4 Publications
Publication Date: 6th January 2021
Journal Name: International Journal of Multidisciplinary Research and Growth Evaluation
Volume: 2
Issue: 1
Pages: 663-676
Description: The banking sector is undergoing a profound transformation fueled by digital technologies such as artificial intelligence (AI), blockchain, and automation. This shift presents both opportunities and challenges, particularly in workforce skills. As digital transformation accelerates, employees must adapt to changing roles and develop new competencies, making upskilling and reskilling essential for a future-ready workforce. This paper explores how digital transformation is reshaping workforce dynamics in banking. Technological advancements are redefining job functions, skill requirements, and organizational structures. Automation and AI are driving data-driven decision-making, reducing manual tasks, and increasing operational efficiency. However, implementing these technologies demands a workforce skilled in managing complex systems. In-demand skills will include digital literacy, data analytics, cybersecurity, and adaptability. Soft skills—such as creativity, problem-solving, and emotional intelligence—will also be increasingly important as employees collaborate with AI systems. The paper underscores the importance of continuous learning and the role of educational programs in preparing the workforce for ongoing change. Challenges include resistance to change, the need for strategic leadership, and addressing skill gaps. Case studies from leading financial institutions illustrate successful approaches, such as partnering with educational providers, internal training initiatives, and fostering agile work cultures. In conclusion, digital transformation is set to significantly alter the future of work in banking. Financial institutions must invest in ongoing upskilling and foster a culture of adaptability to remain competitive and innovative. By prioritizing continuous learning, banks can ensure a successful transition to the future of work.
Publication Date: 17th December 2021
Journal Name: Journal of Advanced Education and Sciences
Volume: 1
Issue: 2
Pages: 55-63
Description: Financial fraud poses a persistent threat to global economies, undermining the integrity and security of financial systems. Traditional detection and forensic auditing methods often struggle to keep up with increasingly sophisticated fraud schemes. This review examines how data-driven techniques can enhance fraud detection and forensic auditing, thereby strengthening financial integrity and security. By leveraging advanced technologies such as big data analytics, machine learning (ML), artificial intelligence (AI), blockchain, and robotic process automation (RPA), financial institutions can detect fraudulent activities in real time, improve predictive accuracy, and bolster risk assessment frameworks. Big data analytics processes large transaction volumes to uncover anomalies, while ML algorithms adapt to evolving fraud tactics. AI-powered natural language processing (NLP) aids forensic investigations by analyzing unstructured data—such as emails and contracts—for evidence of misconduct. Blockchain technology promotes transaction transparency, reducing risks like identity fraud and double spending. Network analysis further enhances the detection of fraudulent connections and collusive activities. Despite these advancements, challenges—including data privacy concerns, implementation costs, and the continuous evolution of fraud tactics—necessitate adaptive regulatory frameworks and ethical considerations. Successful case studies underscore the effectiveness of AI-driven models in fraud detection, highlighting the value of integrating data-driven methods into forensic auditing. This review emphasizes the need for financial institutions and regulators to adopt innovative, compliant fraud prevention strategies. Future research should prioritize scalable, interpretable AI models to better mitigate financial crime. Ultimately, combining advanced analytics with robust regulatory oversight will reinforce fraud prevention and help protect global financial systems from illicit activities.
Publication Date: 1st August 2022
Journal Name: Journal of Advance Multidisciplinary Research
Volume: 1
Issue: 2
Pages: 28-38
Description: In today’s globalized economy, multinational corporations (MNCs) face significant challenges in optimizing corporate tax strategies and transfer pricing policies amid evolving regulations. Effective tax planning is crucial for minimizing liabilities, enhancing cash flow, and maintaining competitive advantage. Transfer pricing, which governs transactions within corporate groups, directly influences taxable profits across jurisdictions. However, improper practices can result in regulatory scrutiny, tax disputes, and reputational risks. This review examines the strategic integration of tax optimization and transfer pricing, with a focus on data-driven decision-making and compliance with international standards such as the OECD’s Base Erosion and Profit Shifting (BEPS) framework. By leveraging advanced analytics, artificial intelligence, and real-time financial modeling, MNCs can increase transparency, align intercompany pricing with economic value creation, and mitigate double taxation risks. Key areas of focus include aligning transfer pricing with arm’s length principles, establishing tax-efficient structures, and managing jurisdictional regulatory differences. The study also reviews case studies of successful tax optimization strategies and outlines best practices for compliance and financial sustainability. Additional topics include increased scrutiny by tax authorities, the impact of digital taxation, and emerging global tax reforms. The findings highlight the importance of integrating robust compliance mechanisms with proactive, adaptive tax planning to balance profitability with regulatory obligations and foster long-term financial stability.
Publication Date: 6th January 2022
Journal Name: International Journal of Social Science Exceptional Research
Volume: 1
Issue: 1
Pages: 141 - 157
Description: Growing demands for financial transparency and regulatory compliance are driving the adoption of innovative technologies in financial reporting. This paper presents a conceptual framework for leveraging blockchain to enhance financial transparency, focusing on its transformative impact on accountability, accuracy, and compliance. Blockchain’s decentralized, immutable, and secure ledger addresses the limitations of traditional financial reporting by providing a tamper-proof environment for data management and transaction validation. The framework emphasizes real-time data sharing, automated compliance via smart contracts, and enhanced traceability of financial transactions, thereby reducing fraud, errors, and misreporting while bolstering stakeholder trust. Blockchain’s immutable records facilitate seamless audits and regulatory reviews, while interoperability with existing financial systems ensures integration without disrupting workflows. The study also examines tokenization for asset representation and reporting efficiency, along with strategies for scalable and efficient blockchain networks. Additionally, the role of artificial intelligence (AI) in analyzing blockchain data is explored, highlighting its potential to deliver actionable insights and support better decision-making. The paper critically analyzes challenges such as regulatory uncertainty, adoption barriers, and data privacy, offering solutions like industry standards, regulatory collaboration, and hybrid blockchain models to balance transparency and confidentiality. In conclusion, blockchain-enhanced financial transparency provides a robust foundation for transforming financial reporting and compliance. The study underscores the importance of cross-industry collaboration and strategic investment to fully realize blockchain’s potential in building a secure, transparent financial ecosystem.