Generative AI has gained widespread consumer interest and acceptance over the past year and implementing this technology is now a critical consideration within many sectors. In fact, economists estimate almost $200 billion could be invested globally into generative AI technology by 2025.
Across the global financial sector, despite overall caution being observed for generative AI in the short term, it clearly has the potential to accelerate banking models and redefine how clients and financial institutions interact. As financial services firms are treading cautiously in exploring its application, many need to address a platform engineering problem before they can experiment and evaluate the full potential of this disruptive technology.
Cloud is the engine that can power generative AI ambitions for any organization. As the financial services industry begins to deploy this technology across automation, coding, customer service and a variety of other business cases, the adoption of this transformative technology necessitates extensive data volumes, substantial computing power, sophisticated security measures, and swift scalability. All proven advantages of cloud.
Global Head of Cloud for Financial Services at Capgemini.
Migrations underway, but impact remains uneven
Financial services organizations are making significant cloud investments to support their deployment of future technologies like generative AI at scale. Recent research reveals 91% of banks and insurance companies have now initiated their cloud journey. That’s up significantly from 2020, when only 37 percent of firms had started the process.
However, cloud investments to date have tended to focus on customer-facing applications such as self-service portals, client onboarding tools, and transaction-based operations, including payments. More than 50 percent of financial services executives said their organization had not yet migrated core business applications such as risk management and compliance systems, data management, and core banking and insurance systems. Since many of these back-end systems provide critical inputs into customer-facing applications, the outcome is often a poor overall user experience.
Similarly, 80 percent cite delivery of a superior customer experience as key towards overcoming current business challenges and driving growth. Firms will need to reimagine their data, processing, and consumption strategies. Enterprises will need to modernize their platforms beyond just moving data to the cloud as-is and instead rebuild them to handle small and big data, structured and unstructured data, and finally batch and stream data. Without good data, the application of AI findings is restricted since it serves as the foundation for many cutting-edge technologies. With the current framework in place for many organizations, generative AI may magnify the problem because, to be truly effective, it must have insight into all company operations. And today, the best way to achieve that is to make all operations cloud native.
Outcomes, skills, and partnerships are core to drive success
Every firm’s cloud journey is unique but there are common elements that must be addressed to be successful.
To start, companies must clearly identify the outcomes they want to achieve. This means creating a well-defined business strategy for cloud, and a phased roadmap that identifies priorities for implementation. From personal experience, I can tell you that every technology firm working in cloud can provide many examples of enterprises that have struggled in their journey, where the problem could be traced back to a vision statement for cloud that did not focus on business value.
Organizations must also have the right skills – including those around cloud and cloud security experts – to oversee the creation and operation of the platform, the migration of data to it, and the deployment of cloud-powered solutions. Otherwise, having a cloud platform will be like having a Formula 1 race car but no driver – or, worse, an unskilled driver with a learner’s permit. If a firm does not have the required talent in-house, it must seek professionals who understand both cloud and the needs of the sector.
Importantly, when attempting to migrate to the cloud, many financial services firms face two technical roadblocks. Most organizational processes are not re-engineered for cloud, and many core systems continue to rely on legacy technologies in discrete silos. To address this, firms should engage with a strategic partner that has established links with the world’s leading cloud solutions providers and has created cloud platforms customized for their sector. Ideally, these will be composable platforms that use pre-built modular components to easily integrate front-end and back-end functions. A modular approach provides enterprises with the flexibility to develop a roadmap that prioritizes functions for migration based on their business strategy. It also enables the cloud platform to evolve, helping to future-proof the investment.
The introduction of any new technology will always be disruptive – whether it’s generative AI, quantum computing or something nobody has yet envisioned. What we know today is that legacy architectures will need to undergo a reboot to be relevant in the generative AI era. Therefore, it makes sense to remain focused on value creation, and let that objective determine how the enterprise will leverage new technology.
At the same time, it’s important to recognise that becoming cloud native is essential to gain competitive advantages through generative AI and other innovations. As one industry executive shared: “Without cloud, there is no future for financial services firms.”
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