Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Crime, Illicit Activities, and Governance
Abstract
The field of financial crime compliance is undergoing rapid transformation driven by increasingly stringent global regulations, technological advancement, and the growing sophistication of criminal methodologies. Traditional financial crime compliance frameworks have relied predominantly on reactive measures such as suspicious activity reporting and retrospective audits. This study examines the global shift from reactive to proactive financial crime compliance using a mixed-methods approach, combining a quantitative survey of 100 compliance professionals from financial institutions across North America, Europe, Asia-Pacific, and the Middle East with qualitative in-depth interviews of 10 senior compliance executives. Findings reveal significant regional variation in the adoption of proactive tools including predictive analytics and behavioural monitoring, with Asia-Pacific leading adoption and the Middle East showing the lowest uptake. Real-time transaction monitoring is deployed by 78% of surveyed institutions, while only 37% use graph analytics. The study proposes a proactive quadrant framework for financial crime compliance and identifies key barriers to transformation including legacy infrastructure, regulatory uncertainty around AI explainability, skill gaps, and organisational cultural resistance. The paper calls for closer collaboration between financial institutions and regulators to enable the transition from reactive reporting to proactive risk management.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.