AI in Behavioral Economics and Decision-Making Analysis

Artificial Intelligence (AI) have greatly transformed the science of Behavioural Economics and decision-making in applications predominantly on digital marketplaces, finance among others. Research examines the AI impact on consumer decision making, pricing and financial decision making with a specific emphasis on the Indian e-cockpit and fin-tech. By utilizing AI-driven recommendation systems, dynamic pricing models, and behavioral nudging techniques, businesses can enhance user engagement and optimize sales. The research examines Flipkart’s AI-powered recommendation system as a case study, revealing that AI-driven personalization has led to a 25% increase in sales and a 30% rise in user engagement. However algorithmic bias, data privacy and transparency ethical aspects are formidable challenges. Results show that AI tracking users with 58% of the user’s express worries about this algorithmic bias in financial decisions and access to loans/investment opportunities Even this study brings to light the requirements for human interpretability of AI models, stronger data privacy laws and ethically-grounded implementation of responsible AI. The next step for future research should be devising an explainable AI infrastructure that maintains technological advancement through fairness, transparency and user power.

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Publication Details

Journal
Journal for Research in Applied Sciences and Biotechnology
Published
2025-02-28
DOI
https://doi.org/10.55544/jrasb.4.1.15
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
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article

AI in Behavioral Economics and Decision-Making Analysis

Poonam Ajit Ghule
Journal for Research in Applied Sciences and Biotechnology
Stock Market Forecasting Methods
article

AI in Behavioral Economics and Decision-Making Analysis

Poonam Ajit Ghule
article en

Abstract

Artificial Intelligence (AI) have greatly transformed the science of Behavioural Economics and decision-making in applications predominantly on digital marketplaces, finance among others. Research examines the AI impact on consumer decision making, pricing and financial decision making with a specific emphasis on the Indian e-cockpit and fin-tech. By utilizing AI-driven recommendation systems, dynamic pricing models, and behavioral nudging techniques, businesses can enhance user engagement and optimize sales. The research examines Flipkart’s AI-powered recommendation system as a case study, revealing that AI-driven personalization has led to a 25% increase in sales and a 30% rise in user engagement. However algorithmic bias, data privacy and transparency ethical aspects are formidable challenges. Results show that AI tracking users with 58% of the user’s express worries about this algorithmic bias in financial decisions and access to loans/investment opportunities Even this study brings to light the requirements for human interpretability of AI models, stronger data privacy laws and ethically-grounded implementation of responsible AI. The next step for future research should be devising an explainable AI infrastructure that maintains technological advancement through fairness, transparency and user power.

Journal for Research in Applied Sciences and BiotechnologyVol. 4(1)
Symbiosis International University (IN)
Openalex Percentile: Top 96%
Stock Market Forecasting Methods
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