A sizable portion of the nation’s economy—$5.4 trillion, to be exact—is driven by financial service providers. Even financial giants face challenges from legacy financial systems powered by outdated technology, affecting community credit unions and multinational conglomerates.
Born in a bygone era of technology, legacy financial systems are riddled with operational inefficiencies, security vulnerabilities, and limited integration abilities that ultimately restrict the customer experience. In the ever-evolving financial landscape, let’s explore these systems more deeply, demystifying their challenges and navigating the path to modernization.
What is a Legacy Financial System?
Legacy financial systems refer to mainframe-based platforms, like computer software or hardware, that remain operational within financial institutions, such as banks, credit unions, and financial service providers. Often, a suite of decades-old, outdated technology legacy core systems support an organization’s back-end functions, including account management, loan processing, and more.
These systems—some dating back as early as the 1950s—were revolutionary in their prime. The archaic Common Business-Oriented Language ( COBOL) programming language used to design them only restricts an institution’s ability to deliver the modern experience customers expect with the heightened security customers demand. In other words, legacy financial systems have become obstructive and obsolete.
Built for a predominantly analog age, legacy systems continue to struggle in today’s digitized finance world, which is now dominated by online transactions, mobile banking, and cloud computing. At a time when most legacy core systems are increasingly out of touch with current consumer preferences and compliance regulations, a system overhaul is likely overdue.
Challenges Posed by Legacy Financial Systems
The biggest challenge in financial institutions, as voted by financial services contact centers, is poor technology. When you consider that they might be as old as the organization itself, the fact that legacy systems are ineffective is no surprise. For instance, batch processing, typical in older systems, cannot match the real-time processing and modern agility capabilities of newer platforms.
The operational inefficiencies of legacy financial systems are also intrinsically linked to security vulnerabilities. Banks, credit unions, and other financial organizations are already 300 times more likely to be targeted by cyberattacks. Due to their age, systems like COBOL databases may not support the latest encryption standards, making them even more susceptible to hackers.
Moreover, integrating antiquated systems with newer applications, like contemporary CRM software or mobile banking apps, often requires makeshift solutions and manual bridging, leading to potential data silos. Such integrations also incur higher maintenance costs, as finding experts familiar with older programming languages and outdated hardware can be challenging.
Not to mention, it can take between 12 and 24 months and upwards of six figures a year for a financial institution to implement fundamental changes to its tech stack. For organizations with intricate internal structures and rigid workflows, this inflexibility inhibits the adoption of modern technologies, such as real-time data analytics and AI-driven customer service solutions.
The Case for Modernizing Legacy Financial Systems
Legacy financial systems are increasingly incompatible with modern processes, preferences, and policies, creating a strong motive for modernizing legacy systems in banking and financial services. Contemporary systems offer features like automated workflows, AI-driven predictions, and instantaneous data access, significantly accelerating operations and enhancing efficiency.
Likewise, there are notable cost savings when transitioning from outdated technology to cutting-edge solutions. While there is an initial outlay in migrating from, say, a mainframe to a cloud-based solution, the subsequent savings from reduced downtimes, lower energy consumption, and minimal manual interventions can offset and optimize operational costs over time.
Similarly, modern platforms come fortified with multi-factor authentication, real-time threat detection, and advanced encryption protocols that ensure stringent data protection and improved security posture. These security measures enable organizations to easily integrate customer satisfaction-boosting technologies, from blockchain in transaction logging to AI-assisted service personalization.
Making the Transition: Best Practices for Modernization
Legacy financial systems have long been a hindrance to elevated customer experiences and enhanced operational efficiencies. With the average customer churn rate in the financial services industry skyrocketing to over 25% in 2023, there’s no better time to adopt these best practices for modernizing legacy systems, from assessment and strategy development to continuous training.
1. Assessment and Strategy Development
The first step to overhaul legacy systems in financial institutions is to map the existing infrastructure along with the steps it will take to resemble a modern bank. For example, if your institution still uses mainframe computers, identify the processes dependent on them and plan a transition timeline. Be sure to engage all stakeholders, from the COBOL programmer who maintains the old database to the CEO, ensuring everyone’s on board and understands the change’s magnitude.
2. Choosing the Right Technologies
Once you’ve outlined your core banking systems, consider which modern alternative best suits your needs. Based on the sustainability of your legacy platform as well as the complexity of your data, you’ll likely choose between a service-oriented banking platform, a cloud-native fintech solution, or a hybrid infrastructure that leverages the best of both worlds. As you research various solutions to support your core financial functions, review the primary differences between your options:
- Service-oriented platforms are designed around a service-oriented architecture (SOA) and typically feature a license- and subscription-based model. They’re offered as hosted software-as-a-service (SaaS) solutions and enable real-time data processing.
- Cloud-native platforms are built with application programming interfaces (APIs) that support a microservices-based architecture of internal and external functions. They feature a pay-per-use subscription model and enable highly scalable infrastructures.
3. Continuous Training
Banking and financial customers generate 2.5 quintillion bytes of data daily, meaning financial institutions ultimately spend over $67 billion on their core banking systems per year. To ensure compliance and customer satisfaction, team members must be trained on how to manage updated banking platforms or cloud technology. As you migrate, say, from COBOL to Python or from mainframes to cloud servers, offer training modules to help staff adapt and maximize the new tools.
Elevate the Financial Experience with arrivia
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In this era of innovation, why limit change to just systems? Envision a landscape where every transaction isn’t just a financial interaction, but a step towards unparalleled travel experiences. Elevate your offerings, enhance client loyalty, and seamlessly merge finance with adventure through arrivia’s white label travel portal and turnkey rewards technology.
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