Banking on Generative AI for a productivity windfall: How event-driven Gen-AI will benefit financial services
The advantages of Generative AI hold immense promise for the banking industry, with the technology set to generate between $200 billion to $340 billion in value, influencing every financial service institution (FSI). Beyond process improvements and cost savings, banking leaders believe Generative AI will strengthen operational capabilities. But aged, heavily-customized technology architectures with poor data flows present a serious roadblock to Gen-AI helping employees, enhancing technology implementations, and planting the seeds for wider innovation. Here, Floyd Davis, Vice President for Solution Engineering at Solace, explains that unless banks are able to overcome this challenge with an event-driven approach to their technology architecture, they will not be able to reap the groundbreaking benefits of Generative AI.
Generative AI has the potential to alter job functions, customer interactions, and even lead to entirely new business models. Recent research from EY-Parthenon reveals decision-makers at retail and commercial banks view three main areas where GenAI is changing ways of working:
- Enabling greater productivity by automating sales-related activities (66%)
- Enhancing existing technological capabilities (63%)
- Accelerating broader innovation (54%)
But these banking opportunities cannot be realized without effective data governance and movement. The ability to convert data into actionable insights is crucial for future success. Banks that embrace an event-driven strategy will be able to achieve precise AI analyses, uphold data integrity, and quickly disseminate actionable insights which are crucial to decision-making. Essentially, the integration of an event mesh with AI will foster ongoing innovation and prepare digital-first banking institutions for the future.
See the bigger picture with data unification and drive operational efficiency
A successful business is not just about possessing vast amounts of data; it’s about transforming and transmitting data in real-time, delivering valuable insights, and enabling smarter operations.
Many banks are currently hampered by data silos, which occur when information is stored in isolated systems that do not communicate with each other. This creates a fragmented view of the customer or business as a whole, resulting in inconsistencies, inefficiencies, and a lack of comprehensive datasets. As long as data from various departments such as customer service, risk management, and transaction processing remain siloed, banks cannot fully leverage AI’s capabilities to analyze patterns, predict outcomes, and automate processes. Without the transformative benefits of generative AI, banks miss out on new opportunities to drive innovation and enhance operational efficiency.
FSIs need to look at the unified control of their data, which ensures consistency, accuracy, and efficiency in data handling across all departments. Beyond that, they also need to ensure that this data is streamed and routed in real-time, for actionable and timely insights. After all, having an AI act on outdated information will result in the AI-generated output being untimely or irrelevant, and require more human interference to rectify.
To initiate the evolution of banking systems towards unified control, banks need to adopt a more event-driven approach to their data integration strategies. Underpinned by an event-driven architecture (EDA) platform, this real-time integration and distribution approach ensures smooth data flow across the organization, reducing latency and enhancing operational efficiencies.
Enable the free flow of information with an event mesh network
Traditionally, banks have operated using a request-driven model where a rigid architecture defines tasks. These systems efficiently handle simple and predefined tasks but fail to react to the variable demands of the digital era.
In this AI era, the key lies in establishing a continuous flow of information across the entire business and extending to and from customers. An event mesh enables precisely that – facilitating real-time, event-driven communications between systems and services across environments and geographies. FSIs must be able to absorb and manage bursts of activity while ensuring data reliability and uptime, as even a few minutes of downtime can be devastating, leading to significant loss of customer satisfaction and financial damage.
Timing is all
Particularly in FSIs, triggering AI analysis at the appropriate moment is crucial as the timing of insights can significantly impact decision-making and operational outcomes. Real-time AI applications require the processing of large volumes of data at high speed. EDA is well-suited for this, as its asynchronous nature efficiently handles the rapid generation of events.
The real-time nature of event-driven architecture can help connect and integrate applications and devices in the FSI ecosystem. Once AI analyses are complete, the resulting data and required actions can be disseminated instantly to relevant systems and personnel. An event-driven integration platform will also enable FSIs to observe, audit, and govern the flow of events from end to end, allowing them to be more selective about what would invoke an AI model while complying with policies and regulations.
Thankfully, the market is waking up to this reality – a recent global study found that more than 30% of financial services industry respondents have already adopted several EDA use cases in their organizations. This prompt dissemination is crucial for maintaining the agility and responsiveness necessary in today’s fast-paced financial environment, where decisions must be made quickly and accurately.
What a mesh! Say goodbye to the silos of traditional banking and hello to dynamic innovation
The integration of Generative AI within the banking industry represents more than a simple technological advancement. It constitutes a revolutionary shift in employee productivity and customer experience. Yet to fully leverage the transformative potential of Generative AI, banking institutions will need to transition away from traditional data management, movement, and governance strategies and explore the power of dynamic and event-driven platforms.
