2 publications

• Published Subscription 15 Jul 2026

  Optimizing Enterprise Financial Risk Management: An Advanced Ensemble Machine Learning Framework for Transactional Fraud Mitigation and Business Continuity

  By Shipra Aggarwal, Manish Aggarwal

  Abstract: Transactional fraud represents a critical threat to enterprise risk management (ERM) and corporate governance, draining billions annually from global financial infrastructures. The Nasdaq Global Financial Crime Report estimates total fraud losses at $485.6 billion annually, with credit card fraud alone accounting for $28.6 billion. Managing this operational vulnerability is severely challenged by data asset asymmetry, where legitimate transactions dwarf fraudulent anomalies by a ratio exceeding 500:1. Standard classification models trained …

  Published in NOLEGEIN Journal of Business Risk management · Vol. 9, Issue 2, 2026 Read article →

• Published Subscription 12 Jun 2026

  The Intelligent Frontier: Orchestrating AI and Machine Learning for Advanced Financial Fraud Detection

  By Shipra Aggarwal

  Abstract: 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 …

  Published in NOLEGEIN Journal of Leadership and Strategic Management · Vol. 9, Issue 2, 2026 · pp. 30–37 Read article →