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Identity Theft – The Root Cause of Widespread Fraudulent Activities
Get PDFIn recent years, identity theft has emerged as a critical issue, with top government officials and industry experts identifying it as the root cause of a wide range of fraudulent activities, including cyber fraud, money laundering, and financial scams. In its Financial Trend Analysis (FTA), the Financial Crimes Enforcement Network (FinCEN) reviewed identity-related suspicious activity reported under the Bank Secrecy Act (BSA) for the year 2021. The analysis revealed that approximately 1.6 million reports—representing 42% of all reports filed that year—were linked to identity-related suspicious activity. These reports accounted for a significant $212 billion in suspicious activity, highlighting the large-scale impact of identity theft.
Identity theft involves stealing personal information—such as Social Security numbers, credit card details, and online credentials—to commit fraud. Criminals use these stolen identities to open fraudulent bank accounts, file false tax returns, or even launder money. These schemes ripple through the economy, affecting individuals, businesses, and governments
Income Smoothing and Its Impact on Shareholder Wealth Creation: Evidence from Firms in the Nigerian Financial Services Sector
Get PDFUnderstanding how income smoothing influences shareholder wealth is critical in the evolving dynamics of Nigeria’s financial sector. This study examines the relationship between income smoothing and shareholder wealth creation in Zenith Bank Plc, a leading financial institution in Nigeria, over the period 2002 to 2024. The aim is to evaluate how Return On Equity (ROE), Dividend Per Share (DPS), and Return On Assets (ROA) Affect Earnings Per Share (EPS), a key proxy for shareholder wealth. An ex-post facto research design was employed, using secondary data sourced from Zenith Bank’s financial reports. Analytical techniques included trend analysis, SWOT, PESTEL, and regression analysis, carried out with the EViews software. The regression results revealed that ROA and ROE had positive coefficients, while DPS had a negative coefficient; however, none of the independent variables were statistically significant (ROA: p=0.2852, ROE: p = 0.9225, DPS: p = 0.5613). The overall model was not significant (p = 0.149), indicating that income smoothing did not have a statistically confirmed impact on shareholder wealth during the period under review. The study is limited by its focus on a single institution, which may affect the generalizability of the findings. Future research should consider a comparative analysis across multiple banks or financial institutions, both locally and internationally. In conclusion, while income smoothing did not significantly influence shareholder wealth statistically, the strategic management of income trends, asset utilization, and dividend policy remains essential for long-term value creation in the banking sector
Linking Compensation Packages to Operational Performance: Evidence from the Consumer Goods Sector (2002-2024)
Get PDFUnderstanding the link between compensation structures and operational performance is crucial in Nigeria’s evolving consumer goods sector. This study investigates the impact of directors’ remuneration, salaries, wages and allowances, and employee benefits on operational performance measured by Return on Assets (ROA). Using an ex post factor research design, the study analyzed secondary data from audited financial statements of Nestlé Nigeria Plc, CBN Statistical Bulletin and World Bank Open Data spanning 2002 to 2024. Analytical techniques included multiple regression via E-Views, descriptive statistics, autoregressive (AR) terms, the Breusch-Godfrey Serial Correlation LM Test, heteroskedasticity, normality tests, Q-statistic probabilities adjusted for one ARMA term, and strategic tools such as SWOT and PESTEL analysis. The regression results indicate that none of the compensation components, directors’ remuneration (p=0.1066), salaries/wages/allowances (p=0.3812), or employee benefits (p=0.9938) had statistically significant effects on ROA. Among macroeconomic variables, only exchange rate had a significant negative influence (p=0.0023), while inflation (p=0.6637) and GDP growth (p=0.6005) were not significant. Despite this, the overall model was statistically significant (F statistic = 14.71, p < 0.001), explaining approximately 88% of the variation in ROA (R² = 0.88). The study’s limitation to a single firm, Nestlé Nigeria Plc may affect the generalizability of findings across the sector. However, the findings emphasize the need for performance-based compensation strategies, proactive foreign exchange risk management, and the use of macroeconomic indicators as planning tools rather than direct performance levers
Investigation into Online Banking and its Prevailing Fraud Factors: A Comprehensive Analysis
Get PDFThis study explores the investigation of security concerns surrounding online banking, the prevailing fraud factors that affect banks and customers and discusses effective measures towards preventing fraudulent activities using combination of authentication and verification methods. Employing a qualitative research approach, data was collected through online interviews during the pandemic lockdown and restrictions. Findings reveal that while online banking has transformed financial transactions by offering unprecedented convenience and efficiency, it has simultaneously exposed both banks and customers to significant fraud risks. The study discusses user perceptions of online security, the impact of fraud on reputation and customer trust and recommends integrated fraud detection, prevention, and resolution measures. These insights provide a critical contribution to the ongoing development of robust online banking security protocols. The study further discusses preventative measures that aid fraud mitigation and prevention in online banking
Ethical Dilemmas and Philosophical Insights in the Clinical Applications of Large Language Models
Get PDFLarge Language Models have started to become an integral part of clinical solutions. From disease diagnosis to medical report analysis, generative models have been creating significant impact. In this work, we analyze ethical dilemmas present in such situations and the philosophical underpinnings of those dilemmas. We also touch upon a few solutions to those dilemmas from philosophical as well as engineering point of view
Assessing the Impact of Academic Stress on Tension-Type Headache Among Medical Students: Triggers, Remedies and Frequency
Get PDFTension-Type Headaches (TTH) are common neurological disorders having a significant impact on lifestyle and academic performance of medical students. The purpose of our study is to assess self-reported triggers and relieving interventions of headaches among medical students. Additionally, it evaluates the frequency and severity of headaches and investigates the relationship between medical students’ academic stress levels and TTH. A quantitative, cross-sectional study was conducted from June to November 2024. Probability stratified sampling was employed to gather data online using a previously validated questionnaire which was ethically reviewed by ERC FUMC. Participants in this study included both genders and the age group (>17). Descriptive (frequency, mean, range, variance, SD) and Inferential statistics tests (chi square) were analysed using IBM SPSS26. The sample consisted of medical students [n=201] between the ages of 18 and 24y [ Mean=21y SD ± 3.33]. A total of n=125 [62.2%] females and n=76[37.8%] males participated in this study. Among them, n=144 [71.6%] people reported experiencing headaches at least twice in the preceding trimester. The two most common triggering factors were emotional discomfort n=133 [68.7%] and sleep deprivation n=167 [83.6%]. Paracetamol was the most often used analgesic n=139 [69.5%]. The chi-square test showed that TTH was significantly associated with gender with females reporting a higher incidence (n=98 (48.75%), p=0.006). It was also significantly associated with academic stress (n=125 (62.18%), p=0.000). Tension-type headaches were reported by more than two-thirds of the sample and show a strong significant relationship with sleep deprivation
The Enduring Value of Case Reports in Modern Radiology
Get PDFRadiology case reports continue to play a vital role in advancing clinical insight, diagnostic vigilance and patient safety. By highlighting uncommon presentations, unexpected complications and real-world decision-making, case reports preserve lessons that cannot always be captured in large trials or guidelines. This editorial reflects on the enduring educational and clinical value of case-based scholarship across diagnostic and interventional radiology
Optimizing LDPC and BCH Forward Error Correction for Improved Reliability and Reduced Bit Errors in Low-SNR DVB-T2 Transmission Environments
Get PDFDigital Video Broadcasting-Terrestrial second generation (DVB-T2) systems are increasingly deployed for high quality terrestrial broadcasting. However, low Signal-to-Noise Ratio (SNR) conditions in urban and fringe coverage areas pose significant challenges, resulting in elevated Bit Error Rates (BER) and degraded service reliability. Forward Error Correction (FEC) techniques, particularly Low-Density Parity-Check (LDPC) and Bose Chaudhuri Hocquenghem (BCH) codes, play a crucial role in mitigating transmission errors and ensuring robust communication. This study investigates a systematic approach to optimizing LDPC and BCH FEC schemes to enhance transmission reliability and minimize BER under low-SNR conditions in DVB-T2 networks. Using simulation-based analyses, the study evaluates multiple LDPC code rates (e.g., 1/2, 2/3, 3/4) in combination with BCH codeword lengths and error-correcting capabilities. Results indicate that an optimized LDPC (64800, 32400) configuration combined with a BCH (255, 239) code significantly reduces BER, achieving approximately 10⁻⁵ at an SNR of 2 dB, compared to a BER of 10⁻³ using standard DVB-T2 FEC configurations. Additionally, iterative decoding algorithms for LDPC were fine-tuned to balance convergence speed and error correction performance, demonstrating a 25% reduction in decoding iterations without compromising reliability. The analysis also explores trade-offs between redundancy, throughput and latency, highlighting the practical considerations for real-world deployment. The findings underscore that strategic optimization of LDPC/BCH FEC parameters is critical for maintaining broadcast quality in low-SNR scenarios. By enhancing error resilience and reducing BER, the proposed approach improves signal integrity, supports consistent reception in fringe areas and maximizes spectrum efficiency. This work provides a foundation for adaptive FEC strategies in future DVB T2 systems, enabling broadcasters to deliver reliable high-definition content even under challenging channel conditions
From Reactive BI to Agentic AI: The Rise of Domain Specific Autonomous Insight Systems in Enterprise Analytics
Get PDFEnterprises need descriptive and diagnostic insight engines that think ahead of users, not after them. This paper presents a research framework for agentic analytics that unifies four ideas into a single, verifiable system. First, ontology aligned grounding maps business language to concrete data assets and permitted joins. Second, a scaffolded tool layer executes plans safely across query engines, catalogs, code runners, and visualization services while exposing traces for audit. Third, a multi-turn hypothesis engine treats explanations as first-class objects that are generated, tested against data, revised, and ranked. Fourth, a dual judge mechanism fuses an LLM critic with a gold data layer that serves as the final arbiter of numerical claims and structural correctness. We specify rubric signals for each stage and show how those signals become rewards for reinforcement learning of both single agents and coordinated teams. The result is a pathway from natural language intent to governed, reproducible descriptive analytics that improve over time
Value Chain Inefficiencies in India’s Power Sector: A Systems Dynamics Perspective
Get PDFIndia's power sector remains burdened by persistent inefficiencies stemming from systemic feedback structures rather than isolated operational failures. This study applies an integrated systems dynamics methodology combining causal loop diagrams, stock-and-flow modeling and scenario simulation to diagnose structural inefficiencies across the sector’s value chain. The model, calibrated with secondary data from government and institutional sources (CEA, CERC, World Bank, NREL), incorporates four interconnected subsystems (generation, transmission, distribution and end-use) and simulates outcomes over a 20-year horizon using a one-year time step and euler integration. Our analysis identifies four dominant reinforcing cycles: the DISCOM debt vicious cycle, agricultural subsidy spiral, renewable integration dilemma and efficiency paradox. Policy scenarios were simulated and validated against historical trends in AT and C losses and debt accumulation. Results indicate that isolated interventions yield limited gains, whereas integrated policy packages such as combining direct benefit transfers with water governance reforms, pairing renewable targets with strategic storage deployment and implementing performance-based regulation with institutional capacity building deliver significantly higher improvements in financial sustainability, grid reliability and renewable integration. Leverage-point analysis, adapted from meadows framework, reveals that high-impact interventions lie in redesigning incentive structures, improving information transparency and shifting sector goals from electricity supply to service quality and economic productivity. This study provides a holistic, systems-based assessment of India’s power sector challenges and offers actionable, sequenced pathways to support the country’s clean-energy transition and long-term sectoral resilience