Behavioral Shift: Rethinking The “Insider”
- IJLLR Journal
- 2 hours ago
- 2 min read
Shalini Saxena, PhD Scholar at Sushant University, Gurgaon
Dr. Divya Sharma, Assistant Professor, School of Law, Sushant University
Dr Treena, Assistant Professor, School of Law, G.D Goenka University
ABSTRACT
The concept of insider trading is based on white-collar crime which was initially based on access to privileged and precise information and positions of trust within various companies and organisations. The rapid spread of digital invention in Fintech industry in India and globally consists of behavioral shifts in rethinking capacity of an individual. This paper shall focus on legal and compliance framework including Securities Exchange Board of India (SEBI) insider trading probes, banking frauds and examination of frameworks under SEBI (Prohibition of Insider Trading) Regulations 2015 (as amended), Companies Act 2013, Prevention of Money Laundering Act (PMLA) 2002, and Reserve Bank of India (RBI) guidelines on white-collar crimes and Fintech industry, exploring behavioral aspects and dynamics of same based on technological affordances, psychological pressures, organizational cultures, and economic incentives.
Two prominent frameworks of Edwin Sutherland and Petter Gottschalk, explain how social learning, organizational environments, and perceived opportunities contribute to white-collar criminal behavior. When complemented by insights from behavioral economics, particularly prospect theory and its application to high-status offenders, these frameworks move beyond narrow legal and regulatory definitions of insider misconduct to provide a more comprehensive behavioral understanding of why insiders engage in financial crime. Fintech industry involves not only the employees or companies but also involves algorithmic systems, third-party vendors, and hybrid human-AI entities exploiting unpublished price-sensitive information (UPSI), data asymmetries, and regulatory arbitrage.
This paper has focused on jurisdictional challenges in domestic as well as cross-border financial services industry. Further, it will reveal outdated notions being followed and attempt to show how these can be remedied or updated, based on automated trading.
The paper has also focused on algorithmic trading, data usage and misuse, identity fraud and lastly paper has made recommendations on or for behavioral risk management, AI driven detection, protection for whistleblower, legislative reforms and gaps, corporate criminal liability. This behavioral rethinking is aimed to bridge compliance gap(s), enhance deterrence, and foster ethical innovation in India’s fintech ecosystem, contributing to broader economic integrity.
