August 10, 2021

Top 6 Challenges Legacy Systems Pose to Digital Transformation in Banks

August 10, 2021

Top 6 Challenges Legacy Systems Pose to Digital Transformation in Banks

“By 2030, 80 percent of heritage financial services firms will go out of business, become commoditized or exist only formally but not competing effectively”, predicts Gartner. While digital transformation has become a priority for banks, they face multiple challenges such as workforce training, change in processes, etc. on that route. And perhaps the biggest bottleneck to digital transformation is the legacy banking systems used for managing banking operations and customer relations.

Top 6 Challenges That Legacy Systems Pose to Digital Transformation

1.    Silos in operations

Gillian Tett, the editor, and columnist at the Financial Times cites information silos as one of the reasons costing banks billions. Legacy IT systems were designed in such a way that there were separate systems developed or purchased to meet the needs of each department or banking function. This led to silos between different bank functions. The fragmented system led to friction in customer experience. Different teams would also lose out on critical customer information due to gaps in information transmittal. Digital transformation requires data to flow into a unified system seamlessly from different functions to generate actionable insights. Silos between the departments and systems cause impediments and hold up benefits of the transformation process.

2.     Missing Fintech integrations

Banks are aware that third-party integrations are essential in today’s times. However, they are still using legacy core systems that are ill-equipped to manage third-party integrations or onboard new applications and partners. They are unable to offer innovative offerings such as banking-as-a-service (BaaS)that uses application programming interfaces (API) to integrate with third-party services, which could help them gain a competitive advantage. The architecture of these systems is such that upgrading the systems becomes time-consuming. There is so much dependency on core systems that integrating with modern systems and processes could create roadblocks in the digital transformation process or lead to failure.

3.    Limitations in features

Today’s customers, expect the same level of experience from banks as they get from the apps of the big tech companies. They prefer highly intuitive mobile-first features that allow them to transact on the go and to get quick resolutions to their queries. Legacy systems make it very hard for banks to support breakthrough features such as chatbots, API-based integrations to third-party products, etc. The legacy core banking systems are built on monolithic architecture. This makes it difficult for banks to add new capabilities or customize them. The systems are also rigid and hard to quickly adapt to changing customer and compliance needs. Digital transformation can happen only if banks shift to using modular architecture such as microservices.

4.    No real-time transactions

Customers are accustomed to receiving real-time updates of payments, delivery schedules, etc. These updates are a hallmark of a good customer experience. However, legacy banking systems still have some catching up to do. These systems often process transactions in batch mode. So, customer’s balances are updated only periodically. Banks need to re-architecture their entire system and build real-time offerings and capabilities to deliver on the promise of digital transformation.

5.    Poor governance and changes in the regulatory framework

Regulations change frequently and the banking systems must be dynamic enough to adapt to these changes Legacy systems are poorly equipped to handle such changes. They are not built for dynamic regulatory frameworks, nor do they possess capabilities to generate reports in multiple formats. Such shortcomings create obstacles for banks to comply with the regulations. Another challenge that banks face is data governance. Banks have access to a gold mine of customer data. However, it’s hard for them to utilize the data fully because the legacy systems make it harder to clean, validate, standardize, and deduplicate the data.

6.    Impact on customer experience

Although banks have been trying to become more customer-centric and digitalize their offerings, they are still not future-ready. Banks are increasingly facing competition from fintech companies. The limitations in legacy banking systems and deeply entrenched archaic backend processes have created many roadblocks. For example, the monolithic architecture of the system is not agile methodology-friendly, due to which banks are unable to pivot quickly. Similarly, the lack of real-time data capabilities has stopped banks from utilizing their data's full potential and offering tailor-made offerings to customers.


Digital transformation is an ongoing process as customer demands evolve, competitors come up with innovative offerings, and compliance rules and technologies change. There will also always be new risks and challenges. Banks must be prepared for such changes. However, modernizing legacy systems is not an easy solution. Banks need to ensure that the process of systemic change is completed quickly, comprehensively, and without compromising the customer experience.

Digital transformation requires careful planning and implementation. Banks should consider following for upgrading their core banking system.

  1. Create a roadmap for overall modernization of the bank that is aligned it with the vision of the bank.
  2. Identify key metrics that measures success of the transformation.
  3. Focus on modernization of high priority areas for the core systems instead of the replacing the complete system.
  4. Documenting all the functional knowledge and technical knowledge around the core banking system. Conduct training to ensure knowledge is not limited to few people.
  5. Expand your core team consisting of domain experts, data specialists, tech team and operations.
  6. Cleanup of data and gear up for migration. Ensure quality of data is good. Watch out of duplicate records, inactive customers and users and data inconsistencies.


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