Unlocking Innovation in Banking
The Power of Low Code, Domain Expertise, and Generative AI
Having worked in Technology & Innovation for more than 25 years and focused solely on building Artificial Intelligence solutions and products for the last five, I am struck by the current hype around AI, especially in the Financial Services sector, but also evident in most other industries. In many of the conversations I’ve had recently with clients, they speak about feeling overwhelmed with the hype, particularly when it comes to Generative AI. There is pressure to do something to adopt it. Each of their technology vendors is coming to them with a “use my GenAI widget” message, and deciding where to start can be challenging.
Earlier this week, I read a quote saying, “AI will be assumed” in a few years. This statement resonates with me and aligns with where I believe we are headed. In the not-so-distant future, there will be no software without AI. As software users, we will become accustomed to a new user experience. One that gives us an assistant to collaborate with and allows us to complete our tasks faster and better, to become more efficient and effective humans. We can expect new features, such as the ones that Generative AI makes possible, will be embedded throughout all the software solutions we use.
It seems straightforward. However, the dynamic landscape of the financial services industry, particularly within banking, presents a more complex challenge. Banks operate with intricate technology systems, and updating these systems involves a substantial investment in budget, planning, execution, and risk management. This often leads to internal stakeholders' frustrations, as significant resources are dedicated to maintaining existing systems, leaving limited funds and capacity for innovation and modernization.
However, there is a promising development in the form of Enterprise Low Code platforms. These platforms offer a practical solution by providing a supplemental layer that addresses gaps within the core banking infrastructure, especially for functions requiring urgent modernization. They allow banks to swiftly develop digital workflows that cater to their unique market differentiators, thus enhancing flexibility and agility. These platforms enable the creation of a process orchestration layer for human-centered workflows, supporting automation across different enterprise systems and fragmented enterprise data sources across multiple lines of defense.
Enterprise Low Code strikes an ideal balance by offering essential capabilities and building blocks for rapid development while maintaining flexibility for customization. These platforms, often hosted on robust cloud infrastructure, offer scalability and reliability characteristic of cloud deployments. Moreover, they integrate AI and generative AI capabilities, streamlining the incorporation of advanced technologies into digital workflows without isolated solutions requiring separate maintenance. Data shows that building solutions with Enterprise Low Code can be multiple times faster than full-stack approaches, also known as “high code”.
In my experience, a critical success factor in building these solutions effectively is access to high-quality domain expertise with proven experience in the niche business process area we are trying to automate. Instead of starting with a blank canvas, having access to this expertise allows for the development of solution accelerators that not only adhere to industry best practices but also incorporate innovative perspectives for future-ready solutions. This approach addresses previously unrecognized gaps, providing a more comprehensive and proactive solution framework that may not have a pre-existing blueprint.
An example of a solution accelerator we are currently developing is one focused on regulatory change management in the banking sector. This tool must perform comprehensive horizon scanning, analyze history, and anticipate future regulatory changes while securely accessing internal documents to update regulatory controls, policies, and procedures. Utilizing generative AI, it can assess the impact of regulatory changes based on specific licenses held by the bank. The flexibility of this system supports customization to align with internal organizational structures and adapt to changes within the bank. Given the increasing pressures of regulatory changes and the impact on innovation due to compliance concerns, a solution like this can significantly differentiate a bank in the marketplace.
By leveraging Enterprise Low Code platforms and combining them with unique domain expertise and generative AI, applied with Responsible AI principles in mind, banks can navigate away from the constraints of legacy technology utilizing a risk-conscious approach. This integration empowers banks to advance their innovation agendas, applying modern technology to specific business processes that deliver immediate benefits and move the needle in taking meaningful steps towards transforming their broader technology landscapes. This approach exemplifies how banks can navigate the overwhelm of the Generative AI hype, foster innovation and maintain competitiveness in an ever-evolving industry and technology landscape.
Best regards,
Chief Innovation Officer and Head of AI
Bits In Glass