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

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

by internationalbanker

By Neil Sandle, Chief Product Officer, Alveo

 

 

 

 

Financial-services firms face challenges in both market-data costs and demonstrating compliance with content licensing agreements (CLAs). On one level, it is simply about rising prices. Financial-services companies often struggle with the escalating costs of market data. As the demand for data increases, so does the overall price tag. Managing these costs while acquiring the necessary data for operational and strategic decisions by all stakeholders is a significant challenge.

Costs can be opaque and unpredictable due to redundant purchases, complex content licensing agreements and inefficient data storage, stemming from individual departments or users selecting and procuring their data feeds without a centralised strategy.

The Financial Conduct Authority (FCA) recently published the findings of its “Wholesale Data Market Study”. The research found that the costs of acquiring the required data and developing the infrastructure to distribute it can be significant. The report highlighted price discrimination through value pricing, which increases the direct costs of data access and indirect compliance costs for users but with limited widening of access.

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

From a regulatory perspective, the requirements for data usage and reporting 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, reporting requirements under EMIR REFIT (European Market Infrastructure Regulation Refit), which recently went into effect, have more than 200 fields. Data usage is critical, given the need to trace and track data flows and be able to explain regulatory reporting as well as valuation and risk numbers. At the same time, new data sets also represent opportunities to be better informed and gain competitive advantages.

Moreover, AI (artificial intelligence) usage is growing. Forty-one percent of financial-services firms have extensively deployed AI across their business operations, according to a recent Alveo survey, and this prevalence puts the spotlight on organisations’ ability to attest to the origin and usage permissions of data fed into their models. The growing use of AI underscores the notion of “derived data” in content licensing agreements and may become a new use case in contracts.

Putting a solution in place

To address these challenges—commercial licensing policies from data owners aside—firms need to get their houses in order when it comes to financial-data management. A good starting point is assessing and mapping the organisation’s specific data needs. This involves identifying what data is essential for operations and decision-making and distinguishing it from non-essential data. This can help reduce costs by ensuring that firms pay only for the data they actually need.

Next, firms should look to optimise data-management processes to ensure efficient data handling and usage. On one level, this is about business-user enablement, which also drives efficiencies and cost-cutting. Data should function as a readily accessible resource, meticulously tagged for seamless retrieval.

Business users should possess the autonomy to fulfil their data needs independently, circumventing the need for IT (information technology) intervention or project alterations. This self-service model should streamline the incorporation of fresh data sets, the customisation of access permissions and the implementation of validation protocols and business rules. Given the fluid nature of business requirements, coupled with the evolving landscape of data variety and volume, adaptability is key. Any modifications to data structures or processing methods must be executed efficiently, ensuring cost-effectiveness without compromising efficacy.

In this context, having a user-driven analytics process is also key, as it helps firms implement tools to monitor and analyse how data is used within the company. This, in turn, assists them in understanding usage patterns and identifying areas in which data subscriptions can be modified or scaled down to save costs without impacting critical operations.

Equally, it is important to utilise 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 the costs associated with manual compliance checks.

On another level, it is about implementing data-governance practices that define clear policies and procedures for data access, usage and storage, thus helping with 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 shifting from on-premise setups but also enhances scalability and elasticity. This transition should further cut market-data costs by allowing for managing data on appropriately sized platforms and centralising licences. It can be accomplished through either partial or complete adoption of vendor-managed solutions that offer comprehensive services—from sourcing 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 real-time costs across different data sources, categories and user groups. Such advancements will facilitate the standardisation of data charges and consumption across the entire bank.

Moreover, data lineage will bring significant improvements, ensuring that the origins of data and any changes it undergoes throughout its lifecycle are meticulously documented. Ultimately, a shift to cloud computing not only streamlines operations but also lowers the expenses associated with changes, leveraging increased scalability to reduce costs effectively.

In terms of a deployment model, firms can choose between in-house management of their market-data strategies or managed services. Managed services offer a wide range of benefits. They help firms potentially lower 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 organisations to tap into a high level of expertise and stay up-to-date with compliance regulations, reducing the burden on the firm. Finally, managed services help deliver enhanced scalability, as they are easier and quicker to scale up or down based on changing data requirements without the need for direct investments in infrastructure.

On 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. It handles not just hosting and IT operations but also essential tasks, such as data cleansing, issue fixing and liaising with data providers. DaaS solutions offer financial-services firms streamlined ways to integrate new data, connect applications, support new use cases, establish reliable data foundations and reduce the costs of changes.

Depending on their needs, however, firms might also want to commit to a more comprehensive managed-services approach. Typically, this will include 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, in turn, to increase efficiency and lower operational costs for the end customer.

Strategic outcomes for enhanced market-data management

To effectively navigate the intricate landscape of market-data management, financial institutions must adopt a multifaceted approach that not only addresses the immediate challenges of cost and compliance but also sets the stage for long-term operational resilience. The strategic integration of cloud technologies, coupled with a robust data-governance framework, presents a viable pathway for firms to streamline processes and reduce expenditures. By leveraging data-as-a-service and managed services, institutions can enhance their data-handling capabilities, ensuring data accuracy and compliance while minimising costs.

The shift towards self-service platforms and user-driven analytics further empowers business users, fostering 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 demands. Additionally, automating compliance and governance processes significantly reduces the risks of errors and non-compliance, which is critical in the tightly regulated financial sector.

Ultimately, by embracing these kinds 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 fortifies 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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