How Banks Can Adopt Analytics on Cloud
Today, making a case for on-premise against the cloud is like arguing whether a car should be steered with the wheel or the windshield wipers. The point of analytics is to be able to see the bigger picture. With on-premise analytics silo syndrome always lurking in the wings, this is a good time to move analytics to the cloud.
Data analytics on the cloud has empowered the modern-day democratization of business intelligence. If data can be collected at the click of a button, then analytics is suddenly less about creating a model and more about serving an answer.
This shift has been accelerated by the availability of multiple cloud-based data analytics repositories and platforms, offered by cloud platforms like AWS and Microsoft Azure. In fact, as per Fortune Business Insights, the cloud analytics market is expected to be worth $86.15 billion soon, growing at a CAGR of 24.3%.
For banks and financial institutions, cloud-based analytics is a logical way to assemble the data insight, dashboards, and reporting that are standard features of business intelligence. However, certain factors must be weighed when migrating to or adopting analytics on the cloud.
Tap Into the Power of Your Data
Banks use many tools to collect and store information about their customers via customer-facing applications such as mobile banking, depositories (ATMs) analytics, credit card operations, and other back-office operations.
This information is stored in systems as diverse as enterprise resource planning (ERP), customer relationship management (CRM), call center management, core banking applications, and multiple operational data stores (ODS).
To get the most out of cloud-based analytics platforms, data from as many of these repositories as possible should be made available in one place. This is no small task, considering that financial institutions typically have multiple implementations of such applications and data stores. This adds to the complexity of achieving an information hub that delivers analytics from a single point of access to data stores.
Develop a Cloud-based Data Strategy
Since a unified data analytics system isn’t as straightforward to implement for banks as for, say, a large manufacturing facility with all its operations in the same place and on the same systems, a strategic data strategy is needed to monitor and control information.
Access control is also a key strategic concern. Data should be managed using secure applications on the cloud to ensure that only authorized personnel can access it. This calls for leveraging reputed cloud platforms like Azure and AWS to provide the security, control, and compliance standards that are key components of a data strategy.
With cloud-based analytics, banks should be able to deliver a more secure information environment while accelerating and simplifying the development of mobile banking applications.
Adoption of analytics on the cloud shouldn’t be considered a mere technical exercise. It is about, first and foremost, a cultural change. Banks may need to rewire their basic technology platforms so that data is central to business operations and users can access it at any time from anywhere.
This also requires banks to create tools for self-service reporting that are easy for business users to create and run their own reports and then deliver the resulting reports on, say, a mobile device. Plus, banks have to establish data governance standards to ensure consistency across applications and platforms as far as information accuracy, and analytical interpretations are concerned.
A data governance strategy further entails total adherence to defined procedures and codes of conduct for data quality. Complying with a wide range of standards and requirements, including encryption, fraud monitoring, and security controls, is a big challenge — something that’s easier on the cloud thanks to its inherent platform-level security measures and customization facilities.
Unlearn and Offload
“If you’re planning a migration, you don’t want to do a ‘lift and shift.’ There are workloads you can leave behind,” writes Chetan Mathur on Forbes. Migrating a bank’s standard application stacks and legacy systems to an analytics platform on the cloud is a cumbersome task.
This is because it entails offloading and unlearning numerous data-handling processes, which are very much part of the bank’s core business but negligibly contribute to the future-facing activities of its cloud analytics-enabled operations.
Therefore, an analytics platform on the cloud is often more suited to newer, better-designed applications and technology stacks. Financial institutions would need to develop such applications as part of a forward-looking technology strategy that embraces a scalable and flexible analytics platform.
Choose the Right Data Analytics Focused Partner
Since building the right technology stack is not easy, it’s best to entrust a partner with the job. The right partner should ideally have a deep understanding of the bank’s needs and requirements in the areas of reporting, API development, mobile development, monetization opportunities, and more.
Then there’s the question of whether the partner can create a solution around a cloud-based platform that integrates with existing applications and systems, as well as a comprehensive data strategy to manage, store, and access the data.
Not to forget, the partner must have deep knowledge of cloud-based analytics capabilities and deliver a solution that enables users to operate in a self-service manner. The right partner should help banks modernize and redefine how they use data to make better-informed decisions with respect to customer acquisition, retention, and profitability.
Seamlessly Adopt Analytics on Cloud with Ellicium
Taking the insights and analytics offered by cloud-based platforms to the next level, Ellicium is an enterprise-class data analytics-focused partner, enabling banks to fully automate and transform core business processes with a uniquely compelling cloud analytics experience.
Our solutions are designed to mobilize, process, and analyze data to unlock real-time insights so that you can make better and faster decisions.