By Justin Llewellyn-Jones, head of capital markets for North America at Broadridge.
As financial services firms craft strategies for what’s shaping up to be a challenging 2023, they must hold strong on one essential point: don’t cut back on investments in data management.
Over the past several years, many financial services firms have launched initiatives to overhaul the way they process and use data. The goal of these programs is to establish some level of centralized data management and governance, and to integrate data and analytics into organizational workflows.
Managing Data
These sometimes sweeping, organization-wide efforts are required because firms in the financial services industry have faced some unique challenges when it comes to managing data. Many of today’s large financial services providers – and even some of the smaller ones – are the product of a series of mergers and acquisitions. Every one of those corporate marriages brought together at least two legacy technology platforms. The end result is usually a fragmented ecosystem of applications built for specific asset classes, regions, and business operations, bolted together and patched to function.
This is a sub-optimal environment for data management. In any given financial services firm, data can reside in multiple places across these siloed legacy systems and platforms. Those datasets can exist in different iterations and formats, some of which have been tweaked and customized by individual business owners within the firm. This is a perfect recipe for inefficiency and error risk.
With data and analytics transforming business and finance, this outdated infrastructure represents a huge liability. Providers able to integrate robust and reliable data into their business functions are experiencing a huge lead over the competition. Those leaders include FinTechs and neo-banks that, unencumbered by legacy platforms, are winning market share with data-driven business models built from scratch.
A recent study by Broadridge shows that 98% of financial service firms are investing to enhance front-to-back-office workflow management. When asked to name their top priorities when allocating those investment dollars, 60% of survey respondents cite data management tools – topping other areas by a wide margin.
Identifying Obstacles
As these firms lay out plans to transform data management capabilities, more than half identify technology gaps like the continued use of cumbersome legacy technology as their primary challenge. Behind outdated technology, survey participants cite two additional obstacles: a lack of trained data management professionals; and a general shortage of resources that makes it difficult to quickly test, onboard, validate and maintain datasets.
What is clear from these results is that financial services firms need to be devoting more resources to data management, not less. In an increasingly challenging business and market environment, budgets will be shrinking. Within IT investment programs, there will be an incentive to prioritize spending that helps achieve short-term cost reductions, as opposed to longer-term strategic goals.
Fighting Today for a Better Tomorrow
In this environment, it is critical that senior management teams hold the line on data management investments. In fact, data management capabilities become more important than ever in tough conditions. When firms establish a sound process for producing reliable, usable and timely data, they are setting a foundation that allows them to automate routine tasks and apply more advanced robotic process automation (RPA) to achieve even bigger time-savings and cost reductions. This foundation also facilitates the use of artificial intelligence (AI) and machine learning (ML) tools that can vastly enhance efficiency, potentially helping to maintain or even expand margins across the business cycle.
Finally, by committing to maintain investments in data management during the current downturn, financial services executives will be keeping their firms on course for a broader strategic transformation into analytics-driven organizations, prepared to compete and thrive in the new, data-driven economy.
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