Why Innovation Matters:
Meeting the Challenges of the Modern Financial Services Sector
Today, financial services firms face increasingly complex challenges. Among them are increasing trading volumes; periods of high market volatility; the introduction of new regulations, such as the Payment Services Directive (PSD2) and Fundamental Review of the Trading Book (FRTB); and the emergence of a new class of competition. To thrive, firms need to accelerate innovation.
Businesses across the financial services sector are increasingly looking to address these challenges, while reducing costs and simplifying infrastructures. 50% of IT decision-makers within the financial/banking sector surveyed in a recent poll commissioned by InterSystems, a global leader in information technology platforms, say their organizations are most strongly focusing their innovation efforts on ‘business processes’ today.
So, what is preventing organizations from meeting these challenges? To a great extent, existing technology infrastructures are simply not sufficiently attuned to the demands of the modern financial services environment.
The survey highlights the core challenges here. More than half — 51% — of the IT decision-makers polled say processes across multiple applications are not well integrated across their organizations, while 43% believe their organization is struggling to achieve a complete and accurate enterprise-level view of all their data.
It’s not just about siloed applications and data. The difficulties associated with handling ever-escalating data volumes are increasing, and showing no sign of abating. Analyst firm IDC recently projected that by 2025, the global ‘datasphere’ will have grown to a staggering 163 zettabytes of data generated per year, ten times the data generated in 2016.
Financial services organizations often find it difficult to handle the vast volumes of incoming data and legacy data — then struggle to use it to get a clear picture of their organization and processes while also using it to comply with regulatory and other requirements.
One of the main reasons is that the systems and infrastructure these firms have in place today do not support a sufficiently agile approach. Most financial services organizations have implemented a wide range of applications over the course of decades that were not designed or built to interoperate. As a result, data is typically siloed, and organizations find it difficult to leverage it in order to advance their business goals.
Reliance on Legacy Systems
This inability to analyze data is compounded by having multiple different types of data management technologies, together with a vast range of applications that operate in silos across the organization.
In the past, with budgets tight and little overarching regulatory imperative to change, many financial institutions had not done enough to address these disconnected legacy systems. When faced with the new wave of regulations that came in after the 2008 financial crisis, long-established financial services organizations generally only had to invest in different applications on an ad hoc basis to meet individual regulations without fully integrating their various legacy systems.
Firms of all ages are struggling. New firms have difficulty complying with new regulations like FRTB, which require analyzing larger data sets within smaller processing windows.
Meanwhile, older organizations, especially those that haven’t integrated the systems they built in the 20th century, are likely to have more serious concerns to address. For these organizations, investment in new technologies will be necessary to meet the regulatory requirements.
According to the survey, one way to address current challenges facing financial services organizations is by implementing innovative new technologies and solutions. By far the biggest driver of innovation for IT decision makers within financial services was “emergence of new technologies,” highlighted by nearly half of those surveyed. That said, organizations will need to be careful that new technology does not disrupt their existing organizational systems. No firm wants to rip and replace their existing infrastructure. The challenge they will face is how to meet their current and future requirements without disrupting their current systems.
According to the survey, the top areas of planned investment are cloud and data analytics. 36% plan to invest more in cloud infrastructures to drive innovation over the next two to three years.
Nearly as many respondents — 31% — are planning investments in data analytics. The data are clear: Artificial intelligence, predictive modeling, and machine learning, together with enhanced integration of applications, will be important to the success of financial institutions’ initiatives. Doing so will eliminate data silos, increase accuracy, provide a clearer view of historical activity, and allow firms to make new insights and create of new data-intensive services.
Beyond these goals, however, better data analytics will also be important in helping financial services organizations comply with challenging new regulations that require analyzing more data within smaller processing windows.
The specific solutions will differ depending on the organization and the requirements. However, most organizations will require a modern data platform that can handle both integration and real-time data management, as well as analytics to meet the pressing regulatory requirements and business challenges they face, provide a real-time view across the business, and connect with external data sources and partners.
The platform must be agile enough to support future queries, and be cloud capable, and secure – in short, future-proof.
Data platforms also need to be agile. As businesses move systems and applications into the cloud, they are starting to ‘containerize’ their applications. Once containers have been set up in the cloud, they become reusable and portable from platform to platform.
It is also crucial too that the chosen platform can perform analytic queries on the data that the organization holds, even if that data is in large data sets and even if the queries are not known in advance.
This capability is critical for complying with regulatory requirements and answering unplanned ad hoc questions from industry regulators and from the business.
Find a Solution
Given these challenges, how can financial services organizations find a solution that meets their requirements? Data platforms that can support transactions and analytics concurrently at very high scale with highly efficient resource utilization, high reliability, and low total cost of ownership are critical in today’s environment. In addition, organizations require comprehensive data and application integration capabilities and advanced analytics capabilities — including machine learning.
Technology solutions that are able to scale up and out to handle very high transactional and analytic workloads simultaneously, are now being used throughout the financial services industry for their ability to handle real time processes at scale, uncover new insights, create new revenue opportunities, comply with challenging new regulations, and improve overall business agility for organizations.
While innovation has always been a key priority for financial services, it is even more critical today as more stringent regulations, increased customer demands, and the emergence of competitive FinTechs create a new set of challenges.
Financial services organizations today plan to invest to meet thes challenges: fully 55% of IT decision-makers within the financial/banking sector expecting their business’s investment in new technology to grow over the next three years.
What is driving this change, above all, is the growing set of competitive pressures and market demands, and the availability of new technology capable of delivering innovation and enabling financial services firms to meet these challenges. For those firms that grasp the opportunity, the future will soon be here.
1- Source: Data Age 2025: The Evolution of Data to Life-Critical – Don’t Focus on Big Data; Focus on the Data That’s Big. An IDC White Paper, Sponsored by Seagate, April 2017.