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
Matt Mueller
Research Analyst
Matt Mueller brings more than eight years of experience in the financial services industry to his Research Analyst role at Cutter Associates. Prior to joining Cutter in 2022, Matt was an investment performance associate at Cambridge Associates before moving onto an investment operations role at 1919 Investment Counsel, an RIA headquartered in Baltimore, Maryland. At 1919 Matt was involved in every aspect of the back office, from trade support to Security Master to compliance. Most recently, Matt served as a research analyst at the financial publication Angels & Entrepreneurs, which specializes in early-stage companies raising money via Equity Crowdfunding Platforms. Matt was responsible for sourcing the deals, and evaluating the product, market, and investment viability of each company. Matt earned his bachelor’s degree in economics with a minor in business from Gettysburg College.
Two key trends have emerged in recent years in managing reference data: the rising cost of market data and increasing pressure to integrate ESG factors into investment decision-making.
Market data, which not only includes ESG factors, but also security, market index, and economic indicator data, represents a significant cost for asset managers. As a result, managers want to optimize their use of data and reduce expenses.
At the same time, ESG has become a top priority for many investors, and asset managers are increasingly integrating ESG factors into their investment process. In a September 2022 Cutter Research Member Survey, more than a third of members stated they plan to extend the use of their reference data management solutions (RDMS) to manage ESG data.
In this article, we provide a preview of Cutter’s research on RDMS and explore how these solutions are expanding their functionality to offer tools to help asset managers control market data costs and manage ESG data.
Controlling Market Data Costs
Firms use various systems and processes, such as spreadsheets, databases, document management systems, and third-party market data administration tools, to track data consumption and market data costs. RDMS vendors realize that the functionality they provide for collecting, validating, storing, and distributing data can also help investment managers monitor their spending on market data. Because RDM solutions acquire data from vendors and distribute it to downstream systems, these solutions can track which data fields are requested and who requests them, when and how frequently. The solutions can also track where data is distributed from the RDMS. One trend we noticed was that RDMS vendors are creating standard functionality to help investment managers monitor and control market data costs. Until recently, investment managers had to perform their own analysis of this information to uncover opportunities to reduce consumption, discover unnecessary data requests, and track where data is acquired but never used.
The RDMS vendors we evaluate in our upcoming Reference Data Management Solutions research have different approaches to monitoring market data costs. What follows are some examples of functionality that RDMS vendors have added to help firms control market data costs.
- Offering white-label integration with a reference data usage management software solution such as XMON. The product helps prevent duplicate vendor requests, estimates vendor costs, and analyzes where costs are incurred and the cost differences between bills and internal estimates.
- Supporting capabilities to establish rules-based warnings and system-side limitations on market data requests. Supporting approvals around whether the RDMS will request data from the data provider based on the data already existing, limits on the number of items that can be requested, and thresholds established by the firm.
- Linking reports and dashboards to rate cards from vendors to track market data usage, including frequency, contents, and number of items per request, in addition to allowing firms to estimate market data costs in real-time.
- Creating reports and dashboards that monitor data distribution and track usage by consumer or consuming system to the individual field level.
Although the examples above represent only a portion of the data optimization features that RDMS vendors now provide to help firms control their market data costs, we expect more vendors to offer these value-added features as enhancements in their coming releases.
Managing Your Firm’s ESG Data
In recent years, the popularity of ESG investing has increased among asset managers. Despite the growth, ESG data remains fragmented, with firms struggling not only with the cost of the data, but also data quality and the lack of adequate data coverage at the required level of granularity for pillar, framework, and security. Several RDMS providers have created new ESG modules or enhanced the base product to support ESG data management.
- While nearly all RDM solutions provide a means to ingest ESG data, the number of providers and frameworks supported by a particular RDMS differs dramatically and is evolving as vendors develop more interfaces, and as datasets and requirements for ESG data change. Given the size and complexity of ESG datasets, some vendors have done a better job than others in providing intuitive tools for clients to build their own interfaces to ingest data from new providers.
- Differences exist among RDM solutions ─ for example, whether the raw data is stored, out-of-the-box normalization processes are provided, and if the solution supports time-series format of stored ESG data.
- Some RDM solutions allow firms to assign rules-based confidences levels to ESG data, but not all products offer this feature.
- Most systems provide functionality to map ESG data to the appropriate issuer.
- Some products provide reporting, dashboards, and visualization to view ESG exposures at the issuer, portfolio, or any other aggregated level across investments. However, most vendors leave this functionality to the downstream systems that consume the data.
- The vendors with the most complete solutions have often separated the ESG data management capabilities into individual optional modules.
Investment managers and RDMS vendors both have different opinions on how RDMS should support ESG data management, and these opinions and the capabilities offered are rapidly changing and evolving.
Capabilities to track market data costs and manage ESG data are just two of the new features offered by RDMS vendors. In our upcoming research, Reference Data Management Solutions, we provide more insights into how Cutter Research members manage reference data and evaluate some of today’s RDM solutions.