Published by linker 5
Posted on August 18, 2020
4 min readLast updated: January 21, 2026
By Boyke Baboelal, Strategic Solutions Director, Asset Control
The COVID-19 pandemic has acted as a catalyst for change across financial services. How quickly firms can adapt to change is key and, as they look to the future, one of the biggest priorities for many will be to minimise the cost of change, ensuring business continuity and analysing ever-larger data sets. Increasingly, firms need a better understanding about all data sets they have and, more to the point, how they can best use them to achieve business advantage.
In a world where data is the fuel to power business performance, bringing intelligence and facilitating access to that data is key. Keeping the cost of change in mind, the emphasis needs to be as much on the adaptability and extensibility of data models and the onboarding of new data sources as it is on data aggregation capabilities. Going forward, the focus for financial services firms should be on actively achieving intelligence from quality data rather than more passively collecting and tracking reams of data.
Managed data services offer the potential to reduce the cost of change but just looking at traditional data sets and integration workflows can be myopic. Firms should be evaluating new data sets, new sourcing and distribution models and reports to more quickly adapt to change and to increase the actionable intelligence they attain from their data management processes.
Today, the number of data sets and the diversity of data is increasing across financial services – and the number of alternative data services continues to grow. Growing volumes and diversity of data make the data integration task ever more complex. It needs to be set up properly if firms are to avoid not being able to see the forest for the trees. Data is meaningless if it is not available to be used. Data quality and tracking contextual information are key as is the capability, speed and reliability of the integration and overall preparation for use by end-users, valuation and risk models, in reports and in business applications.
Boyke Baboelal
Moving forward, data services will need to bring a more detailed and more transparent understanding of data lineage – where does data come from, what are the ultimate sources and what quality checks took place on the way. The more one gains an appreciation of data flows and data transformation events on the way to data usage the more one can expand augment and enrich these data sets.
Data derivation and enrichment can be done through traditional business rules and through machine learning. Linking new sources and data attributes to enable faster cleaning and wider integration is a prerequisite for this. The traditional function of data sourcing, mastering and quality management has to be rethought as AI and machine learning models can go wildly off the rails if fed with inaccurate data. So, it is important to track the context, metadata, quality statistics and permissions to get the context to prepare data for advanced analytics.
Businesses expect data to be plug and play and so do the algorithms. In conclusion, good data management is enabled by introducing processes that create data intelligence, that create a feedback loop for further improvement, a virtuous cycle if you like. To me, data intelligence relates to processes and procedures that bring meaning and depth to classification, categorisation, to rapid labelling and validation of outcomes. Achieving actionable insight is about managing metadata with skill and about building data models that are aligned to the insights that are needed across the business and across the different stakeholders downstream. These insights are discovered through analytics, visualisation, AI models and through different forms of advanced automation.
How quickly you can source, digest and process information and use the right contextual information to positively impact resilience in models in spreadsheets, in applications, or inboxes, will separate leaders of the pack from those scrabbling to keep up. However, to accomplish all that, requires specialist knowledge and understanding and that’s where a managed services provider can really make a positive difference, offering the expert help and advice organisations need to take data management to the next level while all the time allowing them to focus on their core business. Change will continue to impact financial services firms in the post-pandemic age. How capable they are at managing data to navigate this change will be the key to their future success.
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