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Neil Sandle, Chief Product Officer, Alveo
Financial services companies face challenges in both the cost of market data and demonstrating compliance with content licensing agreements (CLAs). At one level, it’s simply about price increases. Financial services companies often struggle with the increasing cost of market data. As the demand for data increases, so will the overall price. Managing these costs while obtaining the data needed for operational and strategic decision-making by all stakeholders is a major challenge.
Costs can be opaque and unpredictable due to duplicate purchases, complex content licensing agreements, and inefficient data storage. This is due to individual departments and users selecting and sourcing data feeds without a centralized strategy.
The Financial Conduct Authority (FCA) recently published the findings of its Wholesale Data Market Survey. The study found that acquiring the necessary data and developing the infrastructure to distribute it can be costly. This report highlights price discrimination through value pricing. This increases direct costs of data access and indirect compliance costs for users, but there are limits to expanded access.
From a compliance perspective, a lack of control and transparency in consumption and distribution, combined with increasingly fragmented and restrictive content licensing agreements, can spell discomfort for financial services companies.
From a regulatory perspective, data usage and reporting requirements are constantly evolving and expanding. Financial institutions will need to comply with new regulations such as ESG (environmental, social and governance) reporting requirements. Existing regulations are being expanded. For example, there are over 200 areas of reporting requirements under the recently enacted EMIR REFIT (European Market Infrastructure Regulatory Reform). The use of data is critical given the need to track and trace data flows and be able to account for ratings and risk figures as well as regulatory reporting. At the same time, new datasets are an opportunity to gain better information and gain a competitive advantage.
Additionally, the use of AI (artificial intelligence) is progressing. According to a recent Alveo study, 41% of financial services companies have broadly implemented AI across their business operations, and this uptake has focused attention on organizations’ ability to prove the origin and authorization of data input into their models. are gathering. The increased use of AI is highlighting the concept of “derived data” in content licensing agreements, which may provide new use cases in contracts.
implement a solution
To address these challenges, aside from commercial licensing policies from data owners, businesses need to be well-positioned when it comes to financial data management. A good starting point is to assess and map your organization’s specific data needs. This includes identifying what data is critical to operations and decision-making and separating it from unimportant data. This helps reduce costs by ensuring businesses only pay for the data they actually need.
Next, companies should consider optimizing their data management processes to ensure efficient data processing and usage. At one level, this is about enabling business users, which also drives efficiency and cost savings. Data must be meticulously tagged for seamless retrieval and serve as a readily accessible resource.
Business users need the autonomy to meet their data needs independently, avoiding information technology (IT) intervention or project changes. This self-service model should streamline incorporating new data sets, customizing permissions, and implementing validation protocols and business rules. Given the fluid nature of business requirements and the evolving nature and amount of data, adaptability is key. Changes to data structures and processing methods must be implemented efficiently and cost-effectively without compromising effectiveness.
In this context, it is also important to have a user-driven analysis process, as it helps companies implement tools to monitor and analyze how data is used internally. This helps you understand usage patterns and identify areas where you can change or reduce your data subscriptions to save money without impacting critical operations.
Similarly, it’s important to leverage technology that automates compliance processes, such as tracking data lineage, monitoring data usage, and ensuring reporting requirements are met. Automation helps reduce the risk of human error and costs associated with manual compliance checks.
At another level, we support compliance by implementing data governance practices that define clear policies and procedures for data access, use, and storage.
Moving your data management processes to the cloud can be a smart choice. Moving to the cloud not only reduces infrastructure and maintenance costs by moving from an on-premises setup, but also increases scalability and elasticity. This move should enable centralization of data management and licensing on a right-sized platform, further reducing market data costs. This can be achieved by partially or fully implementing a vendor management solution that provides comprehensive services, from sourcing market data to distributing it to customers.
Additionally, clearer visibility into data demand and usage improves management and allows for an accurate way to measure and monitor real-time costs across different data sources, categories, and user groups. Such advances will facilitate standardization of data charges and consumption across banks.
Additionally, data lineage brings significant improvements, ensuring that the origin of data and the changes it undergoes throughout its lifecycle are well documented. Ultimately, moving to cloud computing not only streamlines operations, but also leverages increased scalability to reduce costs associated with change, effectively reducing costs.
When it comes to implementation models, companies can manage their market data strategy in-house or choose a managed service. Managed services offer a wide range of benefits. Businesses may be able to reduce costs through economies of scale, as service providers can spread the cost of infrastructure and expertise across multiple customers.
At the same time, it eases the burden on businesses by allowing financial services organizations to leverage advanced expertise and stay up to date with compliance regulations. Finally, managed services can help improve scalability by allowing you to easily and quickly scale up or down based on changing data requirements without requiring any direct investment in infrastructure.
At one level is data as a service (DaaS), which focuses on providing access to specific data sets, often hosted in the cloud. Data as a Service combines traditional data management with the convenience of a SaaS (Software as a Service) platform. In addition to hosting and IT operations, it also handles important tasks such as data cleansing, problem resolution, and liaison with data providers. DaaS solutions offer financial services companies a streamlined way to integrate new data, connect applications, support new use cases, establish a reliable data foundation, and reduce the cost of change.
However, depending on your needs, your company may want to take a more comprehensive managed services approach. This typically involves more technical and operational aspects of data management, such as monitoring incoming data, ensuring data delivery, and maintaining transparency in the data supply chain, ultimately improving efficiency and ultimately Helps customers reduce operational costs.
Strategic results from enhanced market data management
To effectively navigate the complex landscape of market data management, financial institutions are adopting a multifaceted approach that not only addresses immediate challenges of cost and compliance, but also sets the stage for long-term operational resilience. There is a need. Strategic integration of cloud technologies and robust data governance frameworks present a viable path for companies to streamline processes and reduce spending. By leveraging Data-as-a-Service and managed services, institutions can increase their data processing capabilities and ensure data accuracy and compliance while minimizing costs.
The shift to self-service platforms and user-driven analytics will further empower business users and foster an environment of efficiency and adaptability. This transition not only supports the dynamic needs of financial operations, but also ensures that data management can respond to rapid market changes and regulatory demands. Additionally, automating compliance and governance processes significantly reduces the risk of errors and non-compliance. This is extremely important in the highly regulated financial sector.
Ultimately, adopting strategic initiatives like this will enable financial services companies to achieve a more sustainable and cost-effective data management paradigm. This not only ensures compliance and operational efficiency, but also strengthens a company’s market position by enabling more informed decision-making and faster response to market opportunities and challenges. The cumulative effect of these strategies will ensure that financial institutions not only survive today’s data challenges, but also thrive in an increasingly data-driven world.
