This study, titled "Predictive Analytics for Loan Default Risk Assessment in Commercial Banks," evaluates the predictive accuracy, loan portfolio risk composition, Non-Performing Asset (NPA) reduction trends, and financial feasibility of advanced machine learning risk scoring engines in commercial banking. Commercial banks face significant credit risk exposure, with unsecured personal loans representing 40% and MSME business loans accounting for 30% of portfolio volume. A five-year project lifecycle (2021-2025) of an ensemble predictive analytics platform is evaluated using standard capital budgeting parameters: Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP), and Benefit-Cost Ratio (BCR). Quantitative analysis indicates that deploying ensemble neural network classifiers raises default risk ROC-AUC scores to 0.96 compared to 0.72 under traditional logistic regression models. Higher predictive precision improves default detection accuracy from 68.5% to 96.2%, reducing annual credit loss costs from 480 Crores to 65 Crores and lowering Gross NPAs to 320 Crores while achieving an 89.5% Provision Coverage Ratio (PCR) by 2025. The financial model yields a positive NPV of 284.5 Crores and an IRR of 38.6%, far exceeding the 10% discount hurdle rate. The study concludes that investing in predictive credit risk analytics is highly viable, providing commercial banks with enhanced asset quality, lower provisioning overhead, and improved capital adequacy.
Pamarthi Sai, M. Prasad, B. Vijay· American Journal of AI Cyber...· 0 citations
Blockchain technology has emerged as a transformative innovation in the energy sector by enabling secure, transparent, and decentralized management of energy operations and financial transactions. This study, titled "Blockchain Applications in Energy Trading and Financial Transactions at Tata Power," examines the potential of blockchain technology in improving operational efficiency, enhancing transaction security, and promoting trust among stakeholders within Tata Powers energy ecosystem. The research focuses on how blockchain facilitates peer-to-peer energy trading, automates financial settlements through smart contracts, minimizes fraud, and ensures data integrity across distributed networks. The study adopts a descriptive research approach using secondary data collected from journals, industry reports, company publications, and other credible sources related to blockchain technology and the energy sector. It analyzes the impact of blockchain on transaction transparency, cost reduction, settlement speed, cybersecurity, and customer satisfaction. The research also explores the challenges associated with blockchain implementation, including regulatory compliance, scalability, infrastructure investment, and integration with existing power systems. The findings indicate that blockchain has the potential to revolutionize energy trading by enabling real-time, secure, and tamper-proof financial transactions while reducing dependence on intermediaries. For Tata Power, blockchain can support decentralized renewable energy markets, improve billing accuracy, streamline payment processing, and enhance customer confidence through transparent transaction records. Furthermore, the integration of blockchain with smart grids and renewable energy sources contributes to improved energy management and sustainable business practices. The study concludes that blockchain technology represents a strategic opportunity for Tata Power to strengthen its digital transformation initiatives and build a more efficient, secure, and customer-centric energy ecosystem. Although implementation challenges remain, continued technological advancements and supportive regulatory frameworks are expected to accelerate blockchain adoption in Indias power sector, paving the way for a more transparent and resilient energy market. Keywords: Blockchain Technology, Energy Trading, Financial Transactions, Tata Power, Smart Contracts, Distributed Ledger Technology (DLT), Decentralized Energy Systems.
Rohith Satya Phanikumar, Amita Johar, B. Vijay· International Journal of Eng...· 0 citations
Blockchain technology has emerged as a transformative innovation that is reshaping financial systems by improving transparency, security, and accountability. This study examines the role of blockchain technology in enhancing financial transparency at Deloitte, with a focus on its applications in financial reporting, auditing, transaction verification, and regulatory compliance. The research explores how blockchain's decentralized and immutable ledger system reduces the risk of fraud, minimizes human errors, and enables real-time monitoring of financial transactions. A quantitative research approach is adopted using structured questionnaires to collect data from employees and professionals familiar with blockchainenabled financial processes. The collected data are analyzed using descriptive statistics and graphical representations to evaluate the effectiveness of blockchain in promoting transparent financial operations. The findings indicate that blockchain technology significantly improves data integrity, audit efficiency, transaction traceability, and stakeholder confidence while reducing operational costs and reconciliation efforts. However, challenges such as implementation costs, scalability issues, regulatory uncertainty, and the need for skilled professionals continue to influence its adoption. The study concludes that blockchain has substantial potential to strengthen financial transparency within organizations such as Deloitte by creating a secure, reliable, and tamper-resistant financial ecosystem. The research also provides recommendations for organizations seeking to integrate blockchain into their financial management and governance practices.
Saba Fatima, A. K. Reddy, B. Vijay· American Journal of Manageme...· 0 citations
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