Core Revival for Legacy Banking Systems: Why is it Important? 

Finance leaders considering modernization can finally look beyond large-scale migrations

Legacy systems are machines of the past, still capable of leading us into the future. This is mainly because it has worked as a base for data processing and data generation till now. These can easily be migrated to newer platforms but, let's see whether it is worth the cost.


To answer this, Modernization is a buzzword used by big Banks looking to compete with innovative Fintech disruptors. In sync, instead of migration, a few additions to legacy systems can better transform the output for business intelligence and data inclusivity.


Also being termed ‘Core Revival’ – the process explores the benefits of cloud implementation, Artificial Intelligence (AI) and Machine Learning (ML) system additions, automated Big Data sourcing tools, and Blockchain. These have immense potential in the long run, but we are just getting started and are yet to see the extent of their power.


Though in the process of exploration, we are realizing that along with systems for newer types of data we need infrastructure that easily accommodates arriving technologies.


Future-Readiness for New Infrastructure and New Data


To avoid the mistake that made legacy systems a burden, a newer trend professes the adoption of flexible, web-based data management and analytics solutions. These solutions are deployed directly through the cloud or are offered with Software as a Service (SaaS) subscriptions.


Core revival initiatives introduce leading-edge technological changes into existing IT ecosystems. Here, technology teams can account for risks when old and new technologies intersect. Here, close collaboration with data operations teams helps anticipate and manage risk in a manner that doesn’t hamper growth in current and future situations.


With current-day deployment methodologies, finance leaders considering modernization can look beyond large-scale migrations.


For example, when it comes to large cloud vendors, a common practice is to move one component at a time. Moving existing systems to low-code platforms promotes cost-neutral, easily-adaptable options for establishing a future-ready foundation within core systems.


The Pandemic Push: Where is Modernization Headed?


Even as we get back to the new normal, the accelerated rate of business transformation, read: digitalization, will stay the same. Along with promoting a collaborative ecosystem, businesses have realized the importance of preparing for disruption.


Since replacing existing systems are the costliest modernization taking place, new-age alternatives of cloud-based systems have come to the forefront. Banks can now deploy systems quicker, increase scalability, and magnify analytical capabilities cost-efficiently.


Here we see how real innovation isn’t about the next best thing; it’s about developing an ecosystem that supports continuous innovation. Let's take a look at a few functions of modernization that are preparing businesses for improved banking in the digital age


Cloud Systems for Simplified Collaborations


Migrating major systems to a cloud helps Banks and FIs to share business functions easily. Cloud-based systems increase the capacity to collaborate with data and also allow partners to use their business models and offer their services using APIs bringing forth the newest shift towards the prevalent use of Banking as a Service (BaaS).


For a smooth transition, banks can decide whether to approach the migration through any one of the two possible migration methods – the lift and shift model and the transformation model.


Either way, businesses have to be meticulous in the selection of the offerings from their cloud provider, which are –

  • Software as a Service (SaaS) – Applications that end users can access through navigators, browsers, and web interfaces using Internet protocols.

  • Platform as a Service (PaaS) – A container within a programming environment, libraries, and tools that support the application developments.

  • Infrastructure as a Service (IaaS) – Virtual machines, storage memory, database service, and network components.

Integrated Data Systems with Revamped Architecture


Banks need teams that understand and make use of the democratization of analytics. Well-planned solution architecture helps with democratization – which means data is made available at multiple levels, for those who have the skill sets to derive meaningful insights.


As all big data analytics is driven by metadata; all records are linked based on combinations of attributes within the data. Using statistical techniques for integrated systems, collective entities are identified and collapsed to produce single views of vast datasets through a single interface.


Insight Generation from Reconstructed Data Flow


Insight-generating systems using AI/ML provide actionable data for mandatory regulatory reports like IRAC Norms, Ind AS Reporting, and IGAAP Reporting. Automation of multiple data collection processes is teamed with automated data processing for these insights.


Systems modernization for insight generation requires integrated solution architecture consisting of seamlessly interconnected internal and external data sources for Transactional, Financial, and other Big Data.


In building a Data Lake to store and channel data flow to respective teams, Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Programming (NLP) are important additions. These manage data with automated sourcing, cleansing, insight generation, and submissions.


Get in touch with D2K Banking Fintech Consultancy Experts for more information on roadmaps for deploying technologies for comprehensive data analytics.