The Review of Law, International Politics and Economics A Unified Neural–Symbolic Compliance-Aware Framework for Real-Time Fraud Detection in Regulated Financial Systems
NEO-STREAM, a compliance-aware transformer-based framework for real-time fraud detection that employs micro-episode tokenization to capture short-term behavioral patterns without relying on long-term user histories, indicates that compliance-aware AI architectures can effectively bridge the gap between predictive performance and regulatory accountability in modern digital financial systems.
This paper offers a theoretically grounded analysis of the transformation of AML and KYC compliance through artificial intelligence (AI) and machine learning (ML) in digital payment ecosystems and draws on regulatory compliance theory, network theory and dynamic capabilities theory to contend that AI-enabled compliance...
Temitope Onibaniyi, Umar Lawal· Texila international journal...· 0 citations
The persistence of the tax gap illustrates the limitations of traditional compliance monitoring in the face of large-scale electronic filing, complex business structures, cross-jurisdictional activity and rapidly evolving fraud patterns. This study develops an analytics-based framework for fraud-risk detection and audi...
Izuchukwu Shedrack Ofoma· World Journal of Advanced Re...· 0 citations
This work provides a scalable framework for preventing fraud through cross-sectoral innovation, reconciling technological progress with ethical governance through cross-sectoral innovation and cross-cultural analyses of fraud mitigation.
Samuel F. Johnson-Rokosu· Journal of Accounting and Fi...· 0 citations
Machine-learning credit underwriting in the United States operates under three families of obligation that are not reducible to one another: a statutory prohibition on discrimination, a statutory duty to disclose the specific principal reasons for an adverse action, and prudential expectations for model risk management...
Hasibur Rahman, Sarder Abdulla Al Shiam, Md Sibbir Hossain· Journal of business and mana...· 0 citations
Purpose: Money laundering threatens financial systems, while rule-based monitoring suffers from high false-positive rates and limited ability to capture relational transaction patterns. This study proposes an explainable graph-based framework for anti-money laundering (AML) detection that jointly addresses predictive p...
Ali Shahbazi, Faraz Sasani, Arshia Hossein Zadeh et al.· 0 citations
Public expenditure systems are essential to state capacity and public trust but remain vulnerable to errors, weak competition, inflated contracts, collusive behavior, and other indicators of waste or potential fraud. Traditional oversight is often retrospective, manual, and limited by fragmented data and rigid rule-bas...
