Redefining Your Wholesale Market Data Strategy: Compliance, Cost Control, and Cloud Solutions

from Neil SandleHead of Product, Alveo

FFinancial services firms face challenges in both market data costs and demonstrating compliance with content licensing agreements (CLA). At one level, it’s simply about raising prices. Financial services companies often struggle with the rising costs of market data. As the demand for data increases, so does the overall price. Managing these costs by obtaining the necessary data for operational and strategic decisions from all stakeholders is a significant challenge.

Costs can be opaque and unpredictable due to over-purchasing, complex content licensing agreements and inefficient data storage, stemming from individual departments or users selecting and procuring their own data sources without a strategy. centralized.

The Financial Conduct Authority (FCA) recently published its findingsBulk data market research. The research found that the costs of obtaining the required data and developing the infrastructure to distribute it can be significant. The report highlighted price discrimination through value pricing, which increases direct data access costs and indirect compliance costs for users, but with limited expansion of access.

In terms of compliance, the lack of controls and transparency in consumption and distribution, combined with increasingly granular and restrictive content licensing agreements, could lead to unpleasant surprises for financial services firms.

From a regulatory perspective, data use and reporting requirements are constantly evolving and expanding. Financial institutions must comply with new regulations, such as ESG (environmental, social and governance) reporting requirements. Existing regulations are being expanded; for example, the reporting requirements under EMIR REFIT (Reinstatement of the European Market Infrastructure Regulation), which came into force recently, have more than 200 fields. The use of data is critical, given the need to track and trace data flows and to be able to explain regulatory reporting as well as risk assessment and numbers. At the same time, new data sets also represent opportunities to become better informed and gain competitive advantage.

Moreover, the use of AI (artificial intelligence) is increasing. Forty-one percent of financial services firms have widely deployed AI in their business operations, according to recentAlveo survey, and this prevalence puts a spotlight on the ability of organizations to validate the origin and usage permissions of the data entered into their models. The growing use of AI underscores the notion of data obtained in content licensing agreements and may become a new use case in contracts.

Setting up a solution

To address these challenges, commercial licensing policies from data owners in addition to firms need to put their houses in order when it comes to managing financial data. A good starting point is to assess and map the organization’s specific data needs. This includes identifying data that is essential to operations and decision making and distinguishing it from non-essential data. This can help reduce costs by ensuring that companies only pay for the data they actually need.

Firms should then seek to optimize data management processes to ensure efficient data handling and use. At one level, this is about enabling business users, which also drives efficiency and cost reduction.

Business users should have the autonomy to meet their data needs independently, bypassing the need for IT (information technology) intervention or project changes. This self-service model should simplify onboarding new data sets, customizing access permissions, and implementing validation protocols and business rules. Given the fluid nature of business requirements, along with the evolving landscape of data variety and volume, adaptability is essential. Any modifications to data structures or processing methods must be executed efficiently, ensuring cost-effectiveness without compromising efficiency.

In this context, having a user-driven analytics process is also essential, as it helps firms implement tools to monitor and analyze how data is used within the company. This, in turn, helps them understand usage patterns and identify areas where data subscriptions can be modified or reduced to save costs without impacting critical operations.

Equally, it is important to use technology that automates compliance processes, such as tracking data lineage, monitoring data usage and ensuring that reporting requirements are met. Automation helps reduce the risks of human error and costs associated with manual compliance checks.

At another level, it’s about implementing data governance practices that define clear policies and procedures for data access, use, and storage, thus aiding compliance.

Moving the data management process to the cloud is likely to be a sensible option. Moving to the cloud not only reduces infrastructure and maintenance costs by moving from on-premise configurations, but also increases scalability and resilience. This transition should further reduce market data costs by allowing for data management on appropriately sized platforms and centralization of licenses. It can be achieved through partial or full adoption of vendor-managed solutions that provide comprehensive services from acquiring market data to distributing it to customers.

Additionally, clearer visibility into data demand and usage will lead to improved controls, enabling methods to accurately measure and monitor costs in real time across different data sources, categories and user groups. Such advances will facilitate standardization of fees and data consumption across the bank.

Additionally, the data pipeline will bring significant improvements, ensuring that the origin of data and any changes it undergoes throughout its lifecycle are accurately documented. Ultimately, a move to cloud computing not only streamlines operations, but also lowers costs associated with change, leveraging increased scalability to effectively cut costs.

Under a deployment model, firms can choose between managing their market data strategies in-house or managed services. Managed services offer a wide range of benefits. They help firms potentially reduce costs due to economies of scale, as service providers can spread the costs of infrastructure and expertise across multiple clients.

At the same time, they enable financial services organizations to leverage a high level of expertise and stay up-to-date with compliance regulations, reducing the burden on the firm. Finally, managed services help provide enhanced scalability, as they are easier and faster to scale up or down based on changing data requirements without the need for direct infrastructure investment.

At one level is data as a service (DaaS), which focuses on providing access to specific data sets, often hosted in the cloud. It handles not only hosting and IT operations, but also essential tasks, such as data cleansing, fixing issues and liaising with data providers. DaaS solutions offer financial services firms easy ways to integrate new data, connect applications, support new use cases, create reliable databases and reduce change costs.

However, depending on their needs, firms may also want to commit to a more comprehensive managed services approach. Typically, this will involve more technical and operational aspects of data management, such as monitoring incoming data, ensuring data distribution and maintaining transparency in the data supply chain, helping, on the other hand, in increasing efficiency and reducing operational costs for the end customer.

Strategic outcomes for improved market data management

To effectively navigate the complex data management landscape of the market, financial institutions must adopt a multi-pronged approach that not only addresses immediate cost and compliance challenges, but also lays the foundation for long-term operational sustainability. The strategic integration of cloud technologies, coupled with a robust data governance framework, presents a sustainable path for firms to improve processes and reduce costs. By leveraging data-as-a-service and managed services, institutions can improve their data handling capabilities, ensuring data accuracy and compliance while minimizing costs.

The shift to self-service platforms and user-driven analytics further empowers business users, driving an environment of efficiency and adaptability. This transition not only supports the dynamic needs of financial operations, but also ensures that data management can keep pace with rapid market changes and regulatory requirements. Additionally, automating compliance and governance processes significantly reduces the risks of error and non-compliance, which is critical in the highly regulated financial sector.

Ultimately, by embracing these types of strategic initiatives, financial services firms can achieve a more sustainable and cost-effective data management paradigm. This not only ensures compliance and operational efficiency, but also strengthens the firm’s market position by enabling more informed decision-making and faster responses to market opportunities and challenges. The cumulative effect of these strategies will ensure that financial institutions not only survive the current data challenges, but also thrive in an increasingly data-driven world.

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