Automation of Investor Risk Profiling and Portfolio Allocation Using Adaptive Hybrid Asset Allocation Model (Aham) – a Study at Iti Securities Broking Ltd., Coimbatore
The rapid evolution of financial technology has transformed investment advisory services, shifting from traditional manual practices to automated, data-driven frameworks. This study aims to design and demonstrate an automated investor risk profiling and portfolio allocation framework at ITI Securities Broking Ltd., Coimbatore, using the Adaptive Hybrid Asset Allocation Model (AHAM). The model integrates Modern Portfolio Theory (MPT), Strategic Asset Allocation (SAA), and Monte Carlo Simulation to balance risk and return for investors across three risk categories—Conservative, Moderate,and Aggressive. The research, based on secondary data and analytical simulations, enhances advisory efficiency, regulatory compliance, and scalability. Findings show that automation reduces human bias, standardizes advisory services, and improves investor experience, paving the way for future robo-advisory integration within mid-sized brokerage firms.