As banks seek to innovate with new products and services, they must also tackle an increasing burden of compliance initiatives. Consequently, achieving greater speed and agility is a top factor driving corporate banks’ investments in technology. At the same time, banks must deliver their services through the constantly evolving fintech ecosystem and must embrace new AI technologies that are pushing the traditional boundaries of banking.
As a result, the role of technology—and the importance of technology architecture—in corporate banking solutions is more important than ever before. Banks must reevaluate and embrace the technology building blocks that support their needs for today and goals for tomorrow.
The Availability of Modern Architecture for Banking Solutions
A combination of effective architectures, technology platforms, and the use of strategic partners is necessary for corporate banks to deliver their technology portfolio faster. When evaluating applications, a clear understanding of business functionality offered remains essential, but so too are the technology building blocks—and how they align to a bank’s overall strategic architecture goals.
Smaller banks often tend to buy solutions from vendors or subscribe to SaaS models. Large banks primarily build solutions because they believe that the bank has too many unique capabilities, or that a vendor can’t scale to meet their needs. Yet the reality is that, for most banks, there’s almost always a combination of vendor-supplied solutions wrapped in a blanket of internal integrations and applications.
Banks should take a fresh look at “build versus buy” considerations and the practicalities of implementing the architectural trends that are modernizing corporate banking. Banks should be able to realize their target architecture strategy through collaboration with key infrastructure and application technology partners, and create composite banking services delivered through a combination of vendor and bank functionality. Many architectural capabilities (including cloud services, headless applications based on microservices, application containerization, modern data platforms, and more) are currently available from a wide variety of vendors, simplifying considerations and supporting banks’ technological and strategic initiatives.
Today’s Expectations
Several technology and architectural trends are modernizing banking. Some of them—cloud and API-based microservices—have become mainstream building blocks over the past five years. These are no longer considered innovations; they’re expectations.
The public cloud value proposition is growing for banking applications, particularly with the expansion of cloud-based artificial intelligence (AI) capabilities. Banks are increasingly moving workloads to public cloud and adopting public cloud services. The major cloud service providers (CSPs) have worked with regulators and major banks to ensure the security and resilience required in their datacenters and related technology stacks for mission-critical banking services. Many banking platform offering are now cloud-native, with products and services constructed from API-based microservices, which can be composed and orchestrated into many combinations of solutions. This “composable architecture” can enable new businesses and products or establish a next-generation platform that replaces legacy systems. As these composable architectures are implemented by banks and vendors alike, the lines are blurring in the build (proprietary solutions) versus buy (vendor solutions) evaluation.
Data strategy and digital banking data platform capabilities (including the enablement of AI across banking platforms) are more crucial than ever before. Banks must now identify how their data may be exposed for advanced analytics and AI, whether with “in-platform” AI and analytics solutions that are embedded in application code, or by exposing the data to other business intelligence (BI), AI, or analytics tools.
AI readiness relies on modern data platforms that can support rich AI-enabled capabilities, including machine learning (ML) models for predictive analytics (e.g., cash forecasting), receivables cash application, and enhanced risk and fraud threat detection. Relational database management systems (RDBMS) are pervasive, but document databases (or NOSQL platforms) are gaining traction, offering design efficiencies for high-performance workloads. And as data strategy matures, so must the plans for database resilience, recovery and portability (e.g., across cloud platforms, legal jurisdictions, and/or geographic locations).
Meanwhile, security expectations are intensifying. Multifactor authentication (MFA) is now commonplace, with banks expanding the scenarios for which they require MFA. Some banks and vendors are now exploring zero-trust security architectures, with continuous verification of users, devices, and applications; nothing is trusted and every event is verified.
The Way Ahead for Banks
Ensuring that a digital corporate banking application meets the desired functional scope is the top priority—whether choosing to build or buy a banking platform. Innovative platform solutions that are also scalable, secure, and resilient are possible when banks, along with their selected vendors, commit to an architecture of modern technology building blocks.
Successful banks will:
- Select future-proof architecture. The necessary architectural components for product innovation and process improvements may be based on institutional needs, technology stack, and vendor partners. The result will likely play a critical long-term role for the bank, impacting security, the adoption of AI, technical debt reduction, resilience, and portability.
- Understand the end-to-end role of data. Data and AI are now intrinsic parts of a product strategy. As new solutions and services are developed, and as banks develop more “intelligent treasury” products and services, a comprehensive understanding of the role of data components and the application of AI becomes increasingly important.
- Gain a clearer understanding of complex cybersecurity capabilities. Clarity about zero trust security and quantum computing can help corporate bankers and their technology counterparts understand the impact for their corporate clients.
- Bring teams together. Consider the needs of stakeholders from across the bank, beyond product management and their direct operations and technology partners. Technology architecture, infrastructure, product, operations, risk, and data/AI strategy teams should all be part of defining and evaluating digital corporate banking solutions.
Technology now plays a far more important strategic role than the last time a bank selected a new banking platform. Before moving ahead with new corporate digital banking solutions, each bank must be clear about its enabling technology vision. A platform should be flexible enough to be configured to build and deploy new products, features, and operational processes quickly. It must be fast enough to process high volumes of transactions and a large number of users without overreliance on hardware. Being AI-ready, with advanced data handling capabilities, is essential for underpinning AI efforts at scale and in multiple legal jurisdictions. The portability of banking applications to new infrastructure services is also an increasingly important consideration for risk and regulatory teams.
Colin Kerr, CTP, is a corporate banking analyst at Celent, where his research draws on a career at the intersection of global banking business and technology. His focus includes corporate digital channels, treasury and cash management products, technology modernization, and managing data as a foundation for analytics and AI. Before joining Celent in 2022, Colin was a technology executive for digital channels at Bank of America, where he led development of digital cash management and analytics solutions for global transaction banking. As an industry solutions director for worldwide financial services at Microsoft, Colin successfully developed banking industry growth strategies when technology vendors and banks began transitioning to cloud computing.
