Agile methodologies in digital banking: Theoretical underpinnings and implications for customer satisfaction

Open Access Research Journal of Science and Technology, Journal Year: 2024, Volume and Issue: 10(2), P. 021 - 030

Published: March 26, 2024

This paper delves into the theoretical underpinnings of agile methodologies and investigates their potential to enhance customer satisfaction in digital banking. Theoretical foundations draw on several key frameworks complexity theory, complex systems, like banking ecosystems, exhibit emergent properties. Traditional linear approaches struggle predict these. Agile embraces iterative development cycles adaptability changing requirements, acknowledging this lean thinking, derived from manufacturing, thinking prioritizes eliminating waste maximizing value. translates by focusing short sprints, prioritizing features with highest impact, minimizing unnecessary functionalities co-creation, traditional models often distance customers process. emphasizes actively involving them design testing. fosters a deeper understanding needs leads more relevant satisfying experiences. practices encompass diverse practices. visual management system focuses workflow optimization. Promoting continuous flow work deployment user stories acceptance criteria, User Acceptance criteria define specific conditions feature must meet for approval. These ensure align expectations. hold significant promise enhancing digit allows banks deliver new faster, keeping pace evolving demands. Customers benefit quicker access innovative solutions that address financial needs. results experiences are intuitive, efficient, cater Increased Innovation, The nature learning experimentation. Banks can test features, gather feedback, rapidly iterate upon them, leading dynamic experience. Improved transparency trust, promote open communication collaboration between teams customers. kept informed updates have voice shaping process, fostering trust sense ownership.

Language: Английский

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Theoretical frameworks in AI for credit risk assessment: Towards banking efficiency and accuracy

International Journal of Scientific Research Updates, Journal Year: 2024, Volume and Issue: 7(1), P. 092 - 102

Published: March 26, 2024

This paper delves into theoretical frameworks in AI for credit risk assessment, exploring how these enhance banking efficiency and accuracy. It discusses various techniques such as machine learning algorithms, neural networks, natural language processing, their application assessment. Furthermore, it examines the challenges opportunities presented by frameworks, highlighting potential to revolutionize sector. Revolutionizing Credit Risk Assessment Banking, The Role of Artificial Intelligence In dynamic realm finance, assessment stands a fundamental pillar institutions. Traditionally, this process has heavily relied on statistical models historical data. However, emergence (AI) catalyzed transformative shift domain. elucidates underpinnings employed investigates profound implications enhancing accuracy operations. exploration begins delineating pertinent Leveraging processing techniques, offer innovative approaches evaluate creditworthiness. Unlike conventional methods, AI-driven possess capacity ingest vast datasets, identify intricate patterns, adapt dynamically evolving market dynamics. Such capabilities empower banks make more informed timely decisions regarding lending activities. Moreover, practical Through case studies empirical evidence, advanced methodologies enable mitigate risks while maximizing profitability. By harnessing AI, financial institutions can optimize scoring processes, defaulters with greater accuracy, customize terms based individual profiles. Additionally, facilitates real-time monitoring portfolios, allowing proactive management interventions prevent adverse outcomes.

Language: Английский

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FINANCIAL LAW: POLICY FRAMEWORKS FOR REGULATING FINTECH INNOVATIONS: ENSURING CONSUMER PROTECTION WHILE FOSTERING INNOVATION

Finance & Accounting Research Journal, Journal Year: 2024, Volume and Issue: 6(4), P. 515 - 530

Published: April 7, 2024

The proliferation of fintech innovations has necessitated the development comprehensive regulatory frameworks to uphold consumer protection standards while fostering an environment conducive technological advancement. This paper delves into intricate policy landscapes governing innovations, with a primary focus on striking delicate equilibrium between safeguarding interests and nurturing innovation. By conducting in-depth analysis global approaches, including variations across jurisdictions pivotal roles governmental bodies, this study explores measures aimed at fortifying protection. These encompass spectrum strategies, ranging from stringent disclosure requirements robust privacy safeguards implementation anti-money laundering (AML) know your customer (KYC) protocols. Furthermore, examines mechanisms for resolving complaints ensuring accountability within sector. Moreover, investigates various avenues innovation framework, such as establishment sandboxes promotion collaborative endeavors authorities industry stakeholders. Through examination pertinent case studies, highlights both successful interventions challenges encountered in regulating innovations. insights culminate series actionable recommendations tailored policymakers, navigating evolving landscape regulation. Additionally, offers projections future trends regulation, thereby equipping policymakers necessary foresight adapt dynamic nature ecosystem. Keywords: Financial Law, Policy, Frameworks, Fintech Innovations, Consumer Protection, Fostering Innovation.

Language: Английский

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DEVELOPING INTERNATIONAL POLICY GUIDELINES FOR MANAGING CROSS-BORDER INSOLVENCIES IN THE DIGITAL ECONOMY

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(4), P. 1034 - 1048

Published: April 7, 2024

The rapid growth of the digital economy has transformed global commerce, introducing new complexities and challenges, particularly in realm cross-border insolvencies. As businesses increasingly operate across national boundaries rely on assets data, traditional bankruptcy laws struggle to effectively address intricacies This review outlines need for developing international policy guidelines manage insolvencies economy. Cross-border present unique including jurisdictional conflicts, treatment coordination among diverse stakeholders. Existing legal frameworks, while providing some guidance, are often inadequate addressing these complexities. Thus, there is a pressing harmonized facilitate efficient fair resolution proposed aim achieve several objectives. Firstly, they advocate harmonization regulations jurisdictions provide clarity consistency insolvency proceedings. Secondly, call establishment framework recognizing enforcing foreign proceedings, ensuring equitable creditors Additionally, emphasize protection appropriate reflecting their growing importance economy. Implementation strategies include capacity building professionals, mechanisms dispute coordination, ongoing monitoring evaluation effectiveness. Case studies best practices will be utilized illustrate successful resolutions economy, offering valuable insights development replication. In conclusion, managing crucial promoting economic stability, facilitating safeguarding interests stakeholders an interconnected world. Keywords: Bankruptcy, Law, International Policy Guidelines, Cross-Border, Insolvencies, Digital Economy.

Language: Английский

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LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(3), P. 707 - 721

Published: March 16, 2024

The integration of artificial intelligence (AI) technologies into supply chain management has emerged as a crucial avenue for enhancing efficiency, agility, and responsiveness in modern business operations. This comprehensive review synthesizes current practices future potentials leveraging AI optimization. Beginning with an overview traditional challenges, the elucidates how solutions address these complexities by enabling predictive analytics, real-time visibility, intelligent decision-making. delves diverse applications across different stages chain, including demand forecasting, inventory management, logistics optimization, supplier relationship management. Examples AI-driven such machine learning, natural language processing, robotic process automation are analyzed their role revolutionizing Furthermore, highlights transformative impact on resilience, emphasizing its ability to mitigate disruptions, adapt dynamic market conditions, optimize resource allocation. also addresses critical considerations data privacy, ethical implications, organizational readiness adoption within contexts. Lastly, discusses research directions potential advancements AI-enabled envisioning autonomous chains characterized self-learning systems, collaborative ecosystems, enhanced sustainability practices. In conclusion, this underscores pivotal driving continuous innovation competitive advantage networks, while importance strategic planning responsible implementation harness full potential. Keywords: AI, Supply Chain, Optimization, Practices, Review.

Language: Английский

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THE ROLE OF PREDICTIVE ANALYTICS IN OPTIMIZING SUPPLY CHAIN RESILIENCE: A REVIEW OF TECHNIQUES AND CASE STUDIES

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(3), P. 815 - 837

Published: March 23, 2024

This study investigates the transformative impact of predictive analytics on enhancing supply chain resilience (SCR). Employing a systematic literature review and content analysis, research aims to explore integration, challenges, strategic implications within ecosystem. Focusing from 2014 2023, synthesizes insights peer-reviewed articles conference papers, adhering stringent inclusion exclusion criteria ensure relevance recency. The findings reveal that significantly contributes agility, flexibility, responsiveness, thereby bolstering SCR against disruptions. Key challenges identified include data privacy concerns, need for skilled personnel, integration into existing frameworks. Despite these future outlook in SCM is promising, with potential unprecedented efficiency, sustainability, competitive advantage. Strategic recommendations practitioners emphasize importance developing capabilities, prioritizing governance, continuous staff training. For policymakers, suggests standards regulations encourage innovation while ensuring ethical use analytics. Finally, pivotal revolutionizing SCM, offering pathways innovation, enhanced resilience. Future should focus emerging technologies, frameworks, overcoming adoption barriers, particularly SMEs economies. underscores critical role driving forward agenda practice this evolving field. Keywords: Predictive Analytics, Supply Chain Resilience, Systematic Literature Review, Implications.

Language: Английский

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Multifaceted anomaly detection framework for leachate monitoring in landfills

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 368, P. 122130 - 122130

Published: Aug. 24, 2024

Language: Английский

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Exploring financing models for clean energy adoption: Lessons from the United States and Nigeria

Global Journal of Engineering and Technology Advances, Journal Year: 2024, Volume and Issue: 19(2), P. 154 - 168

Published: May 29, 2024

This paper examines financing models for clean energy adoption, drawing insights from experiences in the United States and Nigeria. It underscores significance of need to explore effective mechanisms facilitate its widespread adoption. Through an analysis current state adoption both countries, existing initiatives challenges are outlined. Lessons gleaned successful States, including government incentives, public-private partnerships, renewable credits, then explored. These lessons serve as a foundation assessing how similar approaches can be adapted Nigerian context. Specific attention is given unique facing Nigeria, such infrastructure limitations socioeconomic disparities, tailored address these obstacles. A comparative between two countries identifies similarities, differences, potential transferability models. Based on insights, recommendations proposed emphasizing importance context-specific accelerate Overall, this provides comprehensive exploration offering valuable policymakers, stakeholders, practitioners

Language: Английский

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Addressing environmental justice in clean energy policy: Comparative case studies from the United States and Nigeria

Global Journal of Engineering and Technology Advances, Journal Year: 2024, Volume and Issue: 19(2), P. 169 - 184

Published: May 29, 2024

This paper explores the intersection of environmental justice and clean energy policy through a comparative analysis case studies from United States Nigeria. Environmental justice, defined as fair treatment meaningful involvement all people in decisions, is increasingly recognized critical aspect transitioning to systems. By examining policies initiatives both countries, this study aims identify successes, challenges, lessons learned addressing considerations. In States, focuses on federal state-level policies, assessing their impact marginalized communities efforts promote equity access resources. Similarly, Nigeria, attention given government-led implications for particularly rural underserved areas. Through lens, highlight’s common themes divergent approaches between two countries. It identifies opportunities cross-country collaboration knowledge sharing advance equitable sustainable transitions globally. The findings underscore importance integrating principles into development implementation, with recommendations provided policymakers stakeholders inclusivity, fairness, community engagement shaping future energy.

Language: Английский

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AI-DRIVEN ENVIRONMENTAL HEALTH DISEASE MODELING: A REVIEW OF TECHNIQUES AND THEIR IMPACT ON PUBLIC HEALTH IN THE USA AND AFRICAN CONTEXTS

International Medical Science Research Journal, Journal Year: 2024, Volume and Issue: 4(1), P. 51 - 73

Published: Jan. 23, 2024

This scholarly paper embarks on an exploratory journey into the realm of AI-driven environmental health disease modeling, with a keen focus its implications in diverse healthcare landscapes USA and Africa. The study's background delves historical evolution modeling techniques, emphasizing revolutionary role AI modern public strategies. It meticulously examines comparative effectiveness models these distinct regions, addressing challenges opportunities inherent models. Aiming to unravel multifaceted impact prediction policy, navigates through various thematic corridors. critically analyzes significance data sources quality, ethical considerations integration policies. scope encompasses comprehensive review AI's efficacy predicting diseases, enhancing surveillance systems, geographic socioeconomic variations affecting model accuracy. main findings reveal that models, while effective surveillance, encounter related integrity complexities. study concludes necessitates balanced approach, advocating for policies support development context-specific address concerns. Recommendations include fostering interdisciplinary collaboration continuous evaluation align them evolving needs standards. serves as beacon understanding transformative potential offering insights are crucial shaping future strategies interventions. Keywords: Healthcare, Disease Modeling, Public Health Policy, Data Quality, Ethical Considerations, Geographic Variations.

Language: Английский

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