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Data modernization in banking takes on new urgency

Data Modernization in Banking

Data modernization in the banking sector takes on new urgency as regulatory pressure and regulatory changes continue to increase the complexity and cost of maintaining legacy systems. In order to reap the benefits of data modernization in banking, banks must make several decisions. Some of these include reducing risk, improving customer experience, preventing cyber-attacks, and utilizing big data for fraud detection.

Data modernization is the key to change and innovation

Application modernization can take many forms, but for financial institutions, data modernization is more important than ever.

Data modernization is not just about putting in systems to ensure compliance, but it can also be an investment in innovation and better products. For example, banks are increasingly using data to help them reduce costs and deliver better products and services. This is because banks are moving away from reporting financial value alone and are incorporating ESG (environmental, social, and goververnance) into their data. This makes data modernization an investment in bank innovation, efficiency, and governance.

With the growth of ESG and other societal values, financial institutions are taking their data modernization investments to the next level. For example, by leveraging Oracle Financial Services Analytics, KeyBank can now analyze data in their digital banking platforms to make informed decisions about investments and risk.1 With the ability to monitor data in real time, KeyBank’s bankers can compare the total income of a loan against its credit exposure. A mobile app allows KeyBank’s customers to review transaction histories, balances, and bills.

Regulations are forcing organizations to change and innovate, and data modernization is the key to doing just that. New regulations require more granular data and increased frequency of submissions. Digitalization and cloud adoption programs are gaining ground in BFS organizations, which means that data modernization should be at the heart of the organization’s transformation. And the right approach can help financial institutions realize their business value.

For banks, data modernization is about building new systems that will enable better innovation and better products for customers while ensuring compliance without risks to security. The data modernization process has been slow for decades, particularly in the risk and finance functions. This has largely been to banks sticking to their tried and tested technology infrastructure including legacy systems instead of embracing newer technologies.

Phased transformation can deliver results

When implementing a new technology platform, a bank’s executive team should prioritize the project based on quick wins, such as increased revenue and reduced enterprise-wide risk. The process should be phased to meet the bank’s priorities.

Banks are reinventing themselves to meet the demands of their customers, cope with changing regulations, and compete with pure digital fintech challengers. Some banks now recognize that they can play a more significant role in their customer’s financial life by embracing data transformation. However, while bank transformation can be challenging, it is possible to experience huge gains over your peers who are relying on legacy systems.

As the world becomes more connected and consumers become more aware of new technologies, banks must harness the wealth of data available. The advent of open banking has made it easier to gather data from new sources and specialized databases. New technologies will also enable augmented relationship managers to access a variety of artificial intelligence tools. By embracing these tools, banks can deliver personalized service to their customers while reducing costs. In short, adopting new technologies will make banks future-proof and open new revenue streams.

While core banking system modernization is never simple, it is the first step in a successful transformation. It begins with defining your goals, customer needs, and the regulatory environment. Then, you need to identify the core system functionality and determine the target operating model and IT architecture. In the end, a modernized core banking system will transform your entire business. This process is an investment and requires a significant investment.

Data enables customer-centric banking

Banks need to offer better customer-centric services than competitors. Banks have a huge database of data about their customers and can aggregate this information to create a better customer experience. And, with more data available online, banks can become even more relevant to their customers. This approach can improve the bank’s performance and control costs.

Banks need to become more personal. Using data on customer behavior is essential to creating unique end-to-end journeys for customers and expanding wallet share. This means personalization is crucial to banks in the digital era. It is a trend that digital banks are increasingly adopting, with 83 percent saying customer centricity is driving key decisions.2And most digitally-aware banks expect to increase their investment in personalized experiences.

Big bang data modernization vs incremental data modernization

While big bang data modernization is less complex and less costly than a gradual approach, it has disadvantages as well. It involves a lot of downtime and costly failure, and it might not be suitable for mission-critical applications. Big bang implementations should be undertaken only when the overall project can be done quickly and safely, and with as little disruption as possible. For this reason, banks should avoid big bang conversion if at all possible.

Core banking modernization can be challenging for many reasons. Some of these include the risk of critical operational disruptions, as well as the costs of retooling the entire infrastructure. However, it is possible to avoid major disruption by employing “core pre-modernization.” Core pre-modernization can apply to an older core banking system and address both systemic and procedural requirements. It’s also possible to combine both approaches, so it may be beneficial to adopt a hybrid model.

By embracing change and modernizing the data landscape, organizations can redefine their business and embrace change, which is crucial for success.

While core platform modernization becomes easier each year, it is still a major undertaking and not without risk. In the past, big bang modernization involved setting up a new platform next to the existing one, transferring data over the weekend, and then flipping a switch to turn on the new system. This approach failed so many times that it became a stigma against core modernization. Instead of embracing the change, many banks continued applying patches to their old platform.

While the big bang approach is an absolute necessity, it may not be feasible for many organizations. The incremental approach, on the other hand, is less risky and can be undertaken incrementally over time. One approach involves the creation of a modern digital bank, which runs alongside existing core banking systems. Then, the bank can gradually move its customers to the new digital system. Despite the risk, a bank may choose to go with the incremental approach.

What Relevantz Can Do for You

Relevantz can be the partner you need to help you along your application modernization and digital transformation journeys. With our business-first, outside-in modernization approach, We can help you rehost, replatform, refactor, rearchitect, rebuild, and replace your current enterprise systems, separate the applications from legacy infrastructure, modularize intermingled business processes, liberate data from legacy systems, and innovate new digital systems.

And because our approach is iterative, your enterprise will be able to enjoy all the benefits of new information technologies, such as having the agility to adapt quickly to the demands of the marketplace, while keeping your legacy systems humming behind the scenes.