Mainframe systems can be defined as old and outdated IT systems that are still in use by many banking organizations. These systems developed on the mainframe technology and using languages like COBOL in the 80s and 90s are now becoming outdated. With the ever changing customer needs and emerging markets, banks have to update their back-end processes.
Why Modernization is Critical
Banks cannot afford to stay static with their legacy systems for the following key reasons:
1. Meeting Changing Consumer Demands
Today’s consumers expect seamless digital banking across channels like mobile, web, and social media. Legacy core banking systems often lack APIs and microservices to enable omni-channel delivery. Upgrading core systems is vital to meet modern customer expectations.
2. Enhancing Operational Efficiency
When it comes to manual operations and the batch processing of outdated systems, the result is slowness, mistakes, and high costs. Cloud, AI, and blockchain are some of the new technologies that assist banks in increasing efficiency, reducing expenses, and expanding more rapidly.
3. Launching New Products
Applications that are built using large mainframe systems with intertwined code are extremely difficult to use to quickly bring new products to the market. The use of modular architecture, open APIs, and DevOps allows banks to try and launch innovations quickly.
4. Managing Risk
Old systems are exposed to cyber risks, and there is no advanced fraud mitigation system. The idea of modernization is vital in the enhancement of data security and meeting the set regulations.
5. Gaining Competitive Edge
Innovative digital players and new generation challengers are winning customers with better digital services and extreme personalization. Many traditional players require some technological touch-up to remain competitive in the market.
Thus, it can be concluded that legacy modernization is one of the most important strategic initiatives for incumbent banks at the present stage.
Challenges in Transitioning from Legacy
Transitioning entrenched legacy platforms to modern architecture is, however, riddled with significant challenges:
High Costs
Over the years, massive investments have been required to dismantle and replace complex, interdependent legacy systems. Return on investment is unclear upfront.
Execution Risks
Such large-scale programs are prone to cost/time overruns, vendor issues, skill gaps and migration failures, putting business continuity at risk.
Process Disruptions
Business processes are tightly wound into legacy systems, so transforming technology layers can impact operations, reporting, integrations, etc.
Cultural Inertia
People accustomed to legacy ways for decades resist adopting modern tools and processes – a key adoption barrier.
Banks hence need a well-charted roadmap spanning years to retire legacy estate progressively while minimizing business disruption.
Key Pillars of a Legacy Modernization Program
A structured modernization program should encompass five foundational pillars:
1. Core Banking Transformation
The core banking system is the heart of backend operations. Its renewal to a flexible, componentized architecture enables new products, channels, insights and experiences.
2. Data and Analytics Upgrade
Liberating data locked in legacy siloed into an enterprise data lake in the cloud allows building 360-customer-view, machine learning use cases and robust reporting.
3. Digital Channels Growth
Exposing core banking via modern APIs facilitates omnichannel experience across mobile, web, social and conversational interfaces.
4. Infrastructure Revamp
Moving to compute and storage from legacy on-prem data centers to cloud platforms brings scalability, resilience and savings.
5. Organizational Realignment
Reskilling people, instilling a DevOps culture, making contractual changes, and creating new operating model designs are necessary.
Banks who have succeeded in transforming have invested systematically across the above streams.
Key Technology Enablers
While each bank would evolve its own transformation roadmap based on context, some pivotal technologies form the core:
Cloud Computing
Cloud’s consumption-based pricing, infinite scale and pace of innovation make it the preferred deployment model over legacy data centers.
Microservices Architecture
Breaking business capabilities into independent microservices versus monoliths brings agility. Kubernetes containerizes them for resilience.
APIs and Event Streaming
Exposing functions via APIs allows building new apps faster. Event streaming pipes data in real-time between microservices.
DevOps Culture
Cross-functional teams, lean workflows and automated toolchains help deliver changes rapidly and reliably.
Data and Analytics
A central data lake, machine learning models and visualizations unlock embedded business insights.
Agile Development
An iterative delivery model with continuous testing and customer feedback accelerates the build-measure-learn cycle.
This new-age technology stack sets up banks for innovation and growth.
Key Migration Strategies
Banks can consider five strategies to decommission legacy platforms:
- Replatform (Lift-and-Shift). Rehost legacy applications, such as a mainframe, onto cloud infrastructure without code changes using containers and emulators.
- Refactor (Re-architect). Rebuilding monoliths into cloud-native microservices code without altering functionality to benefit from new infrastructure.
- Rebuild (Rip-and-Replace). Fullydiscardg legacy application code and rewrite everything from scratch on modern tech stack fit for the future.
- Retain (Incremental Change). Keeping legacy systems as-is but transforming data, dev processes, channels and products piecemeal around the edges.
- Retire. Switching off legacy applications that bring little business value and reinvesting in strategic priorities.
Each legacy system would warrant its own transition path based on factors like risk, value and interdependencies.
Key Steps in Program Execution
While strategies may differ across legacy systems, the programmatic steps are consistent:
Set Vision and Goals
Define a long-term target vision aligned to business strategy, and quantify goals around key metrics like time-to-market, cost savings, uptime etc.
Audit and Plan
Conduct application portfolio analysis detailing pain points, risks, value, change complexity and mappings. Create a multi-year execution roadmap.
Start with Quick Wins
Deliver some early wins by tackling straightforward, high-value changes fast to build credibility before longer migrations.
Continuous Communication
Keep all stakeholders updated on progress through multiple channels to secure sustained buy-in.
Measure Outcomes
Monitor metrics defined upfront to validate technology and process changes to deliver expected business benefits.
Course Correct
Expect some objectives or timelines to shift. Analyze gaps, learn and fine-tune plans regularly based on outcomes.
With this structured approach, legacy modernization programs have the rigor and flexibility to succeed.
Real-World Examples
Some inspirational case studies of banks rearchitecting legacy estates include:
BNP Paribas
Europe’s largest bank built a greenfield cloud platform for retail banking named One Bank. They progressively migrate customers across countries onto One Bank even as legacy systems retire.
National Australia Bank
NAB adopted a sweeping “Simplify and Sync” strategy to exit 10 legacy systems and shift to a modular architecture. Over 5000 applications are now consolidated into around 500.
DBS Bank
DBS embarked on a multi-year mainframe migration initiative in 2019. They re-platform batches to the cloud, retire apps, and transform data and channels.
Conclusion
While daunting, legacy modernization is inevitable for incumbent banks today to offer differentiated digital experiences amidst competition. A phased migration focused on business capabilities over technologies using agile methods is key to de-risk this journey. With leadership commitment and endurance, banks can systematically transform legacy constraints into catalysts for innovation.
