As financial institutions expand into new sectors, they often face a surge in sanctions and transaction monitoring alerts. This complexity overwhelms traditional labor-intensive methods, and the slow shift to automation exacerbates scalability and cost challenges amid digital transformation, regulatory shifts, and cybersecurity threats. The solution lies in embracing innovative artificial intelligence (AI) solutions, which transform compliance into a proactive, intelligence-driven process, enhancing efficiency and effectiveness. In this follow-up to our exploration of AI's impact on financial crime prevention, we examine how AI is reshaping transaction monitoring, what that means for the future of compliance and how tools like Ankura's new AI Analyst are transforming the industry.
Principles for Responsible AI Integration
By automating tasks such as alert triage, transactional analysis, extraction of relevant information from third-party reports, and even certain aspects of quality control, AI can enable compliance teams to focus on high-value activities such as strategic decision-making, policy refinement, and emerging threat analysis. But as institutions contemplate AI adoption, several guiding principles should shape their strategy and approach:
- Compliance and Ethics: Ensure adherence to regulations and ethical standards.
- Data Quality: Provide accurate, high-quality data for reliable AI performance.
- Risk Management: Enhance human oversight with AI, but do not replace it.
- Transparency: Build systems with explainable outputs for easy understanding.
- Scalability: Choose solutions that can grow and adapt with changing needs.
- Continuous Improvement: Regularly evaluate and refine AI processes.
- Human Oversight: Keep humans involved to validate AI decisions.
- Training: Educate staff on AI tools to ensure effective use.
- Privacy and Security: Safeguard sensitive data with strong security measures.
- Stakeholder Engagement: Collaborate across teams for aligned adoption.
These technologies are relatively new and often lack extensive validation and review by regulators, making them less seasoned compared to established methods. As a result, starting with a proof of concept is essential. This allows organizations to thoroughly test AI capabilities, assess effectiveness, and ensure alignment with regulatory standards and specific organizational needs before full-scale deployment.
Efficiency Gains with Measurable Impact — Introducing Ankura's AI Analyst
Ankura's AI Analyst tool is designed with these principles in mind and can revolutionize how institutions manage anti-money laundering (AML) operations. AI Analyst leverages agentic AI and can be customized to meet an organization's unique needs. It utilizes securely implemented large language models (LLMs) and generates tailored outputs that align with an institution's specific policies, procedures, and risk assessments, ensuring precise and effective compliance solutions. AI Analyst integrates seamlessly into existing systems, adapting effortlessly to institutional processes while ensuring human oversight remains central to compliance operations and organizational goals. Its AI technology provides Bank Secrecy Act (BSA) officers with the precision needed to combat financial crime even amid evolving regulatory demands to enable institutions to maintain sharp and effective compliance.
Ankura's AI Analyst tool distinguishes itself through its use of both generative and agentic AI to automate alert disposition and transactional analysis. This advanced approach significantly reduces investigation and disposition generation times, with proof of concepts showing savings of 50 to 80% in labor costs. As a result, financial institutions can streamline their compliance operations, enabling them to focus on strategic decision-making and high-value projects.
Bridging the Gap for Mid-Tier Institutions
Mid-tier banks face distinct challenges in adopting AI, often hindered by legacy infrastructure and regulatory concerns. According to American Banker, 98% of financial institutions encounter difficulties in AI adoption, with 40% citing outdated infrastructure as a barrier and 38% highlighting regulatory issues. Additionally, 38% struggle to demonstrate return on investment (ROI), and 37% lack the skilled personnel to develop AI in-house.1
Despite these obstacles, mid-tier banks can effectively embrace AI with the right support. At Ankura, we recognize these hurdles and offer tailored solutions to assist both large and mid-sized banks. Our scalable and flexible AI solutions are crafted to help institutions navigate AI complexities, enhancing customer experiences and compliance operations without becoming overwhelmed.
The Road Ahead
Tools like Ankura's AI Analyst illustrate the importance of aligning technology with institutional goals, enhancing rather than replacing human expertise. As the regulatory landscape evolves, the integration of AI tools such as Ankura's AI Analyst will become a defining factor in organizational resilience and regulatory agility.
AI is no longer a future consideration — it is a present necessity for compliance and transaction monitoring. Institutions that thoughtfully embrace this shift will be better positioned to navigate regulatory complexities, manage operational risks, and allocate resources effectively.
Ankura is ready to guide institutions in this transition, and our AI Analyst tool can help to transform compliance strategies and turn challenges into opportunities, securing a strong position in financial crime prevention.
Footnote
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
