Kathy McDermott
Managing Director, Research
Kathy McDermott has more than 25 years of experience in the financial services industry. Kathy, who joined Cutter Associates in 2011, has authored multiple Cutter Research reports on a wide range of topics. She spent ten years as a consultant for a variety of asset management firms, with a focus on business analysis for front- and middle-office projects. Kathy was previously the senior business analyst, equity trading systems, at Wellington Management, specializing in the firm’s proprietary electronic and basket trading applications. Earlier in her career, Kathy worked for Thomson Financial Services (now Thomson Reuters), supporting FirstCall and PORTIA clients in Hong Kong, Japan, Singapore, and Thailand, and later went on to manage PORTIA implementations. She also worked at LongView (now Linedata) as an account manager and then product manager of electronic trading. Kathy earned her bachelor of arts in mathematics from Hamilton College.
Recent research assignments and publications include the following:
- Alternative Data and the Expanding Universe of Investment Information
- Cutter Benchmarking: Data Management
- Cutter Benchmarking: Market Data Administration
- DataOps: In Theory and Practice
- Enabling Data Analytics
- The Evolving Front Office Support Model
- Evolving Data Governance: Building a Data Culture
- Making Snowflake Part of Your Modern Data Platform
- Managed Data Services
- Market Data Administration
- Order Management Systems
- Outsourced Trading: Has the Time Come?
- Reference Data Management Solutions
Investment managers have always been concerned about data quality, but its profile has never been as visible as it is today. Like no other technology or initiative, AI has brought the need for high-quality data to the forefront as never before. This focus is driving firms to invest in foundational modern data platforms that provide consistent, accessible, and governed data.
Of surveyed firms …
67%
of firms plan on or are in the process of changing their data management solution.
and
20%
plan to migrate to a proprietary cloud solution.
Source: Cutter 2025 Data Management Benchmarking Survey
In fact, 67% of respondents to Cutter’s 2025 Data Management Benchmarking Survey indicated that they plan to or are in the process of changing their data management solution, and 20% plan to build a proprietary cloud solution. However, building a proprietary solution does not mean building every component.
Firms that are architecting their own data platform have several options for creating one, but the platform should be adaptable to new technologies and business requirements. It should be modular and loosely coupled so that different components can be swapped in and out as needs change.
Cutter’s Investment Data Platform (IDP) graphic illustrates the capabilities that comprise an IDP. An IDP is a comprehensive solution that encompasses cloud-native tools for ingesting, transforming, storing, querying, governing, and analyzing investment data at scale. A modern IDP can significantly reduce the time required to integrate data into an organization, support self-service analytics, and often leads to substantial improvements in data quality, response time, and performance. A data platform provides golden source data to downstream applications, including investment management systems, risk engines, compliance tools, and client reporting applications, as well as data science and AI models.
In Cutter’s 2025 data trend article, Modern Data Platforms: Firms Don’t Have to Do It on Their Own, we discussed the improvements in vended IDPs that allow firms to modernize their data infrastructure without the time, resources, and expertise required to build one themselves. We still believe this is an option for some firms, and we published research on Investment Data Platforms in 2025. But we also understand that no one-size-fits-all solution exists, and a vended IDP may not meet some firms’ requirements for flexibility and customization.
Architecting a new data platform is a huge undertaking that involves enabling data pipelines and observability, assessing data quality, providing data catalogs, orchestrating workflows, and more. But firms do not need to build all these capabilities on their own; they can, and do, buy best-of-breed solutions integrated into a loosely coupled architecture that allows them to build a solid foundation while leveraging new technologies as they become available. The goal is to design a data foundation that evolves as the organization does.
Build and Integrate
In 2026 and beyond, how firms architect a hybrid proprietary data solution will vary based on their requirements, priorities, and expertise, as well as their current systems, asset types, data governance framework, and data use cases. Firms may build a hybrid solution using a vended investment data platform as a foundation and customize from there by building proprietary solutions or integrating best-of-breed tools such as data catalogs or data observability tools. Other firms will build and fully customize a proprietary solution based on a technology data infrastructure, such as Snowflake or Databricks. Firms may also partner with managed service data providers or their custodian/service provider to ingest mastered data.
While vended IDP platforms and managed service providers cater to investment managers, most best-of-breed tools and technology infrastructure providers do not. One key is understanding how to adapt generic technologies and tools to investment data and a firm’s unique use cases. Answers vary across firms and may differ by asset type or data domain within the same firm.
We believe firms that intelligently leverage best-of-breed solutions, partner with managed data service providers, or use industry-specific platforms can improve their time-to-market and avoid reinventing solutions for commoditized functions and capabilities.
Modernizing legacy data management technology and architecture is an important first step toward proactively improving data quality, reducing silos, consolidating information, and making curated, golden source data more accessible. For firms that prioritize flexibility and customization and have the necessary resources and expertise, building a data platform can deliver a scalable, unified foundation of trusted data. Firms should focus on designing an adaptable data platform for long-term value. Leveraging best-of-breed tools can accelerate this journey, reduce complexity, and allow teams to focus on building firm-specific features rather than reinventing the wheel to support commoditized functions.
In 2026, we will publish research on Creating an Investment Data Platform. If you are interested or want to share insights on this topic, please reach out at [email protected].
The Cutter Consulting team has extensive experience in helping investment managers modernize their data platforms. To learn more or speak with a consultant, contact us at [email protected].