In a global investment market seeking ever greater efficiencies, moves towards T+1 settlement in Europe and the introduction of new messaging standardization under ISO 20022 are just two developments helping to reshape the securities markets landscape.

Yet growing market complexity, the sheer range of financial products now available, and the need to aggregate, normalize and validate data are placing pressure on financial services professionals and systems.

The age of artificial intelligence (AI) and its widening application in financial services also will only raise the need for robust data management.

According to one recent survey, 94% of decision-makers at UK/US financial institutions anticipate an increase in their overall data budgets over the coming budget year¹. Many are seeking to develop more robust data strategies to help drive operational efficiencies and achieve greater scale.

Taking a strategic approach

Against this backdrop, the need for effective data strategies and management has never been more acute. In an increasingly automated and complex world, combining manual data sources and hoping for the best is no longer an option.

Today’s firms need single, clean, authoritative, trusted master data sets. Yet developing these is no simple task and firms may require better trained people, improved processes and technologies to get the full value from all their existing data sources.

We believe navigating the data challenges presented by global securities market today rest on three key pillars:

• Developing and implementing an effective data strategy
• Evolving a fit-for-purpose data operating model
• Achieving reliable, quality enterprise data

In our view, firms increasingly recognize that technology, data, and operations need to operate in harmony and that defining their data model and strategy is key.

In many cases these firms are keen to simplify their data operating models to unlock the value of their data and make it more readily available and useful. Adopting a domain approach is just one way to address this which can allow firms to decouple data from applications and turn fragmented data into actionable insights.

In addition, achieving reliable, quality enterprise data is imperative, yet poor quality data continues to proliferate across financial businesses. The challenge it presents can seem overwhelming.

It also impacts firms’ ability to create scale and efficiency just as industry pressure on margins through fee compression intensifies. Underpinned by competition and a higher inflation environment, these pressures are impeding flows and increasing operational costs.

Many investment firms still receive much of their data in a ‘non preferred’ format. And too many rely on the manual reconciliation of data, often within disparate internal lines of data processing. Automating these reconciliation processes can lead to significant savings, but the ever-changing nature of data inputs, outputs, and requirements can make automating difficult. Any potential solution must be flexible and adaptable, leveraging people, technology, or the combination of both to update rules and mapping in response to changes in strategy, providers, or desired outputs.

CIO challenge

For chief investment officers, full oversight of investments is crucial in an environment of continual growth and complexity. We see an increasingly urgent requirement for technology to evolve to give investors a total and reliable portfolio view across all the asset classes and investments in their fund structures.

At the front end, we also see continued demand for better quality data and data delivery to enable better investment decision making. Yet, again, too many firms still rely on in-house, manual work arounds to pull this data together from multiple sources.

While these varied data challenges may seem daunting, we believe it is important that investment companies make a start. The data challenge is not insurmountable and even starting small can give firms a base to build from.

As part of this process, it makes sense to partner with firms with the expertise to help transform data collection, develop and implement effective data strategies and empower staff to embrace data-driven decisions.

The road ahead

We appreciate data management projects can be complex, expensive, and resource-heavy and believe it is critical to start with repeatable building blocks based on specific and pragmatic business needs to help accelerate return on investment.

Introducing and implementing effective data strategies are likely to remain some of the most pressing and complex challenges facing financial institutions. With this in mind, we believe it has never been more important for organizations who have not already done so to tackle the data challenge.