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 been looking at new technologies, especially AI, to increase efficiency, enable improved and faster decision-making, and better serve clients. As noted in our Evolving Front Office Support Models member survey, close to 60% of respondents stated they were changing their front office support model to drive or support innovation. Innovation is not just the ability to use AI; it’s also using AI to become more efficient, create analytics and insights, and give employees the ability to create their own insights on self-service platforms. Innovation is using technology to scale and easily adapt to investments in new asset classes and products. Firms looking to innovate and use technology in this way must first ensure that the data that underpins those use cases is high quality, complete, and accessible. Firms cannot put technology to work without first concentrating on their data.
AI and analytics have become increasingly essential in the investment decision-making process ─ and having quality accessible data is an essential baseline requirement. With the volume and complexity of data continuing to increase, firms have looked to build Modern Data Platforms (MDPs) using cloud-native tools to better manage all kinds of data. The illustration shows the layers and numerous tools that can make up an MDP. Architecting a new data platform is a big undertaking, involving multiple vendors and technologies. To build an MDP, firms have integrated third-party tools for data ingestion, transformation, and prep, selecting and supporting tools for AI, data science, analytics, and reporting ─ plus data quality, observability, and security. Until recently, few vendors offered the various layers under one umbrella ─ and fewer still provided an industry-specific platform and services. While many large investment managers have successfully built an MDP and are reaping the benefits, it requires significant resources, configuration, integration, and vendor management.
Many vendors providing legacy Enterprise Data Management (EDM) tools specializing in investment management have been slow to modernize and build cloud-native platforms. These EDMs remain key components of firms’ data management and data quality control measures, but their legacy technology is often a roadblock to innovation. However, these vendors have recently invested in new technologies to create more flexible and complete data platforms designed to support innovation through faster and easier data ingestion and distribution, and integration of tools for analytics and AI use cases.
What’s new for investment managers is that with the modernized platforms that these vendors are bringing to market, along with some newcomers with native-cloud offerings, they have new options for managed MDPs. These vended platforms come equipped with modern pipelines to common market data providers and custodians, tools for data observability, customizable prebuilt data models, and prebuilt reports and dashboards. Vendors offer managed services and managed data services with expertise in investment management. Yes, these platforms still require customization and configuration, but they have a baseline configuration that helps firms accelerate their implementation, and vendors offer industry expertise and managed services for platform implementation and maintenance. In 2025, we expect these new industry-specific data platforms will make the shortlist of investment managers looking for modern technology and improved data platforms to support innovation without the need to build and maintain it themselves.