By Floyd Davis
Solace
Financial services leaders see great potential in generative AI. A study from EY-Parthenon (see bit.ly/4740o7M) canvassed executives at retail and commercial banks about where they believe generative AI (gen-AI) will deliver the most value in their organizations. Enabling greater productivity by automating sales-related activities was listed by two-thirds of respondents, followed by enhancing existing technological capabilities (63 percent), then accelerating broader innovation (54 percent).
But while financial institutions (FIs) recognize the transformative potential of generative AI, they are struggling to capitalize on it due to their legacy technology infrastructures. These systems, often characterized by siloed data and slow processing speeds, create significant barriers to AI adoption.
To fully harness the power of generative AI, banks must break down data silos and adopt a real-time, event-driven approach. Only then can they generate the actionable insights needed to make informed decisions, enhance customer experiences, and stay ahead of the competition.
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, integrating an event mesh with AI will foster ongoing innovation and prepare digital-first banking institutions for the future.
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 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.
FIs 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.
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.
FIs 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.
Particularly in FIs, 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 FI 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 FIs 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 percent of financial services industry respondents have already adopted several EDA use cases. 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.
The future of banking lies in the seamless fusion of AI and business-critical data, and those who prioritize transformation will reap the rewards. By breaking down data silos and adopting an event-focused approach, banks can create a dynamic, agile and intelligent organization capable of harnessing gen-AI to deliver exceptional customer experiences and drive sustainable growth. 
Floyd Davis is vice president for solution engineering at Solace. He leads a multi-disciplinary term that helps clients successfully deploy and get maximum value out of Solace’s products. Connect with him on LinkedIn at www.linkedin.com/in/floyd-davis-0981981/?originalSubdomain=au.a
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