https://mbajournals.in/index.php/JoKSM <p><strong>NOLEGEIN- Journal of Leadership &amp; Strategic Management </strong>is a peer reviewed journal and provides a platform to discuss new issues in the area of Strategic Management process. The journal also seeks to advance the quality of research by publishing papers introducing or elaborating on Management decisions and Corporate strategy. It's a biannual journal, started in 2018. </p> MBA Journals (Consortium eLearning Network Pvt Ltd) en-US NOLEGEIN- Journal of Leadership & Strategic Management 2582-2888 https://mbajournals.in/index.php/JoKSM/article/view/1893 <p>Behavioral accounting has emerged as a crucial field in understanding financial decision-making by integrating cognitive psychology with traditional accounting principles. This study examines how behavioral accounting influences corporate strategies, with a particular focus on mitigating cognitive biases, improving investment decisions, and enhancing financial transparency. The research employs a systematic literature review and statistical correlation analysis of secondary data from 2020 to 2024. Key findings reveal a strong correlation (r = 0.997) between behavioral accounting adoption and improvements in financial decision-making, with a regression analysis indicating that every 1% increase in behavioral accounting adoption leads to a 0.20% improvement in decision efficiency (β = 0.197, R2 = 0.986, p &lt; 0.001). Companies that implemented behavioral insights experienced an 8% improvement in decision-making, a 3.5% increase in return on investment (ROI), and a 6% reduction in financial miscalculations. The study concludes that behavioral accounting significantly enhances corporate governance, risk assessment, and financial forecasting, reinforcing its importance in modern financial strategies. Recommendations include integrating behavioral analytics into corporate finance tools, increasing managerial awareness of cognitive biases, and aligning behavioral accounting practices with regulatory frameworks. These findings contribute to advancing behavioral finance theory and its practical applications in corporate decision-making.</p> Mbonigaba Celestin Shila Mishra Anjay Kumar Mishra Copyright (c) 2026 NOLEGEIN- Journal of Leadership & Strategic Management 2026-06-09 2026-06-09 9 2 https://mbajournals.in/index.php/JoKSM/article/view/1894 <p>Traditional rule-based systems cannot match that scale. They are too slow, too rigid, and too reactive. This paper examines how AI and ML are reshaping fraud detection. It evaluates LSTMs, GNNs, and Transformers as detection tools. Mastercard reported a 20% uplift in fraud detection rates. The paper also maps two emerging frontiers: Agentic AI and Quantum Graph Neural Networks. Strategic guidance is offered throughout CFOs and finance leaders. Global financial crime reached $4.4 trillion in 2025. Fraud networks now deploy AI against the very systems designed to stop them. Static detection methods are no longer adequate. This paper provides a structured evaluation of AI and machine learning architectures for financial fraud detection. Supervised models, including Random Forest and Logistic Regression, form the operational baseline. Deep learning architecture extends this capability significantly. Long Short-Term Memory networks capture sequential transaction patterns. Graph Neural Networks expose hidden criminal networks across accounts. Transformers apply self-attention to behavioural context across full transaction histories. Generative Adversarial Networks address the persistent class imbalance problem in training data. The paper introduces the DLSG framework as a governance blueprint. It integrates deep learning performance with sector-specific compliance requirements. GDPR and CCPA obligations are embedded at the design level. Case studies from Mastercard and Visa demonstrate real-world impact. Mastercard achieved a 20% uplift in detection rates. Visa processes risk scores in under one second per transaction. Ethical risks, including algorithmic bias and explainability gaps, are examined. SHAP-based tools and federated learning are presented as mitigations. Two frontier technologies conclude the analysis: Agentic AI and Quantum Graph Neural Networks. Both will redefine fraud defence within the decade. Strategic recommendations guide CFOs and management accountants toward governance-first AI adoption.</p> Shipra Aggarwal Copyright (c) 2026 NOLEGEIN- Journal of Leadership & Strategic Management 2026-06-12 2026-06-12 9 2 30 37 10.37591/njlsm.v9i2.1894