AI is Here to Stay! Here Is How It’s Revolutionizing Financial Markets
This article was originally published in Traders Magazine on May 19, 2025. With Johnna Powell, Managing Director and Head of Technology, Research and Innovation at DTCC
What is the current industry sentiment on AI?
In financial services, the sentiment around AI is largely positive due to the benefits that this technology can deliver, such as improvements in productivity and efficiency as well as the ability to automate processes. Within our firm, one of the most promising and exciting AI applications we’ve seen to date is our product development lifecycle, where AI has helped us to increase our internal developer coding throughput by 40%.
Read DTCC CEO’s perspective on AI, blockchain and effective modernization.
How can firms successfully integrate AI into their organizations?
When organizations integrate AI into their operations, it is critical that they incorporate it with the same steadfast focus on risk management while ensuring a robust data structure and data governance. As a first step, organizations should develop and implement a strategic AI framework that addresses several key areas including: risk management, data governance, integration requirements, continuous monitoring and human oversight of models, processes and workflows to address potential bias and ensure appropriate data protection. At the same time, the framework must acknowledge training and upskilling needs as firms implement AI into their workflows, including engineers, product leaders, risk professionals and more.
What other emerging AI-driven innovations are having an impact?
AI frameworks, like Agentic frameworks, are becoming very popular now, but haven’t fully been proven in highly regulated environments. This type of framework leverages Large Language Models (LLMs) where you can essentially connect them — or chain the models together — to ultimately complete what human tasks are now. For example, consider a forthcoming regulatory change that may have just been announced. An LLM could scan news coverage leveraging APIs and other data, pick up on that regulatory announcement and automatically send an email to the regulatory team so they’re aware of the changes. Then, an AI agent could act autonomously, recommending changes to be considered to achieve specific goals. In this case, the AI agent would proactively recommend updates to policies and procedures to achieve compliance, that the regulatory team could assess and, if appropriate, implement.
How is AI mitigating risks?
There are many ways that AI can improve risk monitoring and mitigation. In an increasingly complex and interconnected business environment, there is significant importance in developing comprehensive vendor risk profiles. AI presents a unique opportunity to help with these risk assessments. For example, many companies have hundreds, if not thousands, of vendors that they work with. The use of agentic frameworks with AI-driven models and LLMs could be leveraged to profile these vendors, introducing a risk monitoring system for each touchpoint as well as informing organizations of critical or regulatory changes, resulting in timesaving and increased risk management capabilities. Furthermore, AI-driven predictive analytics can empower organizations to anticipate potential risks based on historical trends, facilitating more proactive mitigation strategies.
How does AI impact operational resilience?
AI brings both challenges and advantages to operational resilience. On one hand, AI risks such as model bias, reliance on algorithms and potential vulnerabilities to cyber-attacks must be carefully reviewed and addressed. For example, AI algorithms can be tricked or exploited to malfunction, leading to potential cybersecurity incidents or biased outcomes. These are considerations that need to be analyzed and solved for. However, AI also has the potential to significantly improve risk mitigation and operational resilience by enabling faster incident detection and response, automating routine processes and offering predictive analysis insights that help organizations drive improvements in risk monitoring, detection and response.
What’s the best path forward for AI in financial services?
DTCC recognizes the vast potential for AI to not only transform our organization — with new capabilities, insights and more — but also the whole financial ecosystem. For AI to thrive across a critical sector like financial services, we must prioritize balancing risk management and innovation. AI must be implemented prudently and responsibly. Once that is ensured, the sky is the limit — its potential to deliver real-time insights, predictive analytics and automated processes will empower us to better serve our clients, better navigate the complexities of the financial landscape and create an even safer financial ecosystem.
