Information Week’s Bank Systems and Technology blog shared 3 best-practices that can reverse the data dilemma and help realize the full potential of application modernization projects in banking.
Why Are Banks Engaging in Application Modernization?
Mergers and acquisitions, consumerism, and digitization have exploded application portfolios in the banking sector. In turn, application diversity and redundancy have increased dramatically, creating a huge technology debt for IT and lines of business alike. Aging, poorly utilized, core banking applications have dragged along a growing cost burden, including unsupported hardware, software, and specialized labor. Legacy systems, pre-dating the onslaught of new banking regulations, have also introduced huge costs in meeting compliance requirements. A study by IBM suggests that the inflexibility of legacy systems costs the banking sector $200 billion annually and erodes roughly 20% of pre-tax profits.
[Why aversion to conversion is bad for your bank: The Truth About Core.]
Not surprisingly, modernization of core systems has been top of mind for bank IT executives. But are these modernization initiatives delivering on the promise of lower costs, faster innovation, and streamlined compliance? In fact, the potential gains are very real, but the cost and complexity of modernization projects eat into the returns. Solving this dilemma requires recognizing that infrastructure and application modernization is only a means to the end goal: faster data access and delivery to developers, testers, business analysts, or other information consumers. But data is, ironically, both the ultimate reward and the biggest barrier to maximizing returns on modernization of core banking systems. To that end, here are three best-practices that can reverse the data dilemma and help realize the full potential of modernization projects in banking:
1. Enable data as a service
Core system modernization projects are multi-year initiatives that are also highly data-intensive in nature. Development, QA, integration, training, and other environments are needed for each application being modernized. Moreover, there is a constant need to move data back and forth across project environments. For example, QA or test systems must frequently refresh their data from production systems to maximize the quality of testing. While virtual infrastructure can be spun up quickly, moving large datasets across application landscapes can take days to weeks of coordinated effort across several IT teams. Emerging technologies that virtualize application data can wipe out 90% of the infrastructure and operational overhead in data management. In doing so, these solutions enable data-as-a-service and can double the pace of modernization initiatives while simultaneously cutting cost and risk.
2. Eliminate cross-team dependencies
Internal IT resources almost never have the bandwidth to take on large-scale modernization projects. Staff augmentation through system integrators or other specialized services partners is inevitable. But this introduces long wait times and cross-team dependencies. For example, the modernization project team may be ready to re-test migration to a modernized application test stack, but the internal operations team may not be able to provide access to production data due to peak usage cycles or other constraints. The constant dependence of modernization project teams on internal operations teams is a perennial source of conflict and project delays. What if a space-efficient, synchronized, virtualized instance of production data could be made available to the modernization project team at all times? Look to data-as-a-service-enabling technologies to decouple the reliance of project teams on production operations teams.
3. Address compliance requirements early
Compliance poses one of the biggest roadblocks to application modernization in banking. Many core banking systems are subject to a growing number of regulatory requirements. While aging application infrastructure can be readily decommissioned, the underlying data often has to be retained for years to ensure compliance and audit readiness. Slow recovery of retired data with text-based archiving solutions only adds to the push back. Ultimately, the full cost of legacy applications is sustained for extended durations, and the return on modernization initiatives is not realized. What if entire application stacks (including application binaries, configuration files, database data, etc.) could be efficiently archived and restored in minutes? Demonstrating efficiency in archival and ease of recovery can accelerate modernization projects by eliminating push back from legal and compliance teams.
Easier said than done? Not really. The technology landscape is evolving faster than ever. Over the past decade, infrastructure agility and efficiency has been transformed through server virtualization, private cloud platforms, etc. Today, many banks can claim to have enabled infrastructure-as-a-service (IaaS). That leaves data as the remaining bottleneck to milestone gains in agility, efficiency, and quality. Banks that embrace application modernization solutions enabling data-as-a-service stand to gain a clear competitive advantage.