In the investment industry, success is often built on strong data foundations. Access to accurate, clear data can enhance operational efficiency, improve decision-making processes and create new business opportunities.
And as AI-based solutions are rolled out across the financial sector the importance of having high-quality, clean and standardised data is only likely to grow.
But, as data takes an increasingly central strategic role, firms face a major challenge: how can they manage growing volumes of data while also maintaining their focus on servicing clients, implementing investment policies and developing new revenue streams?
Traditionally, investment companies have kept their data-management functions in house, either through a dedicated team or by spreading responsibility across a number of functions within the company. But such an approach has several potential drawbacks – and these can be amplified as firms look to increase their reliance on data.
Why fragmented data holds firms back
01
Fragmented nature of data across an organisation
One common challenge is the fragmented nature of data across an organisation. It can be argued that most investment companies don’t have a data strategy problem - they have a data operations problem.
Because legacy data-management systems have often evolved unevenly over periods of years or even decades, data may end up siloed in different locations or business units.
As a result, different teams can end up using information that is inconsistent, difficult to compare or stored in a variety of formats.
Valuable time needs to be devoted to reconciling and matching data rather than analysing it and leveraging the insights it provides. At the same time, the fact that data has to travel between systems can introduce additional operational risks as well as potential points of failure.
02
Problems in scaling their data provision
Firms with such legacy systems will invariably face problems in scaling their data provision in line with growing technological or AI-based requirements.
Financial institutions are under increasing pressure to demonstrate agility and innovation in response to fast-moving market conditions. But without access to reliable data sources that can be quickly made available across the business, progress is likely to be held back.
Firms may not be able to capitalise on new opportunities as quickly as their rivals. Without a robust data foundation, AI ambitions are likely to stall before they can scale.
03
Regulatory and audit-related requirements
The extent to which data can be trusted is also an issue in terms of regulatory and audit-related requirements.
Rigorous governance of information related to portfolio performance as well as factors linked to sustainability, for example, is crucial.
Again, considerable time and resources may need to be devoted to reconciliation and validation on a regular basis if firms are to ensure they remain compliant.
How can firms overcome these potential inefficiencies and support a strategy that is truly data-first?
One option is to make a significant investment in bringing the company’s internal data-management function up to date, ensuring it can cope with the demands of today’s data-driven operating environment. But this approach is likely to entail considerable up-front costs in terms of recruitment and training as well as the implementation of new technology platforms. Moving forward, ongoing expenditure will be needed to ensure these systems and processes are able to keep pace with technological and market developments.
An alternative is to consider a third-party data service, where a provider offers a comprehensive managed-data solution to cover the full range of investment companies’ requirements, from sourcing and normalisation to governance, quality control and distribution.
This type of service can be tailored to suit internal systems, operating models and preferred external data sources. Implementation need not require major upheaval: the platform can be provided seamlessly through application programming interfaces (APIs), direct connections or technology partners. And the potential advantages are significant.
A single golden data source
The data management service makes it straightforward to consolidate data into a single, governed source that can be accessed – and trusted – across the whole organisation. This can lead to faster and more accurate regulatory reporting, as well as quicker and better-informed decision making.
Increasing operational efficiency
Outsourcing the data function can also create operational efficiencies through simplifying a firm’s internal technology requirements and freeing up time that has previously been devoted to data management and reconciliation. Looking to the future, clients can quickly and flexibly scale up their data usage without incurring the extra expense of increasing headcount. This approach has the potential to turn data from an operational burden to a strategic enabler.
Making data AI-ready
Ensuring that the firm’s data can be seamlessly integrated with AI services is another bonus. To function most effectively, AI requires data that is normalised, traceable and reliable. A third-party service provider can ensure that AI platforms receive data inputs that are correctly formatted and validated, thus optimising the technology’s ability to generate insights and create value.
At Amundi Technology, our secure and flexible data-as-a-service solution is a proven operating model that is trusted by over 30 leading global financial institutions, including BNY Mellon, Citibank and AJ Bell. Our service is built on real production environments, and is scalable across regions and asset classes. It is delivered through technology built around your model and your systems – and in the environment where you want to consume data.
The result is a single, consistent view of your data across the whole organisation, and without any operational disruption during the implementation process. We ensure that every technology project is based on a solid foundation of clean, centralised and governed data. This supports innovation by enabling new initiatives to get off the ground faster, while ensuring full alignment between business needs and regulatory requirements.
