Old systems, new world: how to transition legacy banking systems

Customers expect 24/7 service and access, both at lightning speed. How can banks enable this through their technology? By being cloud enabled. This is not a novel approach, but how can some of our oldest institutions move from entrenched legacy systems to cloud?  

As financial institutions evolve for the digital age, becoming cloud-enabled is increasingly important for the agility, resilience and efficiency they need. At the same time, the reality is that most banks have a significant legacy of data and applications running on old platforms. So, what should institutions do about their legacy estates on the transformation journey to cloud?

Many banks run their core banking processes on legacy platforms. This means that fund accounting, reconciliation processes, record keeping, credit, and authorization processes are still running on aging platforms. This has a direct impact on the digital strategy, data availability, and the ability to personalize banking and drive modern experiences for customers. Addressing legacy technology, not only improves stability, security, and expense, but it also enables differentiating experiences for the bank's employees and customers, establishing a trusted partnership between the customer and the bank.

Unlocking the value of legacy

Of course, one of the challenges of legacy systems is that they can be costly and slow to change or update thanks to manual build, deployment, test, and integration methods. This may also affect cyber security given the increased time needed to patch, upgrade and test legacy systems as threats evolve. Yet many of these applications have considerable locked-in value in terms of the data they hold, the core functionality they provide, and the deep knowledge often associated with them.

The question, therefore, is how best to unlock this value so that it can be readily and rapidly exploited to support the bank’s wider business and digital transformation agenda. This requires a shift away from the typically application-centric nature of legacy to model a data-driven enterprise.

A nuanced approach

Fully understanding the legacy landscape and its future role is critical. If there are gaps in knowledge, they should be closed through a targeted discovery program framed against the bank’s digital vision and transformation strategy. Structured analysis of the existing IT estate is essential, with assessment of short-term and long-range business requirements, and identification of opportunities to enhance or reuse applications.

Ensuring that the latent value of legacy is unlocked and sustained requires balanced decision-making on a case-by-case basis. Not all workloads can or need to be moved to the cloud, nor should they necessarily be moved immediately. Legacy may be more easily and rapidly exploited in-situ, with associated processes optimized through targeted interventions.

Legacy treatments

When considering legacy in the context of cloud, treatments traditionally fall into six main categories:

Retire

Decommission applications that are obsolete, redundant or will become so as a result of a planned replacement or policy/process change.

Retain

Leave the application as is, either as a result of other priorities, dependencies, levels of investment, or compatibility.

Migrate

Rehost 

Entry-level move to cloud IaaS (Infrastructure as a Service) with minimal change or ‘lift and shift’.

Modernize

Refactor/ rearchitect/ replatform/ encapsulate

Mid-range move to cloud addressing some application component level concerns such as exploiting cloud PaaS (Platform as a Service) in addition to the underlying IaaS migration activity above.

Redevelop

Replace/ rearchitect/ refactor

Re-instantiate on cloud using cloud-native technologies.

Standardize

Replace/ repurchase

Simplification and standardization to an industry-standard SaaS (Software as a Service).

Making sustainable and proportionate decisions about legacy systems and data is not straightforward; setting over-ambitious targets, for example, can have a damaging impact on cloud implementation.

There are a range of alternatives to having to retire and replace legacy. Application programming interfaces (APIs) and microservices can be implemented to open up access to legacy systems; data-scraping can be used to create new data-centric platforms; and application virtualization and containerization can offer banks increased cost-efficiency and agility. If legacy applications need to be redeveloped or retired, protective measures for legacy as the System of Record may still be needed in the interim.

Outcome-based returns

The evolution and exploitation of legacy, and its associated data, is fundamental to outcome-based transformation, given that the costs and timeline constraints of legacy are critical to any cloud-forward strategy.

While cloud, as the engine for transformation, is a significant proportion of the overall cost base, it is far outweighed by the cost of people and processes. The full benefits of cloud are fully realized by reengineering and automating business processes and underpinning these with cloud and other enablers such as artificial intelligence, edge and IoT.

Measuring progress and returns on investment based on business efficiency (cost, throughput of change, quality, availability) aligned to growth and innovation are key to making evidence-based decisions for developing the right cloud strategy and roadmap.

CASE STUDY: Accelerating Virginia-based bank holding company’s journey to cloud 

Challenge 

Early on, this bank holding company recognized the opportunities to design and deliver great customer experiences using software, data and algorithms. The bank had comprehensively reimagined its talent and culture, ways of working and technical infrastructure, which included an all-in commitment to cloud. Existing on-premise infrastructure did not offer the agility, scalability, reliability, or broader ecosystem needed to turn its vision into reality. 

A transformative journey to become all-in on cloud 

Atos was a strategic partner on the journey, delivering cloud-native application development and modernization, enterprise APIs, data engineering, machine learning, and analytics which laid the foundation for personalized customer experiences. The bank embraced a broader community through open source adoption and contribution, accessing the rich world of third-party innovation through its partner ecosystem. 

The results 

In 2020, the bank became the first major United States financial institution to exit its on-premise data centers. Applications and data are in the cloud, with cross-region resiliency. As a result, the bank has gained the benefits of a more available, reliable, scalable and agile infrastructure, with success unlocking the benefits of AI and ML.