Advanced data analytics in internal audits: A conceptual framework for comprehensive risk assessment and fraud detection

Finance & Accounting Research Journal, Journal Year: 2024, Volume and Issue: 6(6), P. 931 - 952

Published: June 13, 2024

In the face of increasing complexity and rapid technological advancements, traditional internal audit methods are becoming inadequate for comprehensive risk assessment effective fraud detection. Advanced data analytics offers a transformative approach that enhances effectiveness audits. This concept paper presents framework integrating advanced into processes, aiming to provide more robust management improved detection capabilities. Integrate diverse sources, including financial, operational, external data, holistic view organization's landscape. Implement rigorous governance practices ensure accuracy, consistency, reliability. Use machine learning algorithms predictive identify patterns, predict future risks, detect anomalies. Employ real-time continuous monitoring, enabling timely response emerging threats. Develop adaptive models can evolve with changing business environments risks. Utilize data-driven insights prioritize risks based on their potential impact likelihood. Deploy uncover complex schemes might miss. Conduct scenario-based analysis patterns strengthen preventive measures. focus efforts high-risk areas, enhancing efficiency Incorporate procedures execution, reducing manual precision. provides deeper insights, proactive management. Real-time significantly enhance ability prevent fraud, mitigating financial reputational damage. Data-driven processes streamline activities, allowing auditors high-value tasks overall cycle time. Analytics accurate supporting better decision-making in prevention. Secure commitment from senior support integration Establish oversee implementation alignment organizational objectives. Invest platforms tools processing analysis. Ensure security measures protect sensitive information. Train professionals techniques tools, fostering culture innovation. pilot projects test refine framework, using lessons learned scale up across organization. Integrating audits significant benefits, enhanced management, detection, increased efficiency. By adopting this conceptual organizations assets, compliance, maintain stakeholder confidence an increasingly digital environment. The auditing is data-driven, must embrace transformation remain competitive secure. Keywords: Fraud Detection, Risk Assessment, Internal Audits, Data Analytics, Conceptual Frameworks.

Language: Английский

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Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(6), P. 1982 - 1996

Published: June 24, 2024

In the context of escalating environmental concerns and transition towards a greener economy, sustainable energy investments have emerged as pivotal area for financial growth innovation. This paper outlines strategic framework decision-making in investments, emphasizing transformative role big data. By integrating data analytics into investment process, stakeholders can enhance market analysis, risk assessment, performance monitoring, predictive modeling, leading to more informed effective strategies. The delves various sources, analytical tools, technologies that facilitate collection, processing, interpretation vast amounts information. Additionally, it presents case studies illustrating successful applications solar wind projects, highlighting best practices common challenges. discussion extends future trends, including advancements artificial intelligence machine learning, which are poised further revolutionize sector. concludes with recommendations developing data-driven approach, building robust infrastructures, fostering culture continuous learning adaptation. leveraging data, investors maximize impact their drive growth, contribute global transition. Keywords: Sustainable Energy Investments, Big Data Analytics, Strategic Financial Decision-Making, Market Analysis, Risk Assessment, Predictive Modeling.

Language: Английский

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Developing scalable data solutions for small and medium enterprises: Challenges and best practices

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(6), P. 1910 - 1935

Published: June 13, 2024

The rapid digital transformation sweeping across various industries has underscored the critical importance of data solutions for small and medium enterprises (SMEs). Developing scalable SMEs presents a unique set challenges requires adopting best practices tailored to their specific needs constraints. This review outlines aspects creating infrastructures SMEs, focusing on involved. Scalability in refers ability system handle growing amounts an increasing number users without compromising performance. For are vital as they provide flexibility expand operations adapt market changes efficiently. primary components such include storage, processing, analytics, security. Each component must be designed accommodate growth, ensuring remains efficient cost-effective business scales. face several developing solutions. Limited financial resources often restrict invest advanced technologies hire skilled personnel. Additionally, many lack in-house expertise required implement maintain complex systems. Data integration poses another significant challenge, particularly when dealing with disparate sources legacy Security compliance also present considerable hurdles, ensure meet regulatory standards extensive budgets or dedicated teams. Furthermore, scalability involves performance trade-offs, carefully balance cost, efficiency, future growth potential. Lastly, risk vendor lock-in can limit increase long-term costs, making it crucial choose technology partners wisely. To address these challenges, adopt practices. Conducting thorough assessment is essential align goals identify most requirements. Choosing right stack evaluating benefits cloud-based versus on-premises deciding between open-source proprietary software based budget Implementing robust management strategies, including governance quality management, ensures reliability integrity data. Effective techniques seamless accurate analytics. Leveraging cloud services advantageous offering infrastructure lower upfront costs. Selecting suitable service provider clear migration strategy significantly enhance flexibility. Ensuring security paramount; should strong measures, adhere requirements, conduct regular audits. Building team, either by investing training existing staff collaborating external experts, successful implementation Creating data-driven culture within organization drive better decision-making foster innovation. Monitoring optimizing solution continuously that meets evolving business. Utilizing analytics bottlenecks areas improvement help efficiency effectiveness. stay informed about trends solutions, artificial intelligence, machine learning, edge computing, multi-cloud remain competitive prepared growth. While enable them overcome obstacles harness power sustainable advantage. approach not only addresses current operational but positions demands technological advancements. Keywords: Scalable, Solution, Small Medium, Enterprise.

Language: Английский

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Driving energy transition through financial innovation: The critical role of Big Data and ESG metrics

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 1434 - 1452

Published: June 14, 2024

Driving the transition to sustainable energy is a critical global imperative, and financial innovation plays pivotal role in accelerating this process. This paper examines intersection of innovation, big data, Environmental, Social, Governance (ESG) metrics advancing transition. By harnessing power data integrating ESG considerations into investment decisions, institutions can drive meaningful change towards more future. The begins by exploring concept transition, highlighting its importance, drivers, challenges. It then delves discussing examples opportunities it presents for driving Subsequently, significance understanding consumption patterns optimizing efficiency, along with influencing decisions corporate behavior. emphasized, focus on their synergistic potential investments informing decision-making processes. Case studies are presented illustrate successful applications sector. Finally, discusses challenges future directions, including regulatory considerations, technological advancements, collaboration. concludes underscoring importance continued calls collective action Keywords: Energy Transition, Financial Innovation, Big Data, Metrics, Sustainability, Investment Decisions, Sustainable Energy, Renewable Climate Change

Language: Английский

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A comprehensive review of it governance: effective implementation of COBIT and ITIL frameworks in financial institutions

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 1391 - 1407

Published: June 14, 2024

In the rapidly evolving landscape of financial institutions, robust IT governance is essential to ensure that information technology supports business goals, mitigates risks, and complies with regulatory requirements. This comprehensive review examines effective implementation two prominent frameworks, COBIT (Control Objectives for Information Related Technologies) ITIL (Information Technology Infrastructure Library), within institutions. The highlights unique features, advantages, challenges associated each framework, provides insights into their synergistic application optimizing governance. a framework focuses on management enterprise IT, providing structured approach aligning strategy, managing risk, ensuring compliance. ITIL, other hand, set detailed practices service (ITSM) delivering value customers improving quality. While offers high-level model, guidance processes. integration frameworks holistic governance, combining COBIT’s strategic oversight ITIL’s operational focus. synergy enhances ability institutions achieve excellence, compliance, alignment. Case studies from leading demonstrate how combined use has led improved risk management, delivery. also addresses encountered during these including organizational resistance, complexity integration, need continuous improvement. Strategies overcoming are discussed, emphasizing importance executive sponsorship, stakeholder engagement, tailored training programs. conclusion, this underscores critical role in strengthening By effectively implementing can enhance capabilities, drive efficiencies, compliance standards. findings provide valuable leaders practitioners seeking optimize support objectives organizations. paper, I examine significant impact integrating efficiency, draw case practical examples my extensive experience illustrate concepts. Keywords: Governance, Financial Institutions, COBIT, Effective Implementation.

Language: Английский

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Enhancing IT audit effectiveness with agile methodologies: A conceptual exploration

Engineering Science & Technology Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 1969 - 1994

Published: June 13, 2024

This concept paper examines the integration of Agile methodologies into IT audit processes to enhance effectiveness and efficiency. In today's dynamic rapidly evolving technological landscape, traditional approaches often struggle keep pace with speed complexity environments. methodologies, originating from software development, offer a flexible iterative framework that can revolutionize practices. The begins by highlighting limitations in addressing challenges posed modern systems. It then introduces principles practices, explaining how they be adapted applied within context audits. By embracing Agile, auditors shift rigid, linear iterative, collaborative promote adaptability, responsiveness, continuous improvement. Key components such as sprints, stand-up meetings, user stories, are explored audits, demonstrating streamline planning, execution, reporting. also discusses cultural required for successful adoption teams organizations, emphasizing importance communication, collaboration, mindset focused on delivering value. Through case studies real-world examples, illustrates tangible benefits applying These include increased coverage, faster identification risks issues, enhanced stakeholder engagement, improved alignment business objectives. Additionally, practices enable adapt changing priorities emerging more effectively, ensuring activities remain relevant impactful Despite its potential benefits, audits presents resistance, skill gaps, need organizational support buy-in. addresses these proposes strategies overcoming them, including training development initiatives, pilot projects. conclusion, advocates means effectiveness, value delivery. better meet demands digital driving improvement innovation processes. this paper, I analyze particularly Scrum, explore improve overall supported practical examples insights my professional experience. Keywords: Enhancing, IT, Audit Effectiveness, Methodologies, Conceptual Exploration.

Language: Английский

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Enhancing business intelligence in e-commerce: Utilizing advanced data integration for real-time insights

International Journal of Management & Entrepreneurship Research, Journal Year: 2024, Volume and Issue: 6(6), P. 1936 - 1953

Published: June 13, 2024

This paper explores how advanced data integration techniques and real-time insights can significantly enhance BI in the e-commerce sector. By leveraging methods such as ETL, ELT, virtualization, API integration, streaming businesses achieve a comprehensive, unified view of their data. The enables dynamic pricing, personalized customer experiences, efficient inventory management, proactive fraud detection, improved support. Despite challenges silos, quality issues, scalability, security, technical complexity, solutions like governance, cloud computing, analytics tools address these obstacles. Future trends, including artificial intelligence, machine learning, edge block chains, fabric, promise to further transform e-commerce. Ultimately, are essential for companies stay competitive, optimize operations, satisfaction. In fast-paced competitive world e-commerce, ability make quick, informed decisions is crucial success. Business Intelligence (BI) plays vital role by transforming vast amounts into actionable that drive strategic operational efficiency. chain, Case studies from leading illustrate practical benefits implementing techniques, showcasing significant improvements efficiency Keywords: Intelligence, E-commerce Analytics, Data Integration, Real-Time Insights.

Language: Английский

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Transforming business scalability and operational flexibility with advanced cloud computing technologies

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 1469 - 1487

Published: June 25, 2024

In the rapidly evolving landscape of digital transformation, cloud computing has emerged as a pivotal technology enabling businesses to achieve unparalleled scalability and operational flexibility. This review explores transformative impact advanced technologies on business operations, highlighting key innovations their implications for organizational growth efficiency. Cloud offers dynamic scalable environment where resources can be provisioned managed on-demand, allowing respond swiftly changing market conditions customer demands. By leveraging infrastructure, companies scale operations seamlessly without need significant upfront investments in physical hardware. flexibility not only reduces capital expenditure but also enhances ability innovate adapt competitive marketplace. Advanced technologies, such multi-cloud hybrid solutions, further augment by organizations optimize IT environments. Multi-cloud strategies allow distribute workloads across multiple providers, mitigating risks associated with vendor lock-in ensuring high availability redundancy. Hybrid which integrate on-premises infrastructure public private clouds, provide balanced approach managing sensitive data while benefiting from cloud. Moreover, cloud-native like containerization serverless have revolutionized application development deployment. Containers encapsulate applications dependencies, consistency different environments facilitating rapid Serverless reviews underlying developers focus solely code, thus accelerating cycle reducing overhead. The integration analytics artificial intelligence (AI) capabilities. platforms offer robust tools AI services that process vast amounts real-time, providing actionable insights predictive decision-making. empowers improve experiences, drive strategic initiatives data-driven precision. conclusion, are instrumental transforming harnessing power cloud, greater agility, cost efficiency, innovation, positioning themselves sustained advantage age. As continue evolve, potential redefine economic value will expand, making adoption critical imperative modern enterprises. Keywords: Operational Flexibility, Transforming, Business Scalability, Advanced, Computing Technologies.

Language: Английский

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Predictive analytics for financial inclusion: Using machine learning to improve credit access for under banked populations

Computer Science & IT Research Journal, Journal Year: 2024, Volume and Issue: 5(6), P. 1358 - 1373

Published: June 7, 2024

This paper explores the application of predictive analytics and machine learning techniques to enhance credit assessment lending practices. By leveraging alternative data sources, such as mobile phone usage, social media activity, transactional records, models can provide more accurate risk evaluations for individuals with limited traditional financial histories. The study demonstrates efficacy these through empirical analysis, showcasing their potential reduce default rates while increasing approval applicants. Furthermore, discusses ethical considerations biases associated use non-traditional in scoring. findings underscore transformative impact fostering inclusion, offering practical insights policymakers, institutions, technology developers aiming bridge gap under banked communities. delves into enhancing inclusion by improving access populations. Traditional scoring methods often fail accurately assess creditworthiness lacking conventional histories, thereby excluding a significant portion population from services. incorporating sources interactions, utility payments, offer comprehensive precise evaluations. research methodology involves developing testing various algorithms, including decision trees, random forests, neural networks, predict creditworthiness. are trained validated on datasets that include both sources. performance is measured against standard metrics accuracy, precision, recall, area receiver operating characteristic (ROC) curve. Empirical results indicate utilizing significantly outperform methods, leading higher applicants maintaining or management standards. Keywords: Financial, Inclusion, Predictive, Analytics, Machine Learning, Alternative Data.

Language: Английский

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Exploring AI's Impact on Fintech and Financial Inclusion

Advances in finance, accounting, and economics book series, Journal Year: 2025, Volume and Issue: unknown, P. 133 - 152

Published: Jan. 8, 2025

This paper investigates how fintech and AI are interacting, especially in terms of improving financial inclusion. Examining elements such as effort expectancy, performance social influence, digital literacy, transformation sentiment analysis, behavioral intention, perceived risk, it explores the intricate relationship between AI, Fintech, inclusivity. We examine impact these factors on adoption intentions risk using a combination approaches, including surveys interviews. The study employs statistical techniques analysis algorithms regression broad sample size 212 people. results highlight importance like influence expectation, underscoring need for customized interventions to successfully promote adoption.

Language: Английский

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