Expert: Preya Patel, Head of Data, Financial Software Ltd Facilitator: Matt Lonsdale, Davies Group
Headlines:
- Poor data quality costing organizations an average of $12.9 million per year, according to Gartner
- The International Organization for Standardization (ISO) predicts that ISO 20022 will support 80% of transaction volumes and 87% of transaction value worldwide by 2025
- One participant mentioned paying £300,000 for a small number of accounts to maintain access to historical data after changing benchmarks
- The pressing need for the wealth management industry to address the challenges posed by the current market data landscape, either through collective action, regulatory intervention, or disruptive technological solutions
Discussion:
The discussion explored the high costs associated with data contracts, lack of transparency in pricing, anti-competitive practices such as expunging historical data upon contract termination, difficulties in switching providers, and the need for data standardisation.
Delegates expressed frustration with the monopolistic behaviour of major data vendors, who charge exorbitant fees and impose unfair contractual terms. They highlighted the significant expenses incurred by firms, particularly smaller ones, in obtaining and maintaining access to market data, which ultimately impacts the end clients through higher costs.
The discussion also explored potential solutions, such as industry collaboration, adoption of data standards like ISO 20022, and the role of emerging technologies like AI in disrupting the current data distribution model. However, concerns were raised about the challenges of implementing such solutions, given the complexity of legacy systems and the resistance from established vendors.
Challenges in acquiring validated sources of high-quality data
The processes and challenges involved in acquiring validated sources of high-quality data were discussed, with emphasis on the importance of having a robust control framework for managing data sources, understanding data hierarchies, and implementing enterprise data management practices. However, the difficulties in ensuring data quality, particularly when dealing with multiple vendors and complex data distribution conditions were acknowledged.
Cost of data contracts and anti-competitive practices
The session covered concerns about the high costs of data contracts, lack of transparency in pricing, and anti-competitive practices by major data vendors. Participants criticized the monopolistic scenario, where consumers find it difficult to switch providers due to market dominance by a few players. The practice of expunging historical data upon contract termination was highlighted as a significant barrier to switching, leading to firms being locked into legacy infrastructure and managing separate data sets.
Challenges of existing data fields and data standardisation
The discussion touched upon the challenges posed by the current state of market data contracts and the lack of data standardization across the industry. Delegates explored the potential benefits of adopting the ISO 20022 standard, which aims to create a common language and improve interoperability among financial institutions. However, concerns were raised about the investment required to meet the standard and the complex process of integration.
Potential solutions and industry collaboration
The potential solutions to address the market data challenges, including industry collaboration, adoption of data standards, and the role of emerging technologies like AI were explored. The idea of wealth managers collectively approaching vendors as a cohort to challenge pricing and demand better services was also discussed. However, concerns were raised about the feasibility of such collaboration, given the competitive nature of the industry and the resistance from established vendors.
Key takeaways:
- Explore the possibility of industry collaboration or collective action to negotiate better terms and pricing with data vendors
- Investigate the adoption of data standards like ISO 20022 and assess the potential benefits and challenges for the organisation
- Evaluate the feasibility of leveraging emerging technologies, such as AI, to disrupt the current data distribution model and reduce reliance on traditional vendors
- Conduct a comprehensive review of existing data contracts, identifying opportunities for cost optimization and potential areas for renegotiation or termination
- Assess the organization's readiness for implementing data governance and enterprise data management practices to improve data quality and control
- Engage with regulatory bodies and industry associations to advocate for greater transparency, fairness, and competition in the market data landscape
