Research Article

Artificial Intelligence in Credit Risk Assessment and Credit Scoring: Evidence from the Indian Banking Sector

Amreen Taj

Authors Amreen Taj
Pages 1-11
Received 2026-07-21
Accepted 2026-07-27
Published 2026-08-11

Abstract

Purpose. This study examines the relationship between behavioural biases and investment decision-making among individual investors in Bengaluru, focusing on overconfidence, loss aversion, anchoring and herding. Design/methodology/approach. Primary data were collected from 155 individual investors using a structured questionnaire measured on a five-point Likert scale. Convenience sampling was used. Descriptive statistics, Pearson correlation and multiple linear regression were conducted using SPSS. Findings. Overconfidence and loss aversion show statistically significant positive relationships with investment decisions (r = 0.647 and r = 0.551, respectively; p < 0.001). Anchoring and herding show no statistically significant association. The regression model explains 68.3% of the variance in investment decisions (adjusted R² = 0.675). Overconfidence and loss aversion are significant predictors, while anchoring and herding are not. Originality/value. The study contributes location-specific evidence on behavioural finance among retail investors in Bengaluru. The findings have implications for investor education, financial advice and behavioural interventions aimed at reducing the adverse consequences of cognitive and emotional biases. Keywords: behavioural finance; overconfidence; loss aversion; anchoring; herding; investment decisions; individual investors; Bengaluru

Keywords: behavioural finance; overconfidence; loss aversion; anchoring; herding; investment decisions; individual investors; Bengaluru

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Purpose. This study examines the relationship between behavioural biases and investment decision-making among individual investors in Bengaluru, focusing on overconfidence, loss aversion, anchoring and herding.

Design/methodology/approach. Primary data were collected from 155 individual investors using a structured questionnaire measured on a five-point Likert scale. Convenience sampling was used. Descriptive statistics, Pearson correlation and multiple linear regression were conducted using SPSS.

Findings. Overconfidence and loss aversion show statistically significant positive relationships with investment decisions (r = 0.647 and r = 0.551, respectively; p < 0.001). Anchoring and herding show no statistically significant association. The regression model explains 68.3% of the variance in investment decisions (adjusted R² = 0.675). Overconfidence and loss aversion are significant predictors, while anchoring and herding are not.

Originality/value. The study contributes location-specific evidence on behavioural finance among retail investors in Bengaluru. The findings have implications for investor education, financial advice and behavioural interventions aimed at reducing the adverse consequences of cognitive and emotional biases.

Keywords: behavioural finance; overconfidence; loss aversion; anchoring; herding; investment decisions; individual investors; Bengaluru

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