In today’s age of hyper-personalization, banks and financial institutions are constantly adopting new technologies serve customers better. The need for superior computing prowess is seeing the emergence of edge analytics.

But what is edge computing? Gartner defines edge computing as solutions that facilitate data processing at or near the source of data generation. Instead of bringing data to the Analytics, we need to bring the Analytics to the data. The model pushes computing applications away from centralized nodes to the edge of data networks, leveraging device resources that are not connected to the network.

Cloud to the Edge

With digital transformation, banks and financial institutions have rapidly adopted cloud technologies for storing and processing large amounts of data. This has constrained the cloud infrastructure with massive data loads and congestion. Hence, edge analytics is growing as an alternative to big data analytics and is poised to take over cloud data-mining analytics. A major objective of edge computing is to provide the benefits of cloud computing and big data processing while minimizing the use of an organization’s IT infrastructure. For instance, instead of installing ATMs, banks are placing interactive kiosks to deliver an omnichannel banking experience along with conducting financial transactions. Virtual reality and augmented reality technologies are being explored to enhance the customer experience. Financial service firms can utilize real-time data generated from edge computing to create a single customer view.

Edge computing follows a topology-based computing model to enable and optimize decentralization. The model places nodes closer to the data sources resulting in reduced latency and localized data traffic. Unlike cloud computing, edge analytics computes data in real-time on edge devices instead of sending data back to the cloud for computing. By carrying out computing closer to the edge of the network helps in analyzing data in real-time – crucial for data-driven decision making in the banking sector.

Gartner research revealed that only 10 percent of enterprise-generated data is created and processed outside a traditional centralized data center or cloud. By 2025, it is expected to reach 75 percent. The rise of edge analytics is attributed to increasing adoption of the internet of things (IoT) and the requirement of workplace performance enhancements. For instance, the Commonwealth Bank of Australia (CBA) is testing end-to-end banking solutions with 5G banking and edge computing. The system has the potential to enhance the availability, stability, and performance of CBA’s network infrastructure and support a range of software-defined networking solutions.

The major benefit edge computing offers is the ease of scaling operations with each new device that is added to the system. For example, banks are empowering their staff with smartphones or tablets to provide personalized service to customers at the branch, reducing wait time and increasing efficiency.

Insights from edge analytics help banks in understanding their customers better. Using location-based suggestions and customer recommendation banks can deliver transactional behavior in real-time. For example, banks can collate anonymized data (via mobile apps and near field communications technology) to create personalized signages to cross-sell products. This edge-to-edge intelligence addresses the near real-time computation needs of the digital landscape and provides a seamless user experience.

The recent introduction of GDPR, edge computing addresses the issues of storing data on the cloud. In edge computing the data is stored onsite, giving banks control of user data enabling better data security from reduced risk of data loss and theft.

Continuing growth

According to Market Research Future’s (MRFR) recent report, the global edge analytics market is predicted to reach $11 billion by 2023. Moving forward, a key question to address is how the industry adapts to edge computing pertaining to infrastructure, operation, integration micro-data centers, and decentralizing public cloud footprint. Currently, the downside to edge computing is the lack of platforms that can handle machine learning on distributed, federated data. Organizations can look at a hybrid edge-cloud solution to deliver fast experiences to customers and provide the flexibility to meet industry requirements. With the proliferation of IoT, the introduction of 5G networks, and the increasing amount of data generated from connected devices, edge computing has the potential of disrupting banking industry and integrating latency-sensitive microservices.

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Digital transformation is the order of the day everywhere with most businesses talking about going digital. However, a majority of them don’t realize that it encompasses processes far beyond just upgrading to the latest IT system.

Businesses must realize that in order to be a digital business in its truest sense means more than just adopting new technology. It’s all about taking the right advantage of the waves of transformation surrounding us. According to a recent research by McKinsey Global Institute (MGI), after looking at the condition of digitization in sectors across the U.S. economy, it was found that there is a growing breach between sectors, and between companies within those sectors. Companies that have digitally transformed themselves have witnessed an enormous growth in productivity and profit margins.

Banks and other financial institutions are contemplating renewing their core systems with digital technology, realizing that their legacy technology will not be able to support their changing needs and will have to be changed in the next few years. But digital transformation in the banking and financial sector isn’t as easy as it sounds. Banks will have to implement a more flexible banking platform on top of the traditional core banking system in order to achieve complete digitization.

Digital core: How does it lead to digital transformation?

What the other sectors lack is not processes, people or tools. It is a performance infrastructure that wires the people, processes, and tools allowing and sustaining digital transformation. It’s the digital core.

A digital core is an innovative technology design that provides businesses with real-time visibility into all mission-critical business processes and all other processes that encompass customers, workforce, Big Data, suppliers, and the Internet of Things (IoT). This cohesive system empowers companies with the required data to predict, simulate, plan and even antedate future business results with unparalleled accuracy in the digital economy.

A digital core can be utilized to overcome complexity in the IT infrastructure of companies. It can provide real-time perceptibility into all the crucial processes that concerns its customers, workforce, data management, suppliers, and devices.

The in-memory computing helps businesses support the consumers and enables end-user decision making. The digital core then changes the system of record into a system of advice, fast-tracking the speed of the business on the basis of real-time, up-to-date decision support.

Core transformation in the banking and financial sector

Core transformation in the banking sector has always been kind of a taboo. The fear of the unknown, comfort level with existing technologies and the luxury of overlooking operational inefficiencies have ensured that core transformation doesn’t take place in the sector.

After the economic crisis of 2008, financial institutions have been streamlining their business and operating models for both monetary reasons and to lessen organizational complications. While historically, banking institutions were held in high regard, the financial crisis hit all financial institutions right where it hurts. Most banks are yet to recover from the damaged reputation they faced during the catastrophe. In comparison to other industries, banking institutions have experienced the least growth in brand value over the last 10 years. With digitization of other industries, consumers now expect next-generation banking experiences to reproduce those in other industries.

The times have changed and in the current competitive environment, it is essential to align the IT strategy of banks to their business goals. Core banking transformation seems to be the only way out.

Technology plays a strategic role in the banking industry. From its core operation to distribution channels, a bank is dependent on the IT. Hence, replacing the core system is a huge exercise for a bank. The bank must have a clear objective, make a simple plan and stick to it. One of the main challenges is to keep all systems up and running during the replacement procedure. Furthermore, keeping costs low is critical because every bank’s key objective is to increase revenues and reduce expenses.

By embracing the digital core, banks can cut their costs and restructure their processes. This endways integration leads to a more seamless, engaging customer experience for the customers and it provides opportunity for further business alteration with new digital technologies like blockchain and artificial intelligence.

Principally, a bank should strategize an IT architecture that reduces complexity. They should use technology solutions that are based on open standards and can be implemented quickly.

To keep up with the rapidly evolving business and operational requirements along with shifting customer demands, the banking sector needs to constantly upgrade its practices and processes. This is possible only if banks regularly augment their core systems and associated applications. Hence, a large number of banks are considering the transformation of their existing core systems with contemporary vendor solutions.

Some BFSI organizations are already leveraging the blockchain technology to alter their business processes as it provides safe, convenient substitutes to traditional banking processes. Off late, blockchain has been the order of the day because it has reduced fraud in the financial world. Other technologies, such as machine learning, are also being utilized widely to automate manual processes, fraud management, and customer segmentation activities.

However, transforming this complex web of applications with new core banking solution is not an easy process. There is a fundamental need to meet functional requirements, cleansing of data from old systems, transformed and then migrated to the new system, and so on. The processes driven by older applications also have to be altered and users need to be re-trained on the new application and processes.

Due to the highly disparate systems in the banking sector, this process is time-consuming and costly. In the last few years, a few banking institutions have used a Line of Business (LOB)-oriented migration approach. This approach helped them experience the benefits of the new core banking solution rather early in the project. This is where the Service-Oriented Architecture (SOA) features as a helping hand in the migration process.

It works as an integration framework that combines the internal and external services to create a solution. With SOA, instead of focusing on different applications that are a part of multiple disparate systems, the emphasis is on business services that denote several different underlying applications.

With the introduction of high-end technologies and global best practices that offer enhanced dexterity, efficiency, CRM capability and faster deployment cycles, banks need to be aware of the challenges that plague the core banking deployments. Once these challenges are understood and alleviated properly, digital transformation is achievable and perfectly manageable.

Over the past decade, banks in the Middle East have embarked upon a number of core banking transformation initiatives with the stated objective of improving business agility, only to realize the magnitude of challenges and their unpreparedness mid-way, and finally go live compromising on quite a lot of objectives. Given that a transformation initiative has tremendous interplay across multiple service providers including the banking product (solution) vendor, system integrators, assurance specialists and others, this article heavily draws upon our organization’s experience providing assurance services during core banking transformation engagements and highlights some of the common pitfalls along with possible remedial measures.

A common pitfall is the absence of a common understanding among the banks’ stakeholders on the expectations from a transformation program.  Replacing a legacy system with a ‘modern’ core banking platform does not automatically result in improved business processes or translate into the better customer experience. The Program Sponsor needs to have onboard all key stakeholders, prioritize key features for implementation, strategize the roadmap and periodically evaluate the business benefits delivered during the course of the transformation program.

Our recommendation: The original business case, payback, and benefits realization needs to be revisited periodically to examine the impact of program delays. Corrective actions need to be initiated that may include a re-look at the program objectives and scope, especially when programs involve huge budgets and are spread over long timelines.

As a part of the program initiation, all key features/requirements need to be cataloged to align with the bank’s business/operations process flow. This activity needs to be done independent of the product (solution) vendor. An observed practice is the banks’ tendency to identify the core banking product first based on high-level product walkthrough sessions without going through the exercise of documenting business requirements. In a lot of instances, requirements were documented only for those features that deviated from the existing functionality available.  In our experience, selecting the core banking product first resulted in mismatches between product features and business operations requirements, excessive customizations during implementation and deferring some of the business critical requirements for implementation post Go-Live due to program schedule pressures resulting in expectations mismatch for business stakeholders. Also, incorrectly implemented/deferred implementation of requirements results in maintenance costs for all such changes and delayed business benefits realization.

Our recommendation: Engaging specialists (in-house or external) to document business requirements through structured storyboarding sessions or business process documentation led walkthrough sessions with business stakeholders can ensure a prioritized set of features and functions. This should be used as a basis for core banking product selection.

Another common trend observed was to bundle too many initiatives as a part of the transformation program. Core banking transformation per se may lead to technology and architecture changes. However, bundling it with various other initiatives such as business process re-engineering, new middleware implementation, and the introduction of new delivery channels (Including digital platforms) besides replacement of some surround systems and adopting an omnibus approach complicates an already complicated program and adds a significant number of failure points.  Banks have tried to tide over this situation, trying to engage service providers who specialize in such services. However, the enormity of the task of managing multiple solution vendors, stakeholders, and conflicting priorities has resulted in mixed results.

Our recommendation: A strong Program Office that oversees multiple programs being run in parallel is critical to ensure success in this context. An empowered Program Office with Staffing experienced Program Management staff & clearly established accountability would mitigate some of the risks.  A phased approach to implementation was more successful rather than a big bang approach.

Quality Assurance services are almost an afterthought during transformation programs. There is an inherent assumption that core banking products are standard products that do not require extensive testing and hence, inadequate time and budget is allocated for verification and validation. What is overlooked is that core banking products need to be tested extensively for integration with other applications in the ecosystem besides being thoroughly tested for custom developed features. We have observed a few banks engage the services of the core banking product for testing services as well.  The downside to the approach is the lack of an independent perspective of requirements implementation.

Our recommendation: Banks need to plan and budget for Quality Assurance services adequately during the program initiation itself. Engaging independent assurance service providers can help detect incorrect requirement implementation (prior to Go-Live) that would otherwise go unchallenged in the absence of an independent perspective.

A key aspect that gets missed out during the contracting process is the absence of Service Level Agreements (SLAs) that aligns the interests of all the service providers in the program. Most contracts are bilateral (between the bank and each service provider) and hence can potentially miss out the inter-dependencies. For example, SLAs pertaining to the delivery of defect fixes and quality of defect fixes has a direct impact on the quality assurance program, but the requirements of the QA service provider are ignored during the contracting process with the core banking product vendor thereby having a direct impact on the program schedule. Engaging external advisory firms have produced mixed results on this front.

Our recommendation: Banks need to factor in inter-dependencies of all service providers during the contracting process. Banks need to conduct adequate due diligence before engaging third-party advisory firms who can weigh in with industry benchmarks and help them with the contracting process and subsequent monitoring.

Another critical area often glossed over is the extent of the complexities involved in data migration. The legacy application would have undergone extensive customizations driven by business and regulatory requirements with inadequate documentation describing the changes resulting in an inadequate grasp of the data structures of legacy systems leading to a bigger problem – migrating the data from legacy system to the target system in a reliable manner.

Our recommendation: Early involvement of in-house business/application experts, engagement of the right specialist firms for data migration services and product (solution) vendor teams, agreement on acceptable data quality and scheduling adequate mock runs early during the program to ascertain data quality are some mitigation measures.

As a part of dress rehearsal/operational readiness, banks often complete infrastructure testing, end-user training on the new solution and go live. In a few instances, centralized helpdesk services are set up to tide over the challenges associated with change management. However, there is no ‘ready reckoner’ available for end users to assist with navigating the newly implemented core banking system.

Our recommendation: Banks should get adequate documentation done and get business user manuals created that is in line with the customized version of the IT system being implemented. This will help tide over users’ resistance to uptake of the new system, a key challenge associated with change management.

Some of the other challenges include a lack of attention to non-functional requirements, ability to manage the scope and exit criteria during various rounds of testing through tight gating criteria and a lack of a strong governance and oversight mechanism. All core banking transformation engagements have their fair share of challenges. Acknowledging the complexities and addressing the same through appropriate risk mitigation measures can help banks tide over some of these challenges.

*This article was previously published in Banker Middle East Issue 30 June 2016