The ability to analyze massive volumes of data in real time and at scale can provide organizations with a strategic advantage over their competitors. However, for many financial institutions, business users and IT teams faced significant challenges. As data volumes continue to grow, their historically on-premises solutions cannot keep pace.
Efforts to modernize data infrastructure have been slow to scale, making the financial services industry an exception to more cloud-friendly industries. For example, North American banks run only 12% of their workloads in the cloud, and in Europe it’s only 5%. Despite slow adoption and the industry’s unique data needs, there are steps IT managers can take to avoid being overwhelmed by their data, as well as processes to help modernize their data infrastructure to improve scalability as their data grows.
The first step in meeting an organization’s unique data needs is to assess the pain points. In my discussions with financial services organizations, I see these common threads:
Data silos: Over the past 10 years, we have seen an explosion of data silos as data platforms and solutions have evolved. Businesses struggle with getting the right data to the right people and ensuring the data is clean and usable. Often these data silos are created because departments within an organization use different tools to store and analyze their data.
Reluctance to modernize: Financial services institutions (FSIs) have collected massive amounts of data across multiple solutions, platforms, and legacy data formats. With different data center technology stacks, APIs, and cloud solutions blending together, data is everywhere. This chaos makes it difficult for organizations to digest their data, or even begin to plan an effective transition to modern cloud-based architectures.
Cloud Barriers: Cloud-only solutions leave ISPs clueless, as they are forced to either jump into the cloud, which can be an expensive proposition, or stay behind and risk being left behind on-premises. A drastic push to the cloud is not a viable option for highly regulated companies that handle a lot of sensitive consumer and business data.
These pain points signal the need for financial services organizations to start modernizing their technology stacks, starting with their data warehouse, as there are currently several solutions that are being phased out, namely SAP IQ and IBM Netezza. While these technologies have served their purpose, they both miss the mark by providing enterprises with a highly scalable solution capable of operating across multiple clouds and on-premises – a critical requirement in today’s age of advanced analytics. today.
Moving to a more modern data stack doesn’t mean everything has to go away. What works well is planning for incremental change. A good starting point is an organization’s data warehouse, as it is a critical tool for many business functions. IT leaders should identify 2-3 use cases that will improve business value as a result of modernization – such as accelerating month-end book closing – and secure management buy-in. During this transition, it will take time, and that is perfectly fine.
The cloud will play a critical role in any transformation effort, but it’s critical not to rush into the cloud because a cloud-only model has potential downsides, including cost and vendor lock-in. The organization should focus on on-premises modernization first and then transition to the hybrid cloud deployment strategy, which should encompass multiple cloud providers.
As ISPs work to determine the next steps to achieve a modern data stack, here are some tips and best practices to ensure data remains flexible, accessible and actionable for business decision makers:
Choose your battles: Choose small, winnable points of proof as you modernize and grow your on-premises and cloud operations. Your approach should be iterative and constantly improving.
Adopt the right solution: For many players in the financial services industry, a hybrid approach to data warehousing will be the best approach, as it gives an organization the flexibility to keep workloads on-premises as well as across multiple clouds to leverage best of both worlds.
Building a “Bank of the Future” mindset: Your data ecosystem is more than your own business analysts and data stewards, it’s also your customers. Start thinking about data warehousing in a new light where it directly delivers near real-time information to your customer base. This mindset will be key to unlocking new scalable data opportunities.
Establish a common understanding: Agreed-upon semantics and workflows are key to developing your organization’s own data culture. Align your data needs and goals with business leaders and data stewards for optimal success.
Don’t wait for the cloud: You don’t have to wait for the cloud to modernize. You can start your modernization journey here and now on site.
With the ensuing cloud expansion in the financial services industry, we are poised to move from legacy data solutions to a hybrid approach to data across FSIs. This transition to the cloud will allow ISFs to renew their data governance framework and develop their own data cultures. In this new era, organizations must embrace flexible, dynamic, and resourceful new technologies to prepare for success.