Digital Transformation in Banking: How Core Modernization Helps Tackle Challenges and Opens New Revenue Streams for Financial Firms
Digital transformation in banking (retail and consumer banking) has so far been quite narrow. Some financial firms have made efforts to get out on social channels (to where the prospects are) and streamline common front-office operations. But that’s about where their modernization ended. Lending, deposits, and other core activities are still mostly run on complex and monolithic legacy systems, though a few companies now have a digital veneer over their antiquated architectures.
In this post, we’ll talk about how financial institutions can go beyond putting out apps, which clients then barely use, and applying rule-based chatbots in their digitization efforts; we’ll discuss how to open new paths to value creation by moving to API-driven, versatile and scalable cloud core platforms.
70% of banks are now actively reviewing their core banking platforms, according to a McKinsey survey from May 2019.
Why hasn’t digital transformation in banking gone far yet?
The main problem, paradoxically, is that legacy solutions still work.
That aging software can run some core operations, however slowly, has prevented multiple financial institutions from throwing investment into a heavy transformation. Not only has modernizing the core been considered an extremely costly and time-consuming undertaking; it’s also been associated with risks.
Legacy software, home-engineered or bought off a vendor at one point and modified beyond recognition, is in many cases the engine running the bulk of banks’ most involved activities. So, repairing it (or setting up a replacement solution) may cause massive operational disruption.
That being said, all software tends to decay over time and, currently, many of these firms’ support and maintenance contracts are expiring.
When trying to update monolithic core systems, financial firms are finding out their platforms are rife with vulnerabilities, have been modified by multitudes of shoddily documented customizations, and have integrations that are impossible to unravel. Updating them sufficiently would be equal, in terms of engineering effort, to implementing a brand-new platform.
There are four crucial ways flawed architectures impede on banks’ performance.
1) They chew through a large part of digitization budgets and of overall IT spend due to having large technical debts. The issue is compounded by the manual deployment and regression testing these platforms require as well as the low through-process-rates caused by layers of complexity.
2) Their legacy code, a sea of interdependencies and bottlenecks stemming from the monolithic architecture, and lengthy manual delivery processes hinder drastically banks’ ability to put out products and services fast.
3) Besides slow time to market , cumbersome systems may also cripple banks’ service personalization initiatives : since application data is typically stored in a variety of product-aligned solutions, firms have trouble catering to the individual needs of each client.
4) Their lack of third-party connectivity is, too, a major concern, since creating diverse ecosystems (banks having networks with mortgage services providers, etc.) is a proven way to enable innovation and come up with unique differentiating proposals.
Types of transformation
There are a few options financial firms choose from.
Rip and replace. Breaking established processes and implementing a completely new core platform requires a sizeable initial investment. It’s a viable option for firms whose contracts (legacy platform support, maintenance, etc.,) are coming due and whose core systems, if left untouched, won’t be able to meet the firms’ operational and financial needs much longer. Before embarking on such a heavy project, the company must thoroughly analyze all possible outcomes and make sure the associated risks are justifiable.
Capital One, one of the largest banks in the U.S. by assets, has announced its plans to move completely their core business and customer applications to the public cloud by 2021.
Parallel cores. Instead of blowing existing architecture completely, some banks opt for augmentation. They implement new, more flexible core systems on top of the functioning legacy ones, which allows them to maintain daily activities while also gradually transforming operations and launching new modernized offerings (that run on the new software). Also, both platforms can be utilized simultaneously – each serving a certain business purpose and banks can decide to migrate to a new system eventually after making sure it’s been tested enough times and is completely stable.
Modernize. There’s an argument for refactoring old platforms’ code too – for example switching from outdated COBOL to Java. Some banks reject changing their platforms’ baseline behaviour, so, instead, they can work on increasing the extendibility, readability, and maintainability of the existing ones. Sometimes the platforms lend themselves so well for modernization through new technologies, they can even be made cloud-ready.
New Base Platform. When a drastic transformation is unfeasible and a bank seeks to avoid the slightest operational disruption, migrating the existing code to a more powerful platform with some minor changes might be the best choice. It won’t really help a firm to address the ever-evolving market and business demands (since no meaningful changes to the applications’ functionality will be implemented) but it can at least become an important first step towards future modernization.
Passive observation. Finally, some institutions don’t yet have the business case (or a risk profile) for core modernization, though they are aware such need is likely to occur in the imminent future. For them, it’s best to keep relying on the current functionality while still observing closely the market leaders to determine what upgrade to go for.
The Properties of an Ideal Core System
Modular architecture is key; it allows creating platforms that are adaptable, configurable and flexible which, in turn, enables banks to facilitate and support new ways of operating and have stand-alone products (that could be pre-integrated). The modular components can also be deployed separately while being on top of a single infrastructure. Engineers can work on advancing specific core functionalities – by focusing on a specific decoupled piece of the platform – instead of rewriting an entire monolithic solution. This expedites matters drastically and allows incumbent banks to adopt agile methods.
The core should be composed of multiple well-defined layers :
- a stateless one that lets APIs and supported services into the platform;
- a business logic one – preferably portable so that the core’s code can be migrated to different hardware and operating systems;
- a data layer that supports bi-directional real-time data flows between the applications in the network.
Sufficient connectivity is the next important feature; fine-grained APIs, that allow firms to externalize different services and strengthen the link with various data consuming applications – are vital for creating robust partner business ecosystems. A third-party should be able to plug into a banks’ core capabilities and the institution itself should be able to participate in emerging ecosystems to deliver innovative services.
Moving a bank’s core system up to the cloud is, too, a common recommendation as it allows banks to scale their operations quickly. Both using a private cloud environment or tapping into a data center capacity of some cloud provider will work, as long as the cloud allows for continuous delivery of services, responsive business process management, and offers comprehensive tools for launching and configuring products.
Overall, to support emerging business models, a cloud-based platform must have a containerized architecture, an API-first design, multi-tenancy capacity, distributed database and support for continuous integrations and deployments.
Finally, there ought to be a strong approach to data processing: the volume, velocity, and variety of financial information are rising while the regulations aren’t getting any lighter. A modern banking core platform should, therefore, support a variety of database management tools, both open and enterprise ones, and enable a reliable, real-time data-stream across applications.
Though digital transformation is sweeping through multiple industries, including financial services, incumbent banks have been relying on legacy platforms and generally lag in terms of meaningful core modernization.
Many traditional institutions have reinvented customer channels (through the implementation of bots etc.), invested in their mobile and web presence and, overall, taken initial steps towards altering antiquated business strategies. But the front-office view of digital transformation isn’t enough, it won’t help them fight the pressure from Big Tech companies, who have massive customer bases already, and nimble fintechs, who have been quite successful in targeting important niches in the financial value chain.
To meet the ever-evolving needs of modern business models and find new ways for value creation, a more profound change is needed; incumbents have to tackle the limitations of their core platforms and the cloud technology is well suited to helping them do so.
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