Data-Driven Success: How Financial Firms are Harnessing External Data
Summary:
- Data Consumption is Increasing within Financial Services: Financial firms have seen a significant increase in data consumption driven by business complexity and technological advancements, with divisions independently managing their data strategies and a growing adoption of MDM technologies to unify data and create reliable golden records.
- More Data, New Challenges: Financial institutions face challenges in balancing desktop terminals with direct data feeds, managing switching costs between data providers, and integrating new technologies like cloud and AI amidst increasing data consumption.
- Unifying Disparate Data is Required to Maximize ROI: Financial firms face significant financial impacts from increased data consumption due to price hikes and specialized licenses, driving the need for effective monetization strategies and Master Data Management (MDM) to maximize ROI by unifying data, reducing reconciliation efforts, and enhancing operational efficiency.
In the rapidly evolving landscape of financial services, data consumption has become a critical factor for success. Financial institutions are increasingly relying on external data sources to drive their decision-making processes, enhance operational efficiencies, and stay competitive. This blog post explores the current trends in data consumption within the financial sector, based on insights from industry experts & Tamr customers, and highlights the importance of a master data management (MDM) strategy in this context.
Three major trends have emerged in financial firms over the past year:
- A significant surge in data consumption driven by increased business complexity & technology advancements
- Divisions are increasingly opinionated and empowered to use the data sources most relevant to them
- Increased adoption of MDM technologies to help unify all of this data and create golden records that firms can rely on to run their business
Increasing Demand for Data
Over the past year, data consumption within financial firms has seen a significant uptick. This surge is driven by several factors, including the complexity of financial models, advancements in technology, and improved accessibility of data through cloud platforms. Data science and machine learning teams, in particular, are insatiable in their demand for data. Agreements that provide unlimited access to data, such as those with major vendors, have further fueled this growth by removing barriers to data accessibility.
Divisions are Driving their own Data Strategy
Different divisions within financial firms exhibit varying levels of data consumption. For instance, Sales and Trading teams heavily rely on Bloomberg for their data needs, while Investment Banking often turns to FactSet. The demand for data feeds has grown substantially, with Risk Management functions also increasing their data consumption to match front-office operations. The feedback from people in the industry indicates that data services as a whole are getting better over time, demonstrating that this increase in demand is translating into R&D investment that is creating a better experience overall.
Increased Adoption of MDM
In this environment of growing data consumption, a robust master data management (MDM) strategy becomes essential. MDM ensures that data from various sources is accurately integrated, consistent, and accessible across the organization. It helps in managing the complexities of data from multiple vendors, enabling better data quality, reducing redundancies, and ensuring that all teams have access to the same, up-to-date information. Entity resolution, a crucial aspect of MDM, plays a vital role in identifying and linking data from different sources to create a unified view, which is particularly important for divisions that rely heavily on precise and timely data to make informed decisions.
Challenges Introduced by the Growth in Data Consumption
As financial institutions navigate the evolving landscape of data consumption, three challenges stand out:
- Finding a balance between desktop terminals and direct data feeds
- Switching data providers as needs change
- Integrating new technologies such as Cloud and AI
Desktop vs. Direct Feeds: A Balancing Act
Data consumption methods have evolved, balancing between desktop terminals and direct data feeds. While desktop terminals are indispensable for in-depth data analysis, direct feeds are crucial for integrating data into internal applications and dashboards. Bloomberg remains the primary terminal for Trading and Sales, whereas FactSet is preferred in Investment Banking and Wealth Management. The usage of Eikon/Workspace is also notable, particularly for specific needs like TradeWeb/FXMatching data.
Managing the Switching Costs of Changing Providers
Switching data providers is often fraught with challenges, including technical and resource-intensive hurdles. The disruption risk associated with switching, combined with the need to synchronize changes across front, middle, and back-office functions, makes it a complex decision. Long-term agreements that spread costs and offer comprehensive data access can make the prospect of switching less attractive, despite potential economic incentives.
Leveraging New Technology: Cloud & AI
The successful adoption of cloud technology by financial firms has simplified the onboarding of new data vendors and testing of data. However, the rise of AI has introduced new complexities, particularly around legal and contractual requirements for data consumption through AI. The debate is still early here, but it’s a high enough priority for most firms that we’ll likely see progress made quickly.
How Firms are Maximizing the ROI of Data Investments
The financial implications of increased data consumption are significant. Data vendors have implemented notable price hikes, influenced by inflation and new pricing models. Specialized licenses for specific applications have driven costs higher, especially post-COVID among niche vendors like those providing ESG data.
Contractual agreements with data vendors vary widely. While some firms avoid enterprise license deals due to higher costs, unique agreements offering extensive usage rights are highly valued. These comprehensive deals, however, often exclude specialized products, necessitating careful consideration of specific data needs and cost implications.
Consolidating vendors can streamline data management and reduce costs, but the presence of valuable niche vendors makes this challenging. The growth in data spend, driven by pricing and volume increases, underscores the ongoing demand for high-quality data. Though regulatory scrutiny has not been a major factor recently, it could drive future increases in data consumption, particularly in risk and compliance functions.
Given the rising costs of differentiated data assets, firms need an effective monetization strategy to justify their investment and get the expected returns. A well-implemented Master Data Management (MDM) strategy can play a critical role in capturing these returns. By creating an accurate and unified view of key data assets, MDM ensures a single source of truth, minimizing the need for extensive data reconciliation efforts and reducing the likelihood of a data asset becoming ‘shelfware’. This streamlined approach leads to more efficient operations and better resource allocation, maximizing the ROI of data investments.
Conclusion
In the rapidly evolving landscape of financial services, data consumption has become a pivotal factor for success. Financial institutions are increasingly relying on external data sources to drive decision-making, enhance operational efficiencies, and maintain a competitive edge. Over the past year, we have seen a significant surge in data consumption driven by business complexity and technological advancements. Divisions within firms are now more empowered to choose the data sources most relevant to their needs, and the adoption of Master Data Management (MDM) technologies has become essential to unify data and create reliable records.
However, this growth in data consumption introduces challenges, including balancing desktop terminals with direct data feeds, the complexities of switching data providers, and integrating new technologies like cloud and AI. Despite these hurdles, financial firms are finding ways to maximize the ROI of their data investments. This involves navigating rising costs, forming strategic data agreements, and leveraging MDM to ensure accurate and unified data management. By effectively managing these factors, financial institutions can optimize their data strategies, reduce redundancies, and achieve significant operational efficiencies, ultimately maximizing the returns on their data investments.