Insider Threats and Identity-Based Cyberattacks in Financial Services: Detection, Prevention, and Governance

Abstract

Financial services firms work in a high-trust, high-value environment where legitimate access is indispensable and, at the same time, inherently risky. Insider threats and identity-based cyberattacks converge at that point of dependence. Attackers, negligent users, and malicious insiders can all operate through accounts, credentials, sessions, devices, privileges, and workflows that appear legitimate until behavior, context, or intent shifts. Across the peer-reviewed literature, insider-threat research has moved away from static rule sets toward behavioral modeling, anomaly detection, user and entity behavior analytics, explainable artificial intelligence, and continuous authentication, while identity-management research has produced taxonomies of attacks targeting digital identities, identity providers, authentication protocols, and authorization processes (Homoliak et al., 2019; Pöhn & Hommel, 2023). In financial services, digital banking, FinTech platforms, payment systems, regulatory obligations, third-party integrations, and the centrality of customer trust intensify the stakes (Javaheri et al., 2023; Cele & Kwenda, 2024). This article brings those strands together to examine detection, prevention, and governance. Its argument is that financial institutions are better served by an identity-centered governance model that combines least privilege, zero trust, behavioral analytics, risk-adaptive access control, cyberfraud controls, privacy-aware monitoring, and board-level accountability. Technical detection matters, but by itself it is not enough. Institutions also need governance structures that tie identity lifecycle management to behavioral risk signals, incident response, regulatory compliance, human factors, and ethical oversight.