Angela Centeno, CPA
Director, Research
Angela Centeno has more than 25 years of experience in financial services. Prior to joining Cutter in 2015, Angela worked for The Northern Trust Company in multiple roles including sourcing and procuring enterprise market data, investment operations outsourcing, and vendor and custodian relationships. She previously held senior positions in operations management, project management, data management, and solutions implementation. Angela earned a bachelor of science in accounting and a bachelor of science in business administration from the University of Kansas, as well as an MBA in finance from DePaul University. She is a registered CPA.
Recent research assignments and publications include the following:
- AI Use Cases in Investment Management: Infinite Possibilities
- Alternative Investments
- Client Reporting Systems
- Cutter Benchmarking: Alternative Investments
- Cutter Benchmarking: Derivatives and Collateral Management
- Cutter Benchmarking: Firmwide ESG Capabilities
- Derivatives and Collateral Management Solutions
- ESG Data Management
- ESG: It’s a Jungle Out There ─ A Look at the Data Provider Landscape
- ESG Investing: One Vision, Many Lenses
- Market Data Administration
- Private Debt
While Cutter’s 2024 research report on artificial intelligence centered on the infinite possibilities that AI has to offer, and how Cutter member firms were exploring use cases with this technology, 2025 finds firms wanting to capitalize on this momentum and add support for structure and governance.
But it's not that easy.
We’re sure you come across the same articles that we do ― asset managers and asset owners are all talking about AI, with many planted on one side or the other in terms of what AI can do for them. Some firms predict they will reap operational efficiency or savings through the use of AI (and some say they’ve already done so). Others express skepticism, and the conversations about the “hype” of AI versus the “reality” abound.
So Where Are We?
As requested by our members in our 2024 research, we provided examples of where a firm can apply AI. Many firms shared their visions of simplifying operations by automating manual and routine tasks, especially accessing data. Or promoting personalization in sales and marketing with tailored solutions for individual clients. In fact, as we were scoping our research just a short 12 months ago, we observed that exploration was primarily aligned functionally by business teams that had discretion to “poke around” and learn by talking with their peers and seeing what vendors were developing.
Fast forward to today, and we see more firms considering how to best structure their AI programs and policies and talking about the right operating models to support it. For example, an AI center of excellence (CoE) could help share knowledge, expose overlapping use cases, and shepherd transformation across the organization.
Enter AI GRC
With much at stake, asset managers and asset owners are taking a thoughtful approach to best implement AI in their shops. They are exploring their exposure to all different types of risks and concerns, such as quality, transparency, and security. Furthermore, as the regulatory landscape evolves to address the challenges and opportunities presented by AI, asset managers and asset owners will need to keep abreast of regulatory changes and ensure compliance with new requirements. While the EU passed the EU AI Act in May 2024, the regulatory field continues to unfold on a global scale.
Nonetheless, governance is increasingly top of mind as firms are considering the integration of more and more AI solutions into investment processes. Firms will need to establish appropriate organizational structures and robust frameworks to ensure accountability, ongoing oversight, and compliance with the unfolding regulatory requirements. NIST has developed an AI risk management framework, OCEG is adding AI GRC webinars to its GRC technology series, and Monitaur offers governance software that helps financial services, along with other regulated industries, build AI models.
Those firms that have been piloting AI use cases but have yet to implement the technology want to move onto the next step. We expect to see firms building support for AI based on good governance and risk frameworks in 2025 and beyond.