OVERCOMING RECENCY BIAS AND RISK AVERSION IN SIP INVESTORS USING AI TOOLS IN INDIA

Systematic Investment Plans (SIPs) are the foundation of retail investment in Indian mutual funds. Despite the
benefits of rupee cost averaging and automated investment discipline, Systematic Investment Plans (SIPs) are
frequently paused or discontinued during periods of market volatility. This behavior is largely driven by
behavioral biases, particularly recency bias and heightened risk aversion, which led investors to overreact shortterm market downturns. This study has two primary objectives: (1) to investigate how Indian retail SIP investors
exhibit recency bias and risk-averse behavior during volatile market conditions, and (2) to evaluate the potential
of AI-based advisory solutions in mitigating these biases and promoting sustained investment discipline. This
study investigates how recency bias and risk aversion manifest in Indian Systematic Investment Plan (SIP)
investors and evaluates the effectiveness of AI-based advisory interventions (nudges, personalization, and
simulations) in reducing these behavioral biases. Using survey data (N=300), the study employed reliability
analysis, ANOVA, and regression models to examine five hypotheses. Results indicate that recency bias and risk
aversion significantly undermine SIP adherence and portfolio diversification, respectively. AI interventions
successfully reduced these biases and enhanced trust in advisory platforms, ultimately improving adherence.
Findings provide evidence for the role of AI tools in strengthening investor resilience in volatile markets.