In this age of digital transformation, banks are significantly changing their business models, culture and operational processes. Faced by ever-changing regulations and a rapidly evolving technology landscape, banks seek to modernize and adopt service-based approaches for the core banking platform.

Decoupling has become a byword for infrastructure modernization with banks breaking up the core into its individual components and making them available as services, often through application program interfaces (APIs). However, this core-decoupling process is increasingly drilling down to the fundamentals. Instead of just opening up once closed-off systems to interested parties through interrogative APIs, banks are looking to utilize event-based triggers as well as preemptive and predictive data analysis to improve responsiveness and the overall user experience.

Legacy Lethargy

Traditionally, banks have followed a request-driven model wherein a rigid architecture defines tasks. However, the digital world brings with it the complexity of handling large amounts of data generated from millions of users and internal processes. Despite the rise in real-time analysis and smart computational algorithms, traditional data architecture cannot effectively capture, process and disseminate all relevant enterprise and external data.

Financial institutions are often hamstrung by their established infrastructure as there is no realistic expectation that mainframe cores will get replaced wholesale any time soon. Meanwhile, customers are demanding a much-improved user experience that reflects their expectations of a modern digital bank.

For many reasons, the status quo of relying on non-real-time and restrictive information sharing is unsustainable. As mainframe staffing and processing costs rise relentlessly, the digital banking phenomenon explodes with over half of all transactions originating from internet or mobile channels. Innovation is now an essential that must underpin the bank’s value proposition, yet the limitations in the bank’s underlying infrastructure often hinder the development and launch of new products and services. Clearly, this situation has not gone unnoticed, as evidenced by the fintechs who are lining up to snatch their piece of the banking pie. In many ways, banks are becoming software companies (whether they like it or not), but too often their digital product leaves a lot to be desired.

How Data Lakes Feed Event Streams

In the past few years, the concept of event-driven architecture (EDA) has been adopted as a slick mechanism to respond to changing markets, connected consumers and mobility. By using events as process triggers across a range of applications (rather than the more interrogative approach of the classical client/server paradigm), EDA brings the possibility to react instantaneously, even preemptively, to changes in circumstances to make the best use of data.

With more conventional infrastructure, systems dump data into data lakes that then need to be processed and analyzed. EDA is different. Every change in state in a core and every customer transaction creates events that are published to real-time event streams. Products, services and internal systems can subscribe to pertinent event streams and take the appropriate action instantaneously as the stream flows.

An “event” is any notable change in state that can occur inside or outside of a system that triggers a set of services, business processes and/or operations that bring meaningful business outcomes. EDA can be seen as a design paradigm in which a software component executes in response to receiving one or more event notifications. This occurs in a decoupled manner; the component that sends the notification does not know nor care about the identity of the components triggered by the events.

EDA is real time by design and can be used to build reactive applications that are event-driven, scalable, resilient, reliable, distributed and interactive. Since systems are triggered only in case of an event, EDA helps eliminate dependencies among components and lowers operating costs.

Enterprisewide Consistency and Opportunity

Efficient event-data logging and usage is nothing new, but EDA brings the opportunity to share important events across the enterprise and react instantly; all interested parties from end users to back-office operations get to respond to real-time events equally. Traditionally, information regarding events was buried in the core and only accessible through batch interrogation. Under an EDA paradigm, customer relationship management (CRM) systems, customer-facing apps, marketing campaigns, help desks, risk scoring and other ancillary services outside the core get live feeds on the events in which they are interested.

As a middleware layer, applying EDA insulates core-system processing from the rigors of real-time responsiveness and consequently greatly reduces the core’s workload – saving money and reducing risks – and it allows artificial intelligence (AI) to operate on data stores independent from the core. For example, end customers can get fraud alerts based on transaction data in real time, customers can receive automated investment suggestions based on historical behavior and current spending levels, and real-time notifications can offer instant discounts at a point of sale (POS) using loyalty points. The possibilities for creative uses of the technology are abundant.

While improved consumer services are the initial push for EDA, regulatory compliance is also becoming a data-driven discipline. Banks and financial institutions continue to struggle to comply with regulations. Issues from lack of uniformity in the Know Your Customer (KYC) process to lack of periodic assessment of vendors are all areas of potential non-compliance. With EDA, banks can respond to the real-time view of the entire enterprise across all business silos, and therefore improve risk-based decisions and positions taken.

Real-time Transparency

By becoming event-driven enterprises, banks improve their scalability and regulatory compliance. The evolution of EDA to integrate microservices or API management solutions adds another dimension to the development of a smart service-oriented architecture (SOA). Increasing adoption of the internet of things (IoT) and big data will further boost EDA in the banking sector.

New use cases for event-driven enterprises are still emerging. While retail end users are currently the most visible with real-time alert notifications, more will come for all sectors. However, at the highest level, it is the real-time view across the enterprise that is most important.

Real-time event-driven data means that the bank and its customers, as well as other interested parties, have access to timely, meaningful and accurate data that enables them to make better decisions and take action. EDA gives banks many additional opportunities for growth, and positions them as the expert and authority of that data internally for the bank’s business itself and externally for their customers.