Introduction  

The macroeconomic environment has led to increased operating costs. Since 2019, staff expenses have risen by about 8% annually due to wage indexation and the need for additional personnel to address evolving regulatory requirements. IT costs have surged even more rapidly, with an average annual growth rate of 12%, as banks invest in digital transformation projects.

Enhancing operational efficiency is crucial for mitigating the impact of rising operating costs on profitability. A key area where banks can achieve significant savings is in market data management. According to our recent Deloitte Luxembourg study, financial institutions identified average potential savings of 20% in their market data expenditures.

This Deloitte study benchmarks 15 financial institutions across Luxembourg, evaluating them based on factors such as revenue, assets under management, and market focus. It includes a range of participants, including banks, asset managers, wealth management firms, and financial service providers, from both local entities and branches or subsidiaries of global institutions. The findings highlight how effective market data management can drive substantial cost reductions and improve overall operational efficiency.

This article explores the five main challenges banks face in market data management (MDM), where inefficiencies and rising costs are significantly driven by these obstacles.

The five challenges banks face in MDM

1. Diversification of data providers

Most banks incur high costs due to using multiple market data providers, with 60% of respondents using five or more providers. This leads to significant annual spending that accounts for an important share of their total operating expenses.

Banks face challenges related to infrastructure and system design that limit their flexibility to negotiate better contracts or switch to cost-efficient alternatives. Additionally, licensing fees have increased by 20% over the last three years, affecting 80% of respondents.

2. Over-reliance on market data terminals

Banks heavily depend on market data terminals, with some using a large number regardless of the institutions size. Terminals are often underutilized, being shared by multiple FTEs, which leads to preventable expenses. Alternatives such as shared terminals or consolidated platforms are rarely considered, limiting potential cost savings. 

3. Complexity of integrating multiple data sources

Banks face significant challenges in integrating data from various providers, with over 70% of respondents reporting difficulties in this area. Key obstacles include inconsistent data formats and the reliance on manual consolidation, which increases costs and reduces operational efficiency. Additionally, more than 50% of banks still use self-developed on-premises solutions, limiting automation and Application Programming Interface (API) integration. These challenges hinder agility and drive up the time and costs associated with integrating new data sources.

4. Compliance and data governance complexities

The survey highlights significant compliance and data governance complexities faced by Banks when using and distributing market data. Banks often struggle to comply with market data providers' licensing agreements. Nearly 40% of respondents report challenges in ensuring the compliant usage of their market data, and approximately 50% experience recurring data quality issues.

The lack of robust data governance frameworks exposes banks to significant compliance risks, which may result in fines up to two to three times their annual market data costs. Moreover, the reliance on manual processes further compounds the risk of non-compliance and data inaccuracies. 

5. Low automation and operational efficiency

Nearly 30% of respondents rely on manual processes for data standardization and enrichment, resulting in a significant allocation of resources to manage large volumes. This lack of automation not only drives inefficiencies but also increases operational costs and the potential for errors, emphasizing a critical area for improvement in operational efficiency. 

How to address these challenges

These key challenges identified highlight the need for efficient solutions to address cost, regulatory, technological, and operational inefficiencies. Banks can use a set of levers to address them.

The first step involves assessing data provider consolidation and optimization to reduce the number of vendors and eliminate redundancies. Research shows that 70% of the data banks need can be obtained from any major provider. Additionally, renegotiating vendor contracts to secure better terms and more flexibility can further reduce costs. It is also important to identify and optimize the number of terminals by reassessing the current usage and necessity.

Another strategy is to standardize data processing by using common data formats and automated workflows for consistency, accuracy, and efficiency. By standardizing extraction, filtering, and enhancement techniques, organizations can reduce manual effort and improve data quality. Scalable solutions, such as cloud-based systems offer flexible deployment models, optimizing infrastructure and reducing costs compared to traditional on-premises setups. Automation also streamlines data integration, reduces errors, and enables quicker, more reliable decision-making.

Banks should strengthen their governance processes by creating robust frameworks to ensure compliance with providers' licensing and usage policies. Implementing capabilities for traceability and monitoring of data is crucial. Standardizing procedures for data management and compliance also helps to effectively mitigate risks.

Figure 1. Success lies in leveraging a tailored combination of these strategies

Conclusion

Rising costs and inefficiencies in market data management are driven by challenges such as vendor reliance, gaps in automation, and inadequate governance. Addressing these issues requires tailored solutions that meet specific organizational needs.

By leveraging the discussed levers, banks can significantly enhance their market data management cost efficiency. In the short term, focusing on vendor consolidation, processing standardization and a strong data governance can deliver “quick wins.”