In today’s fast-paced landscape, where disruption is common and market volatility takes place with monotonous regularity, access to accurate and current data is necessary to ensure businesses can respond to changes effectively in the moment to remain competitive.
Being able to access to real-time data, and thus decrease business latency, is crucial to the competitiveness of financial services firms. Basing decisions on assumptions derived from old data imposes restraints on their ability to cope with sudden changes in market sentiment, deliver high-value services to customers, and manage risk exposure.
Research conducted by InterSystems shows that more than a third (35%) of European financial services organizations aren’t basing critical business decisions on real-time data, with just 8% of firms using data that is less than an hour old to make decisions. Given the constraints imposed by the traditional definition of intraday data, better solutions to managing, distributing, and deriving data are clearly required.
Financial services missing out on real-time data
The survey, involving almost 200 senior line of business leaders within European financial services firms, found the biggest data challenges are revealed to be delayed access to data (39%) and not being able to get the data in the correct format (33%) or from all the needed sources (31%).
Consequently, the overwhelming majority (92%) of European financial services firms are relying on data that is more than an hour old, with 85% relying on data that is 24 hours old or older. As a result, 35% of senior leaders report being unable to base decisions on real-time information and therefore forced to make assumptions, which may well be flawed.
There are multiple causes for delayed data within an enterprise, with the root often found in disparate legacy systems and applications that no longer connect to the rest of the organization. Typically, this causes pressure that then spirals to the IT department, where data-provisioning requests get stuck in a bottleneck. Forty-three percent of respondents also claimed they have anywhere between 25 and 100 data and application silos, an added complexity which further slows down their access to the required need.
But the use of intraday numbers, which can be up to eight hours old, no longer has a place in financial services. Instead, firms must now feed their frontline teams with real-time data that tracks events moment by moment to ensure they are able to respond to market changes and customer demands as they happen.
But delivering actionable data in real-time only solves part of the problem. Firms within the financial services sector must also go further and arm professionals with the data and analytics capabilities to predict what could happen next, through performing analytics on fast-moving transactional data, and provisioning access to those who need it.
Real-time data via smart fabric architecture
One solution that can be adopted uses an innovative architectural approach, the smart data fabric, which accesses and harmonizes data from existing systems and silos inside and outside the organization on demand, ensuring that the information is both current and accurate. It incorporates the ability to perform analytics on real-time event and transactional data without impacting the performance of the transactional system. This means firms can move away from querying information stored offline or elsewhere and equip themselves with real-time insights to drive their businesses forwards.
A smart data fabric architecture removes business latency and embeds agility by decoupling the reliance on old data derived via legacy methods. It achieves this by accessing, transforming, and harmonizing data from multiple sources, on demand, to make it usable and actionable for a wide variety of initiatives. It allows existing legacy applications and data to remain in place, ensuring one source of truth, and reducing architectural complexity. The ability to bridge silos from multiple sources, and from disparate locations, and allowing employees to access, query, and manipulate this data to deliver informed decision-making across the enterprise.
It also eliminates delays in accessing data and allows organizations to incorporate analytics on real time event and transactional data without impacting system performance. This is due to its distributed nature, and helps to eliminate errors and missed business opportunities. Allied to the enhanced flow of information, AI and ML can be utilized across the fabric to augment the decision-making process, delivering predictive and prescriptive suggestions while enabling programmatic decision-making when the use case warrants it.
Amid ongoing disruption, sudden market changes, and unforeseen circumstances, when the requirement for ever faster data delivery is an essential element of business success, smart data fabric architecture gives financial services business leaders a holistic view of the entire business at their fingertips so they can take a more strategic approach to their operations. Doing so gives the agility needed to not just survive, but thrive and gain a true competitive advantage in a volatile world.
This is a sponsored blog post by Tim FitzGerald, EMEA financial services manager, InterSystems