The summer blockbuster film season reminds us that more isn’t always more. Bigger budgets and longer runtimes don’t necessarily produce a better story, and wealth management platforms have reached a similar point. After years spent connecting systems and aggregating data, many firms have more information than ever, yet the result isn’t necessarily better insight.
Brian Ross, CEO of Flyer Financial Technologies puts it as, “Aggregation stopped being the hard problem years ago. Most firms today can pull data from custodians, CRMs, financial planning tools, and portfolio accounting systems without much trouble. The real challenge is that aggregation was never the finish line, it just produces a bigger pile of data.”
Ten years ago, getting systems to talk to each other was an achievement. Today it’s largely expected. The harder part is figuring out what all that information is actually telling you.
Most firms still organize reporting around individual accounts. That’s useful if you’re trying to see whether a portfolio has drifted or a trade didn’t execute properly, but less so if you’re trying to understand the financial life of an actual client.
“The meaningful question isn’t whether a single account is drifting from target,” Ross said. “It’s whether the full household, across every account, custodian, and strategy, is on track relative to its goals and constraints. That’s the right unit of analysis.”
Custody and trading infrastructure get budget and executive attention because everyone understands the consequences of failure, the executive added. Data infrastructure supports the same priorities but is often owned by whoever inherited the reporting stack.
“The practical implication is that firms need a purpose-built data platform beneath their BI and AI tools, not a reporting layer bolted on top of existing systems,” Ross said. “Connecting systems is plumbing; an operating model is what happens because the plumbing works. The firms that get this right design around outcomes first, then build the data flow to serve that outcome.”
Firms are also actively looking at AI agents that work through governed APIs, instead of building a fresh integration for every pair of systems. The agent handles the coordination between systems, while the firm sets the rules for what it can read and write, with a record of every action it takes.
But none of that works without clean data underneath it. “AI doesn’t fix bad data, it amplifies it, and it amplifies it at scale and with a tone of authority that makes people trust it more than they should,” Ross said.
Most firms already have the data to flag which clients are at risk of leaving or which advisors need coaching on specific behaviors. In practice, that data tends to get used almost exclusively for compliance reporting and quarterly statements, leaving a gap between data as a backward-looking record and data as a forward-looking signal. Often the harder problem isn’t spotting the opportunity but acting on it: an advisor can see the full picture in one dashboard, then still has to toggle between an OMS, a compliance system, and a custodian portal to actually do anything about it.
When firms close that gap, the impact shows up in operations before it shows up in growth numbers. Reconciliation time drops, and exception handling that used to eat hours of an ops team’s day gets caught and resolved automatically, often within weeks.
“What follows is a specific, measurable revenue effect, not just a productivity story,” Ross said. Once the household view is clean and reconciliation friction is gone, rebalancing workflows run more often and track more closely with the firm’s actual investment strategy, a throughput gain that shows up directly in the numbers.
This article is produced in partnership with Flyer Financial Technologies
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