Compliance teams have heard the phrase "garbage in, garbage out" for years. What's changed is how much is now riding on it. As disclosure timelines shrink, in some jurisdictions to same-day filing, and as firms start layering AI and agentic workflows on top of their compliance processes, the quality of the data feeding those processes has become the whole game.
That was the central theme of a recent joint webinar between BlackRock's Aladdin platform and FundApps, marking the completion of a direct integration between the two systems. Speaking were Kuhu Dixit, Senior Product Manager for Investment Compliance Technology at Aladdin, and Will Bryceson, Product Manager at FundApps. Here are the key themes from that conversation.
It's rarely one dramatic failure. It's a series of small handoffs, each one introducing a little more risk. Will Bryceson broke the typical journey into five steps:
Kuhu Dixit made the same point from the other side of the workflow. From Aladdin's perspective, the challenge is rarely a lack of data, it's what happens after that data leaves the platform. Once firms start running their own mapping and transformation logic outside a governed system of record, that logic becomes hard to maintain and harder still to keep up to date as disclosure rules evolve.
Both speakers agreed on why this persists: bespoke, in-house pipelines feel like the path of least resistance. There's no invoice for it the way there is with a vendor contract, so the real cost, engineering hours, maintenance, and institutional knowledge locked in one person's head, stays hidden inside the tech team instead of being weighed as a real business decision.
Dave Polonsky shared a case that captures exactly what's at stake. A client's legacy internal data feed, patched together over decades, had an incorrect conversion ratio baked in for a convertible bond. The compliance engine did exactly what it was built to do: it calculated the threshold and filed. The result was a public disclosure showing a position roughly 100 times larger than what the firm actually held, followed by a scramble to explain it to regulators, investors, and their own front office.
The system worked on the wrong data. That's why, as Kuhu explained, regulators and auditors are no longer just asking what was reported, they're asking how the result was reached. When data passes through several systems before reaching a filing decision, demonstrating that lineage becomes genuinely difficult, and an internal data quality issue can turn into a regulatory one very quickly.
This is where the Aladdin and FundApps integration comes in. Kuhu described the shift plainly: no more extracting data from Aladdin, transforming it offline, and feeding it into another system by hand. Instead, Aladdin remains the source of investment and reference data, and FundApps becomes the execution layer that consumes it directly.
In practice, Aladdin generates daily position, security, and transaction data, transferred to FundApps through a secure, standardised process with no manual intervention. FundApps applies its own shared, regulatory-grade mapping logic, built once and reused across its client base, and layers in enrichment from sources like the SEC, ESMA, and various takeover panels.
Will framed this as the value of a trusted "golden source." When you have confidence in where your data originates, you can interrogate it and file against it with confidence, rather than relying on an opaque, on-site pipeline that might hide a problem until the worst possible moment, right before a T+1 or T+0 deadline.
The practical payoff, according to both speakers, is a shift in where people spend their time. Instead of validating inputs or managing an ageing internal pipeline, teams can focus on reviewing outputs, handling genuine exceptions, and making decisions.
Will connected this to a broader industry shift, from running everything on-site toward managed services, not unlike the earlier move from on-premise software to SaaS. Compliance doesn't generate revenue directly, so it's increasingly hard to justify dedicating scarce engineering resources to bespoke data plumbing when a specialist vendor can do it more reliably and at scale.
There's a forward-looking piece too. Kuhu noted that AI and agentic workflows only amplify the need for this foundation, an AI agent working with unreliable data hits the same problems a human analyst does, just faster. Only with clean, auditable data does it make sense to layer in AI to investigate exceptions, trace ownership calculations, or gather evidence for a regulatory review.
Compliance outcomes are only ever as good as the data feeding them, and the biggest source of risk sits in the gap between systems, not the systems themselves. Aladdin and FundApps are both strong platforms individually. What this integration is meant to solve is the handoff between them: a single trusted source of data, flowing automatically, with the lineage and auditability to back up every filing decision.
If you're an Aladdin client curious about FundApps, or a FundApps client wanting to learn more about Aladdin, this integration is live now, not on a roadmap. Speak to the team today.