and multinational companies operating in Vietnam. However, logistics operations in Vietnam are exposed to various risks, such as natural disasters, infrastructure issues, regulatory uncertainty, and human factors. Therefore, it is essential to manage logistics risk effectively to ensure the supply chain's resilience and the business's sustainability. This paper aims to provide a critical review of the risk management literature in logistics by analyzing the key concepts of supply chain risk, the principles of logistic risk management, types of logistics risks, and some ideas on solutions in risk management in the supply chain. Keywords: Supply chain, risk management, Vietnam

Assessment of Climate Change Risk on Insurance Portfolios

Purpose: The general purpose of this study was to investigate the assessment of climate change risk on insurance portfolios.
 Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The findings reveal that there exists a contextual and methodological gap relating to climate change risk on insurance portfolios. The assessment of climate change risk on insurance portfolios reveals the significant challenges posed by increasingly frequent and severe climate-related events, impacting insurers' financial stability and policyholders' security. Key conclusions emphasize the imperative for insurers to enhance climate risk modeling, integrate climate considerations into decision-making processes, and foster collaboration with stakeholders to develop effective risk management solutions. Proactive measures are essential to address the systemic nature of climate risks, underscoring the urgency of collective action and innovation to build resilience and sustainability in insurance portfolios and broader society amidst a changing climate.
 Unique Contribution to Theory, Practice and Policy: The Prospect theory, Agency theory and the Resilience theory may be used to anchor future studies relating to climate change risk on insurance portfolios. Insurers are advised to invest in advanced risk modeling, diversify risk exposure across regions and lines of business, integrate climate risk into underwriting and pricing, strengthen regulatory oversight, collaborate with stakeholders, and invest in climate adaptation and mitigation measures. These recommendations aim to improve insurers' ability to quantify and manage climate-related risks effectively, promote sustainability, and contribute to broader resilience-building efforts in the face of climate change.
 Keywords: Climate Change Risk, Insurance Portfolios, Resilience, Risk Modeling, Diversification, Underwriting, Regulatory Oversight, Collaboration

Види цифрового бізнесу у сфері рітейлу

Analyzing various aspects of digital business in the context of European integration processes, it is substantiated that digitalization plays a key role in the modern economy, facilitating the transformation of traditional business approaches. It has been proven that European integration processes provide a powerful impetus for the development of digital business, opening new markets and promoting the establishment of unified standards in e-commerce, data protection, and consumer protection. This creates conditions for seamless cross-border interaction between companies and consumers, ensuring high competitiveness and innovative development. It is argued that the use of digital technologies and online platforms allows businesses to adapt to changing market conditions, optimize internal processes, and enhance customer satisfaction through personalized offers and high-quality service. At the same time, digital businesses face challenges related to the need to comply with regulatory requirements, ensure cybersecurity, and protect personal data. However, these challenges also encourage companies to innovate and seek new solutions for effective risk management. Overall, European integration processes significantly contribute to the development of digital business in Europe, opening up broad prospects for growth and international cooperation.

A policy instruments palette for spatial quality: lessons from Dutch flood risk management

ABSTRACT Worldwide, more integrated and spatially embedded forms of flood risk management have been advocated. In the Netherlands, this ‘spatial turn’ can be associated with a quest for spatial quality, i.e. making use of existing landscape values to create more liveable, aesthetic and sustainable flood risk management solutions. Reflecting on Dutch flood risk management practice, this paper inventorizes which policy instruments are currently used to strengthen spatial quality, and how involved actors view these instruments. We present empirical insights on common concerns, standpoints and dilemmas from the Dutch Flood Protection Programme (DFPP), a large-scale reinforcement operation to climate-proof the Netherlands’ main flood defences by 2050. Spatial quality here remains a rather ambiguous policy objective, lacking a legally binding framework. Using the NATO-policy instruments’ typology as a starting point, and based on a co-learning process between science and practice, we present an instruments palette that can be used to strengthen spatial quality in flood risk management. Our findings reveal that the DFPP makes use of rather ‘soft’ policy instruments. The actual achievement of spatial quality goals seems to depend largely on the combined project team competencies, guidance and support provided by responsible water authorities, and commitment of other project partners.

FINTECH, TAXATION, AND REGULATORY COMPLIANCE: NAVIGATING THE NEW FINANCIAL LANDSCAPE

The emergence of financial technology (Fintech) has revolutionized the global financial landscape, offering innovative solutions that challenge traditional banking systems and investment practices. This review explores the intersection of Fintech, taxation, and regulatory compliance, highlighting the complexities and opportunities within this dynamic ecosystem. Fintech encompasses a wide range of technologies, including blockchain, artificial intelligence, and mobile payment systems, which have streamlined financial services and expanded access to capital markets. However, this rapid evolution poses significant challenges for taxation and regulatory frameworks. Traditional tax laws struggle to keep pace with the speed and complexity of digital transactions, leading to uncertainties in tax treatment and enforcement. Navigating the tax implications of Fintech requires a nuanced understanding of digital assets, decentralized finance (DeFi) platforms, and cross-border transactions. Tax authorities worldwide are grappling with these challenges, seeking to balance innovation and compliance while ensuring a fair and transparent tax regime. The review examines various approaches adopted by governments and regulatory bodies to address Fintech taxation, including legislative reforms, international cooperation, and the use of advanced data analytics. Furthermore, regulatory compliance remains a critical concern for Fintech firms, as they must navigate a labyrinth of rules and standards across jurisdictions. Compliance requirements vary widely, ranging from anti-money laundering (AML) regulations to data protection laws, presenting operational and legal challenges for market participants. The review discusses strategies for achieving regulatory compliance in the Fintech sector, emphasizing the importance of proactive risk management, regulatory engagement, and technological solutions such as RegTech. Despite these challenges, the convergence of Fintech, taxation, and regulatory compliance offers immense opportunities for innovation and growth. By embracing digital transformation and adopting agile regulatory frameworks, governments and businesses can unlock the full potential of Fintech while safeguarding financial stability and integrity. This review provides insights into the evolving landscape of Fintech taxation and regulatory compliance, highlighting key trends, challenges, and best practices for navigating this new frontier in finance.
 Keywords: Fintech, Taxation, Financial, Technology, Review.

INTEGRATING ARTIFICIAL INTELLIGENCE IN PERSONALIZED INSURANCE PRODUCTS: A PATHWAY TO ENHANCED CUSTOMER ENGAGEMENT

The integration of Artificial Intelligence (AI) in the insurance sector has ushered in a new era of personalized insurance products, offering enhanced customer engagement and satisfaction. This review explores the transformative potential of AI in reshaping the landscape of insurance services, focusing specifically on the augmentation of customer engagement through personalized offerings. AI-driven algorithms and machine learning techniques enable insurers to analyze vast amounts of data with unprecedented speed and accuracy, facilitating the customization of insurance products to meet individual customer needs. By leveraging data from various sources such as IoT devices, social media, and historical claims data, insurers can gain deeper insights into customer behavior, preferences, and risk profiles. Personalized insurance products not only cater to the unique requirements of customers but also foster greater engagement by offering tailored recommendations, proactive risk management solutions, and real-time assistance. Through predictive analytics, AI algorithms can anticipate customer needs and preferences, allowing insurers to offer timely and relevant services, thereby enhancing customer satisfaction and loyalty. Moreover, AI-powered chatbots and virtual assistants serve as accessible and responsive touchpoints for customers, providing instant support, guidance, and personalized recommendations throughout the insurance lifecycle. By streamlining communication channels and offering seamless interactions, AI technologies strengthen the bond between insurers and customers, fostering long-term relationships built on trust and transparency. The integration of AI in personalized insurance products represents a transformative pathway towards enhanced customer engagement. By harnessing the power of AI-driven analytics and automation, insurers can deliver tailor-made solutions that resonate with individual customers, driving higher levels of satisfaction, loyalty, and ultimately, business growth.
 Keywords: Artificial Intelligence, Insurance, Privacy-Enhanced, Customer, Engagement, Review.

Environmentally Friendly Antiagglomerants: A Promising Solution for Gas Hydrate Plugging and Corrosion Risk Management in Oil and Gas Pipelines

Environmentally Friendly Antiagglomerants: A Promising Solution for Gas Hydrate Plugging and Corrosion Risk Management in Oil and Gas Pipelines