Why Financial Services Institutions Becoming Data-driven Shouldn’t be a Burden for IT Teams

  • Tim FitzGerald, EMEA Financial Services Sales Manager at InterSystems

  • 25.07.2022 10:45 am
  • #data

Becoming data-driven is an aspiration for organizations across all industries, and the financial services sector is no different. With data at the heart of their operations, financial institutions can improve everything from regulatory risk and report to providing more personalized services to their customers. However, there is currently a significant barrier standing in the way – of accessing that data.  

Research from FIMA, sponsored by InterSystems, could hardly make the challenge more obvious. Conducted among 250 financial leaders across the US and Canada, the research found that for 71% of financial services institutions, their biggest challenge to becoming data-driven is providing employees at every level of the organization with secure access to data. 

At the same time, the research found IT teams at more than half (57%) of financial services institutions spend at least a quarter of their time helping individuals across the organization to access the data and insights they require. 

Together, this points to a need for financial institutions to democratize access to data so that line-of-business teams can move forward with data-driven initiatives and reduce their reliance on IT departments. 

The wide range of current blocks on data-driven dynamism – and plans to remove them

Before examining how financial firms achieve this, however, it’s worth examining a few more statistics from the research about the current blocks on data-driven dynamism in the financial sector. They show, for example, that highly compartmentalized data remains a problem, with more than half of all respondents (54%) saying the existence of data silos within their organization is one of the three biggest barriers to innovation. Despite the long-standing acknowledgement of the financial sector’s difficulties with complex and ageing IT estates with many systems, significant problems persist.

This is why more than six-in-ten firms in the research (62%) have made improving access to siloed, distributed, data one of their top three priorities for the next 12 months. Within these organizations, employees know they have valuable data locked away in different systems and applications that are unable to communicate with one another. There is effectively a barrier between the firm, its data, and the insights that data contains.

Increasingly, financial services businesses know they must resolve their data access challenges to enable more innovative services. More than four-in-ten (44%) of respondents want to expand the use of analytics across the wider organization, for example. Four in ten (40%) say that within the next year they want to develop new applications. Yet 42% say they lack the IT resources to innovate and more than a third of financial services firms (37%) are not happy with their current data management technology stack.

Driving forward innovation

Innovation has taken on a variety of forms in the financial services industry. Self-service solutions for customers have become particularly attractive, as customers demand more ways to connect with their financial companies from home. Artificial intelligence and machine learning are also making inroads among financial firms due to their ability to make predictions and offer strategic insights into customer behaviour, fraud or illegal activity in real-time. 

As the research, reveals, financial firms are prioritizing solutions that enable data visualization, self-service, and integration. Compared with static dashboards, dynamic self-service data exploration capabilities enable business users to interactively explore the data, ask ad hoc questions, and ‘drill down’ via additional queries based on initial findings in an interactive and iterative manner, reducing reliance on IT. They also believe they could benefit by emulating or partnering with financial technology companies.

Overall, the research findings show how financial sector firms need to increase access to clean, reliable data and insights for non-specialists, enabling them to respond to new trends in demand more creatively and to make faster and more effective decisions to optimize opportunities.

The data fabric is the obvious answer

To overcome all these significant challenges, organizations should prioritize the implementation of a data fabric, using a modern, comprehensive data platform. This will draw all the different types of data together to manage them and clean them up, ready for use. A data platform will do this without creating additional copies of the data, which adds to the complexity and the responsibilities of IT. 

The smart data fabric extends this capability further, by embedding a wide range of analytics capabilities including data exploration, business intelligence, natural language processing and machine learning. Business users can continue to use the analytics and visualization tools they feel most comfortable with – and they can do it mostly on a self-service basis, interrogating live data from multiple sources in a consistent format. This makes the data fabric “smarter”, making data usable for many applications in a wide range of use cases. Data also becomes the fuel for innovation as frontline teams know they can introduce new services or financial products on the basis of data and insights that are current and trustworthy.

The smart data fabric democratizes data without adding to the mounting pressure on IT teams. It overcomes many of the barriers revealed in the research. Organizations struggling with complex, legacy systems gain trouble-free access to new capabilities that unlock information from disparate data silos, drive collaboration, and unleash the creativity and ambition of individuals right across the organization. Armed with access to better insights, these data-empowered employees will transform the fortunes of the entire organization, as the whole becomes so much greater than the sum of its parts.

Related Blogs

ISO 20022 Enhanced Data - The Golden Standard
  • 5 months 3 weeks ago 08:00 am
Data Compression Strategies
  • 6 months 1 week ago 09:00 am

Other Blogs