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
Laura Jesson
Director, Research
Laura Jesson has more than 25 years of experience in the financial services industry as a project manager, business analyst, and consultant. She joined Cutter Associates in 2013. Prior to Cutter, Laura spent eight years at Wells Capital Management and Evergreen Investments, where she managed investment operations projects, including those focused on outsourcing, client reporting, and trade management. She previously worked at Omgeo as a member of the Central Trade Manager (CTM) product design team. Laura started her career at Andersen Consulting (now Accenture) as a process consultant supporting a variety of projects for clients in the financial services industry. Laura earned her bachelor of arts in economics and psychology from Amherst College. She holds the Project Manager Professional (PMP) certification.
Recent research assignments and publications include the following:
- AI Use Cases in Investment Management: Infinite Possibilities
- Business Intelligence Tools
- Cutter Benchmarking: Client Reporting
- Cutter Benchmarking: Firmwide ESG Capabilities
- Cutter Benchmarking: Managing Vendors and Service Providers
- DataOps: In Theory and Practice
- Enabling Data Analytics
- ESG Data Management
- ESG: It’s a Jungle Out There ─ A Look at the Data Provider Landscape
- ESG Investing: One Vision, Many Lenses
- Execution Management Systems
- Hybrid Work Arrangements and Their Impact on Firm Culture
- Using RPA to Automate Business Processes
- The Role of the CRM for Asset Managers
When we talk about all the parties involved in the various aspects of vendor management, the list can grow long.
When we talk about all the parties involved in the various aspects of vendor management, the list can grow long: project managers, procurement experts, legal experts, finance representatives, risk management, compliance officers, and, of course, the vendor relationship owners themselves. What we never talk about is the important role that data scientists can play, but we think there is an opportunity to involve them in the future.
Vendor risk management is exhausting, because of the sheer volume of available data for analysis and the organization’s obligation to report a complete, accurate, and timely risk register. Firms request service organization controls (SOC) reports, due diligence questionnaires (DDQs), and other content-rich materials from their vendors, all of which require scrutiny. The most difficult aspect is reading the tea leaves within the data. Could we apply artificial intelligence (AI) techniques such as natural language processing (NLP) to analyze responses?
Purely quantitative risk data is readily available to monitor vendor location risk, cybersecurity risk, financial risk, and ESG risks. Investment managers can consume this information to red flag changes and escalate new areas of risk to explore. And this is already happening ─ institutions and vendor management solutions are integrating and analyzing data supplied by vendors such as Dow Jones, RapidRatings, and SecurityScorecard. But rather than simple rules to detect changes, can we probe deeper and make predictions?
Applying AI and data science techniques to structured and unstructured data is exactly what quants in the front office excel at. The methodologies that quants use to find alpha with hypothesis setting and testing could be employed to assess and predict vendor risk. We believe that there’s an untapped opportunity to put data science skills, alternative data, and sophisticated technologies together to evaluate current risk and to predict future risk.
Is this too far-fetched? It probably is today, because the scarce data science skills are focused on investment opportunities, and vendor management doesn’t yet afford the same ROI justification. However, we do not think it’s out of the realm of possibility that data analytics methodologies will soon be implemented in the vitally important area of a firm’s vendor risk management efforts.
Laura Jesson, a Senior Research Analyst at Cutter, has more than 20 years of experience in the financial services industry as a project manager, business analyst, and consultant.
At our upcoming member meetings, Advance Together, in June, we’ll examine current industry trends related to vendor management, including best practices and the types of tools, data, and services members use to perform vendor/provider due diligence and ongoing oversight. Choose the meeting location above that works best for you and register now.