Papers by Aisha A H M A D Ishaq

Credit Risk Management beyond Compliance: A Strategic framework for enhancing financial performance in regulated environment , 2025
In the contemporary financial landscape, credit risk management (CRM) has emerged as a critical c... more In the contemporary financial landscape, credit risk management (CRM) has emerged as a critical component of regulatory compliance and operational stability. However, conventional approaches continue to treat CRM primarily as a compliance-oriented function, often marginalizing its strategic potential. This conceptual study challenges that paradigm by proposing a reframing of CRM as a dynamic capability that can drive sustainable financial performance in regulated environments. Drawing on the resource-based view (RBV) and dynamic capabilities theory, the study presents an integrative framework that positions CRM not merely as a defensive tool but as a proactive enabler of strategic advantage. Practical, regulatory, and academic implications are discussed, offering guidance for financial institutions, policymakers, and scholars. By bridging the gap between risk governance and strategic management, this study contributes to a deeper understanding of how CRM can evolve into a performance-enhancing capability within financial institutions.

Journal of Technology Innovations and Energy, 2023
Within this compendium, an exhaustive examination is undertaken to scrutinize the intricate amalg... more Within this compendium, an exhaustive examination is undertaken to scrutinize the intricate amalgamation of artificial intelligence (AI) and machine learning (ML) techniques within the paradigm of real-time energy demand response and load management. Placing paramount importance on the pervasive significance of AI and ML, this research expounds upon their profound capabilities to adroitly harmonize the delicate interplay between supply and demand, meticulously calibrate the multifarious dimensions of grid stability, and optimize the boundless potential inherent in renewable energy resources. An indepth analysis ensues, encompassing the deployment of AI algorithms, poised at the vanguard of demand response optimization, and the judicious utilization of ML techniques, flawlessly calibrated to deliver unerring accuracy across varying temporal scales in the realm of load forecasting. Furthermore, the seamless integration of AI into the very fabric of intelligent appliances and Internet of Things (IoT)-enabled systems unfolds, illuminating the path towards energy consumption optimization, ascertaining an intricate tapestry of interconnected devices, and engendering an ecosystem of intelligent load management. Notably, this comprehensive exposition delves into the far-reaching implications for optimal load management and resource allocation, magnifying the transformative potential that AI-driven algorithms hold in precisely balancing energy utilization and deftly managing the intricate interdependencies that permeate load distribution. Through meticulous elucidation, this illuminating manuscript emboldens the reader with insights into the progressive advancements and myriad benefits that the tandem of AI and ML confers upon the dynamic energy sector, charting an unyielding course towards unprecedented resilience and sustainable utilization of our cherished renewable energy resources.
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Papers by Aisha A H M A D Ishaq