Disruptive AI technologies can dramatically improve banks’ performance in four key areas: higher profits, at-scale personalisation, smart omnichannel experiences, and rapid innovation cycles. The stakes could not be higher, and success requires a holistic transformation spanning all layers of the organisation’s capability stack.
Any organisation undertaking an AI-bank transformation must determine how to structure the organisation so that its people interact and leverage tools and capabilities to deliver value for each customer at scale.
Currently, the widening divide between fast-evolving customer expectations and inertia within the bank reinforces silos and weakens the bank’s ability to respond to the demands of the new machine age. The challenge for leaders will now be to shift the organisation from this siloed structure to a radically flattened network of platforms.
AI banking platforms focus on delivering business solutions
Today, banks that recognise the value of AI and technology enabling better customer and business experience are moving steadily toward a platform operating model, levelling command-and-control structures to speed decision making and bring people together in teams relentlessly focused on delivering solutions that customers value.
In this agile approach, each platform can be thought of as a collection of software and hardware assets, funding, and talent that together provide a specific capability. While some platforms, such as those for retail mortgages, deliver business-technology solutions to serve internal or external clients, others enable other platforms with shared services and support functions (for example, payments and core banking).
Each platform is largely self-contained in producing business and technology outcomes and autonomous in prioritising its work to meet strategic goals within clearly defined guardrails, such as common standards, finance, and risk control.
As banks think about setting up a platform operating model, they should bear in mind that each platform comprises three main elements: strategy and road map, organization and governance and technology. When structured correctly, these elements will help a platform team set its North Star and carry out its mission in a way that creates value for customers and the enterprise.
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The platform model can help organisations seize new opportunities
Executing on a platform operating model is arduous. However, when done correctly, it has the potential to deliver four main benefits to all stakeholders: value-oriented business-technology partnerships, stronger performance (speed, efficiency, and productivity), transparency, and a future-ready business model.
The collaborative framework of the platform model brings business and technology leaders together as co-owners in creating value for the enterprise. Joint owners of business-facing platforms share accountability for outcomes, merging business knowledge of market opportunities with expert insight into how technological advances can enhance customer experiences.
The leader of the platform facilitates the interaction of business and technology owners in determining the right balance between run-the-bank and change-the-bank initiatives. All members of a particular team are unified in delivering a solution (just as those of the entire “tribe” of a platform are focused on a service line) in order to create value in alignment with enterprise strategic objectives.
This unity is reinforced by the fact that all team members share in performance metrics for both business and technology outcomes, including impact on users (internal and external), on-time delivery of solutions, customer and employee satisfaction ratings, and more.
The platform approach can strengthen an organisation’s performance in terms of speed, efficiency, and productivity when each platform is large enough to address a set of use cases crucial to realising the business model of the enterprise but small enough to keep the team agile.
Each team enjoys a degree of autonomy, with a budget and mandate to experiment and discover the best way to maximize value within a discrete domain in alignment with predefined guardrails (for instance, finance, risk, compliance) without having to wait for approvals from finance and allocations from IT and human resources. This autonomy speeds up decision making, innovation, and solution delivery.
In addition to the emphasis on interdisciplinary collaboration, the platform model is designed to increase transparency, accountability, and knowledge sharing to the fullest extent possible.
Finally, shifting to a platform model can help an organisation future-proof its business model because each platform is incentivised to continuously improve on its technology landscape. Within a culture of continuous learning, team members are accustomed to change and adept at finding the best response to fast-evolving circumstances.
Interdisciplinary initiatives led by business-technology co-owners strengthen a team’s capacity to anticipate and consider potential challenges and opportunities before they appear on the horizon. Enterprise-wide standards, rigorous documentation of processes, and consistent cataloguing of technology assets enable teams to apply best practices as they develop and implement new solutions.
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Increasing collaboration and value creation with the platform operating model
By underpinning business-technology co-ownership of solutions delivery and value creation, the platform operating model offers banks an opportunity to maximise the impact of their technology capabilities in ways that count for customers.
The implementation of the platform model begins logically with the formation of joint business-and-technology teams focused on the design, development, and implementation at scale of new AI-bank innovations, always striving toward a more intelligent value proposition and smarter experiences and servicing.
The creation of cross-functional platforms is also an excellent approach to increase business–technology collaboration, developing an IT operating model that generates immediate and tangible business value and moves the full organisation, not just technology, to an agile way of working. However, to derive maximum value from platforms and the people who make up these platforms requires new skills, mindsets, and ways of working.
Bringing all these elements together is a powerful mechanism to optimize the full capability stack, from core technology and data infrastructure to AI-powered decision making and reimagined customer engagement. The platform operating model ensures that these layers run in sync to spur the growth of an AI bank of the future.
The full report, Platform operating model for the AI bank of the future, dives into how organisations can implement a platform operating model and what features are needed to further optimise performance and deliver value for each customer at scale.
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Image Credit: Nguyen Dang Hoang Nhu
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