Spokesperson: Tom Fairbairn, Distinguished Engineer, Solace
The tech capabilities of financial enterprises are evolving rapidly. From real-time payments to AI-powered fraud detection and predictive analytics in trading, institutions are becoming faster, smarter, and more connected. But this digital acceleration is revealing a critical flaw: legacy integration systems are no longer up to the task.
Artificial Intelligence didn’t break financial integration, it simply exposed how outdated the underlying infrastructure has become.
Legacy integration: real-time red tape
For years, banks, wealth managers, insurers, and hedge funds have relied on APIs, batch processing, and point-to-point connections to knit together their systems. This worked when data only needed to move once a day, or when workflows were isolated within specific departments.
But today’s AI-driven use case functions like real-time liquidity optimisation, instant compliance checks and adaptive credit scoring, require split-second decisions and continuous access to live data. If an AI model is instructed to flag a suspicious transaction, adjust an exposure limit, or execute a trade within milliseconds, but must wait on outdated integration workflows, the opportunity is lost – and so is the competitive edge.
Fragmented data speed
Speed isn’t the only issue. Fragmented data remains a persistent challenge. Many financial institutions continue to operate with siloed business units, disconnected product lines, and customer data spread across multiple legacy platforms.
When a client’s risk profile changes, when a geopolitical shock hits the markets, or when a regulatory threshold is breached, these events often cannot trigger coordinated action across the organisation. According to an industry connectivity benchmark report, only around 29% of enterprise applications are actually integrated – a sobering statistic in an environment where responsiveness is everything.
In today’s fast-moving markets, delays and blind spots create systemic risk.
From data at rest to data in motion
Modern financial institutions must move beyond the idea of data as a static resource to be collected and reviewed after the fact. Every tap-to-pay interaction, KYC update, client message or real-time risk calculation is an event. And events must trigger immediate action.
AI systems don’t only analyse quarterly summaries. They respond to streams, continuous flows of real-time context. When that stream is broken, slowed, or incomplete due to fragile integrations or legacy tooling, the full value of intelligent automation is lost.
This is not a challenge unique to traditional banks or insurers. Even digital-native players struggle when their integration platforms rely on point-to-point architecture that wasn’t designed for decentralised, event-driven environments.
Event-driven integration
What’s needed is not another optimisation of legacy infrastructure, it’s a reimagining of integration as a strategic capability. Event-driven integration represents that shift.
Instead of polling for updates or transferring data in timed batches, such integration enables systems to publish and subscribe to real-time events. These events are distributed via an event mesh, a network of event brokers that supports seamless, low-latency communication between systems, applications, and users.
At Solace, we’ve seen how this approach can decentralise intelligence, allowing AI models, business systems, and even external partners to act immediately, without bottlenecks or manual intervention.
Agile and scalable finance
By adopting event-driven integration, financial institutions can become more agile, scalable, and resilient. It enables faster response to shocks, whether economic, regulatory, or technological, and positions firms to take advantage of fleeting opportunities in volatile markets.
Leading analysts, including Gartner and IDC, now identify event-native architecture as foundational to the next wave of digital transformation. For derivatives markets, where milliseconds matter, the implications are profound. AI didn’t cause integration to fail. It simply made its limitations impossible to ignore.
The capital markets differentiator
In an AI-enabled financial system, firms that move with their data, not behind it, will outperform competition. Competitive advantage will come not only from smarter models, but from infrastructure that enables continuous sensing, decision-making, and execution.
In that way, integration is a strategic enabler, a nervous system for the real-time enterprise. And for those in capital markets, it may prove to be the difference between keeping pace with the market – or setting the pace.
