Key takeaways from FIMA 2024 (Part one): Navigating the complexities of market data in financial services

Credera recently attended the Financial Information Management (FIMA) conference, a premier event for data management professionals in the financial services industry. FIMA brings together leaders and experts to discuss the latest trends, challenges, and innovations in financial data management.

This year’s conference provided invaluable insights into how organisations can navigate the complexities of market data, particularly in wealth and asset management. Drawing from the discussions and key takeaways from FIMA, this blog explores issues such as licensing, data governance, the importance of relationships and talent, and the need for advanced data literacy and automation.

The expanding universe of market data

Market data has evolved beyond traditional financial metrics to include alternative data sources, on-chain metrics, and blockchain data. Sentiment analysis, particularly within the cryptocurrency space, adds another dimension to the data landscape. The sheer volume and variety of available data can be overwhelming, making it crucial for organisations to have robust strategies for data management and utilisation.

In wealth and asset management, the ability to integrate and analyse diverse data sources is becoming increasingly important. Alternative data, such as social media sentiment, geospatial data, and transaction data, can provide unique insights that traditional data sources may not capture. On-chain metrics and blockchain data offer transparency and traceability, which are particularly valuable in the context of cryptocurrencies and digital assets.

Licensing and data governance

One of the primary challenges in market data utilisation is licensing. Ensuring that an organisation has the appropriate permissions to use various data sources can be both complex and costly. Effective data governance is essential to manage these complexities. Organisations need strong foundations in data quality and governance before engaging in commercial conversations about data use. This helps mitigate risks associated with non-compliance and inefficiency.

Data governance involves establishing policies, procedures, and standards to ensure the accuracy, consistency, and security of data. It also includes defining roles and responsibilities for data management and ensuring compliance with regulatory requirements. By implementing robust data governance frameworks, financial organisations can enhance data quality, reduce operational risks, and improve decision-making.

The role of relationships and talent

Trust and collaboration are built on strong relationships and capable people. However, the financial services industry has seen a significant loss of talent due to events like COVID-19 and Brexit, which has eroded in-person relationships. Much of the talent is now offshore, making it challenging to maintain close connections. Rebuilding these relationships is crucial for understanding the needs of individual investors and staying close to the wealth and asset management processes.

The loss of in-person relationships has impacted the ability to collaborate effectively and share knowledge. To address this, organisations need to invest in building strong virtual relationships and fostering a culture of collaboration. This includes using digital tools and platforms to facilitate communication and knowledge sharing, as well as providing opportunities for professional development and training.

Monitoring and utilising market data

Organisations like Investec leverage third-party services to conduct discovery pieces, helping them understand how market data is used within their operations. Monitoring whether wealth and asset managers are using specific data points is fundamental. Regularly challenging the necessity and value of the data being paid for can prevent wastage and ensure that the data meets user needs.

Effective data utilisation requires continuous monitoring and evaluation. This involves tracking the usage of data by different teams and individuals, analysing the impact of data on decision-making, and identifying areas for improvement. By regularly assessing the value and relevance of market data, organisations can ensure that they are investing in the right data sources and maximising their return on investment.

The impact of regulation

Regulation plays a crucial role in shaping data management practices within the financial services industry. Various regulatory frameworks, both existing and emerging, enforce stringent data quality and governance standards. Compliance with these regulations is essential for maintaining operational resilience and protecting the interests of clients and stakeholders.

Regulatory requirements often mandate the establishment of robust data governance frameworks, including policies for data quality, security, and privacy. They also necessitate regular audits and reporting to ensure compliance. By adhering to these regulations, organisations can enhance their data management practices, reduce operational risks, and build trust with clients and regulators.

Enhancing data literacy and automation

Despite the growing importance of data, self-service data and analytics remain at a nascent stage in many organisations. Delivering data literacy, policy, and technology is essential for empowering teams. Transforming mindsets to become data-literate and demonstrating the value of data initiatives are key steps.

Data literacy involves equipping employees with the skills and knowledge to understand, interpret, and use data effectively. This includes training on data analysis techniques, data visualisation, and the use of data tools and platforms. By fostering a data-literate culture, organisations can enhance their ability to leverage data for strategic decision-making and innovation.

During a live poll at the event, we saw that automation of data processes varies, with many organisations reporting that only 50% of their data processes are partially automated. Additionally, 57% of people indicated that 50-75% of their data stack is legacy. Moving towards greater automation and modernising legacy systems will be critical for improving efficiency and effectiveness.

Automating data processes can reduce manual effort, minimise errors, and accelerate data processing and analysis. This includes implementing automated data collection, cleansing, and integration workflows, as well as using advanced analytics and machine learning to derive insights from data. By modernising their data infrastructure and embracing automation, organisations can enhance their agility and responsiveness to market changes.

How Credera can help

At Credera, we understand the complexities and challenges associated with market data in financial services and offer tailored solutions to meet your unique needs. With extensive expertise in data management, we help organisations unlock the full potential of their data by implementing robust governance frameworks, enhancing data literacy, and automating processes. Our innovative approach ensures compliance, streamlines operations, and empowers better decision-making.

Our case studies showcase our impact, such as partnering with a leading financial services firm to achieve a 30% increase in data accuracy and a 25% reduction in processing time. Similarly, we helped a global asset management company enhance data governance, driving compliance and improved decision-making. By navigating market data challenges with confidence, we enable organisations to remain competitive, foster growth, and deliver greater value to clients.

• Data & Analytics
• Financial Services
• Data Governance
• Data Integration
• Data Management and Activation
• Data Management Platform