Uses of AI and Machine Learning in Financial Fraud Detection

Manish Aggarwal Related Seminars and Products

Senior Developer / Engineer

Aspen Technology

Manish Aggarwal is a Senior Developer / Engineer at Aspen Technology with over 15 years of experience spanning process design, software development, and applied research. He holds a Master’s in Chemical Engineering from Carnegie Mellon University, where his work focused on data science, machine learning, and advanced modeling. Manish has applied AI/ML techniques in supply chain optimization, economic evaluation engines, and anomaly detection frameworks. A Senior Member of AIChE and editorial advisor for Chemical Engineering Progress, he actively contributes to the advancement of engineering and analytics. His expertise lies in integrating AI and machine learning to improve decision-making, detect anomalies, and enhance efficiency across industries, including finance and chemical engineering.

Shipra Aggarwal Related Seminars and Products

Director of Finance

Pelmeds

Shipra Aggarwal is the Director of Finance at Pelmeds in Waltham, Massachusetts, where she oversees financial strategy, budgeting, and compliance across business operations. She holds a Master’s in Finance from Babson College’s F.W. Olin Graduate School of Business, where her research and projects focused on financial modeling, macroeconomic forecasting, and risk analysis.

With over a decade of experience spanning corporate finance, FP&A, and accounting, Shipra has led financial operations for organizations in both the U.S. and India, driving measurable improvements in reporting accuracy, profitability, and audit compliance. Her technical proficiency includes tools such as Bloomberg, FactSet, Power BI, SQL, and Python.

Shipra’s expertise bridges financial management and data analytics, providing valuable insights into economic behavior, fraud detection, and business decision-making—complementing the application of AI and machine learning in finance and risk analysis.