Blockchain Papers

Teresa Goody Guillén

No abstract is available for this record.

Ashimiyu Nafiu, Salaam Olawale Balogun, Courage Oko-Odion

The complexities of modern financial markets, characterized by heightened volatility and uncertainty, have necessitated the evolution of advanced risk management strategies.As global markets become increasingly interconnected, financial institutions, investors, and policymakers face unprecedented challenges in identifying, assessing, and mitigating risks.Effective risk management has emerged as a cornerstone of financial stability, requiring a blend of traditional methods and innovative tools.This paper explores comprehensive strategies for navigating volatility in complex financial environments, addressing systemic, credit, market, and operational risks.Traditional approaches, such as portfolio diversification and value-at-risk (VaR) modelling, remain foundational but are now complemented by cutting-edge technologies, including artificial intelligence (AI), machine learning (ML), and big data analytics.These tools enable real-time monitoring, predictive analytics, and stress testing, enhancing the capacity to anticipate and respond to emerging threats.Additionally, the integration of blockchain technology offers improved transparency and resilience in financial transactions, further mitigating systemic vulnerabilities.Case studies from diverse sectors highlight the practical applications of these strategies, illustrating how robust risk management frameworks can minimize losses, enhance profitability, and ensure regulatory compliance.The paper also examines the role of regulatory frameworks in shaping risk management practices and emphasizes the importance of a proactive, adaptive approach in navigating volatile market conditions.By combining traditional methodologies with technological advancements, financial institutions can build resilient systems capable of withstanding shocks and fostering long-term stability.This paper concludes by identifying emerging trends, such as quantum computing and decentralized finance, as transformative forces likely to redefine risk management in the future.

Elena Korobova, Dean Fantazzini

No abstract is available for this record.

Burcu Kapar, Mabruk Billah, Mohammad Talha

No abstract is available for this record.

Archana Pattabhi

The increased volatility in the financial world, alongside the dynamics that characterize the global economy, have motivated the concept of Financial Digital Twins (FDTs) as AI-based, virtual models of the banking systems aimed to optimize risk management, fraud detection, and operational performance. With real-time data, operational research for risk assessment, and artificial intelligence systems, FDTs are useful in helping financial institutions anticipate risks, manage their decision systems, and design a better model for compliance with regulations. In the following paper, a literature review will look into using AI and ML to enhance the effective development of Financial Digital Twins. It discusses some modelling approaches that can be used in the industry, including Monte Carlo simulations, agent-based modelling, and the scenario approach, which help financial institutions model the market risk and credit performance alongside conditions in an economic downturn. Moreover, it reveals that AI can benefit credit scoring, fraud detection, and stress testing to increase the evaluation of risks. Still, when it comes to the drawbacks of the FDT, they are all associated with data protection, data processing, scalability, compliance issues, and AI model quality, respectively. This paper also covers new technologies like quantum computing, blockchain integration, and decentralized finance (DeFi), which have enhanced the existing dimensions of risk management in finance. Financial institutions must meet these challenges and adapt high technologies to advance banking systems to be financially sound, more informed, and more protective of banking systems

Yu Li, Jian Jiao, Shi Ping

No abstract is available for this record.

Liyuan Zhang, Limian Ci, Yonghong Wu, Benchawan Wiwatanapataphee

The rapid expansion of blockchain technology has created both opportunities and challenges in financial markets, particularly in the investment of blockchain-based real estate tokens. Unlike traditional financial assets, these investments exhibit high volatility, decentralized trading mechanisms, and complex transaction fee structures, all of which significantly influence portfolio management strategies. This study tackled the core issue of portfolio optimization in blockchain asset markets by incorporating both proportional and fixed transaction costs, factors often overlooked in conventional models. To address this, we proposed a multi-period investment optimization framework that leveraged Lagrange multipliers and dynamic programming to determine optimal asset allocation. A key feature of our model was its ability to define an optimal no-trade region, balancing transaction costs with investment returns under varying fee structures. Through numerical experiments, we analyzed how different levels of transaction costs impacted trading frequency, risk exposure, and portfolio efficiency. Our findings indicated that higher transaction costs expanded the no-trade region, reducing trading frequency, while lower costs encouraged more frequent rebalancing. Additionally, we highlighted the practical benefits of blockchain real estate tokenization, including lower investment barriers, enhanced market liquidity, and seamless cross-border transactions. By providing a robust theoretical and empirical framework, this research offered valuable insights for investors navigating blockchain-based financial markets and contributed to the broader discourse on decentralized finance (DeFi) and tokenized real estate investments.

Lauri Naskali

Tutkielma tarkastelee älysopimusten ja lohkoketjuteknologian soveltamista vakuutusliiketoiminnassa, painopisteenä parametriset vakuutukset. Tavoitteena on arvioida, miten teknologia vaikuttaa vakuutusmarkkinoiden keskeisiin ongelmiin — haitalliseen valikoitumiseen, moraalikatoon, kilpailuun ja hallinnolliseen tehokkuuteen — sekä millaisia haasteita käyttöönottoon liittyy. Menetelmänä on kirjallisuuskatsaus, jota täydennetään olemassa olevien ratkaisujen tapausesimerkeillä.

Dawei Xu, Fan Huang, Jiaxin Zhang, Yunfang Liang · 6 authors

With the rapid proliferation of Internet of Things (IoT) devices, ensuring their communication security has become increasingly important. Blockchain and smart contract technologies, with their decentralized nature, provide s... | Find, read and cite all the research you need on Tech Science Press

Alessandro Cocco

No abstract is available for this record.

Henry Han

No abstract is available for this record.

Sergii Grybniak, Oleksandr Nashyvan, Igor Mazurok, Yevhen Leonchyk · 5 authors

ABSTRACT This article presents algorithms and smart contract designs to facilitate recurring bill payments on decentralised platforms using the Ethereum‐like Virtual Machine (EVM). The proposed approach enables the inclusion of recurring and deferred transactions, ensuring compatibility with ERC‐20 and ERC‐777 standards, thereby contributing to the establishment of a novel token standard. The research addresses the growing need for non‐custodial mechanisms to support automatic periodic payments in decentralised environments, offering potential benefits to both service providers and customers in various industries.

kaushal patidar

No abstract is available for this record.

Hu Ju, Luo Jie, Cheng Wang

No abstract is available for this record.

Xihui Haviour Chen, Provash Kumer Sarker, Chi Keung Marco Lau

No abstract is available for this record.

S Sarumathi, Juliet Johny, Lukas Mol, Ms. Shruti G. Khandare · 5 authors

The integration of block chain technology in disaster relief donation processes offers a transformative approach to enhance transparency, efficiency, and trust. Although the conventional methods can be easy to use and reasonably priced, they could not provide the transparency and immutability that block chain-based alternatives provide. The block chain based charity process framework(BECP) aims to overcome the difficulties of conventional methods in terms of transparency and immutability, The Proposed approach explores the implementation of a block chain-based donation system during disasters, highlighting its potential to address longstanding challenges in traditional donation methods. By leveraging the immutable and decentralized nature of block chain, the proposed system ensures secure and traceable transactions, minimizing the risk of fraud and misappropriation of funds. Smart contracts automate the allocation and disbursement of donations, reducing administrative overhead and expediting aid delivery to affected areas. Furthermore, the transparent ledger allows donors to track their contributions in real-time, fostering accountability and encouraging sustained support. This innovative approach leverages distributed ledger technology to create an immutable record of all transactions, ensuring that every donation is traceable and accounted for. This technology not only streamlines the donation process but also fosters trust among donors, beneficiaries, and relief organizations, potentially encouraging increased participation in disaster relief efforts. This study examines the technical architecture, benefits, and potential obstacles of implementing such a system, providing insights into its feasibility and impact on improving the overall effectiveness of disaster relief efforts.

Michel Guirguis

No abstract is available for this record.

Emomotimi Agama

No abstract is available for this record.

Ammoon Birzoim

No abstract is available for this record.

Prajkta Waditwar

The rise of artificial intelligence (AI) in procurement has transformed how organizations engage with suppliers, optimize spending, and drive contract negotiations. Traditional procurement negotiations rely on human intuition, historical knowledge, and manual research. However, with the advancement of AI-driven Smart Negotiation Assistants, procurement teams can leverage real-time market intelligence, price benchmarks, and predictive analytics to autonomously negotiate contracts. This paper introduces an AI-powered Procurement Chatbot, capable of conducting supplier negotiations with minimal human intervention. The system utilizes machine learning (ML), natural language processing (NLP), and historical transaction data to negotiate terms, secure cost savings, and ensure compliance with procurement policies. Real-world case studies, including automated software licensing negotiations and dynamic supplier pricing adjustments, demonstrate how AI-driven negotiations can save millions in procurement costs, reduce cycle times by up to 40%, and mitigate supplier risks [1]. The paper also explores technical architecture, algorithmic models, and deployment strategies for integrating AI negotiation assistants into enterprise procurement workflows. Furthermore, it highlights regulatory and ethical considerations in AI-driven procurement, emphasizing transparency and fairness. By leveraging AI-driven negotiation chatbots, businesses can achieve autonomous, efficient, and data-driven procurement processes, ensuring better supplier relationships and long-term cost savings.

Mohammad Naser Reyhani

No abstract is available for this record.

Damodar Bihani, Bright Chibunna Ubamadu, Andrew Ifesinachi Daraojimba

The fusion of financial modeling and blockchain technology presents a transformative paradigm for advancing portfolio management and risk assessment. Traditional financial modeling, while robust in projecting asset performance and managing portfolio allocations, often grapples with issues of data transparency, latency, and counterparty trust. Blockchain, with its decentralized, immutable, and transparent ledger infrastructure, offers a compelling solution to these limitations by enabling real-time data validation, smart contract automation, and trustless transactions. This paper proposes an integrated framework that leverages blockchain technology to enhance the accuracy, efficiency, and security of financial models used in dynamic portfolio management and risk evaluation. At the core of this framework is the use of tokenized assets and decentralized financial instruments that enable seamless tracking of asset performance across diverse investment classes. Smart contracts are utilized to automate portfolio rebalancing, enforce compliance, and mitigate execution risk. Furthermore, decentralized oracles and on-chain analytics provide real-time market data that improves model inputs, leading to more accurate forecasts and risk-return simulations. By embedding cryptographic proofs and consensus protocols within the financial modeling infrastructure, the proposed framework minimizes data manipulation, enhances auditability, and fosters institutional trust. The integration of blockchain also redefines traditional risk assessment models by introducing mechanisms for real-time stress testing, liquidity monitoring, and exposure analysis across decentralized finance (DeFi) ecosystems. This shift not only improves the responsiveness of financial decision-making but also supports the development of more resilient investment strategies that adapt to market volatilities. Case studies within this research demonstrate how blockchain-enabled financial modeling tools reduce operational friction, improve transparency, and provide better risk-adjusted returns in both traditional and emerging financial markets. The framework aligns with the increasing demand for digital asset governance and regulatory compliance in the evolving fintech landscape. This paper contributes to the literature by offering a scalable and secure blueprint for future financial systems, paving the way for institutions to adopt hybrid models that marry the strengths of quantitative finance and blockchain innovation.

Madina V. Alikaeva, M.A. Volov

No abstract is available for this record.

Emanuele Antonio Napoli, Noemi Romani, Valentina Gatteschi, Claudio Schifanella

No abstract is available for this record.