We all complain about inconsistent provider data — but few understand just how deep the problem goes.

In this blog we cover;

• Why inconsistent LoA data creates operational and compliance risks.

• The structural reasons standardisation remains painfully slow.

• What’s actually happening across the industry to change this.

• How AI solves data chaos today without waiting for reform.

The Pain: Inconsistent LoA Data

Same policy, different data.

One provider sends a neat email summary, another dumps a PDF with half the info missing, and the third sends some variation of War and Peace (still with half the info somehow missing).

Meanwhile, your admin team is knee-deep in chaser emails, spending hours trying to piece together a full picture of the policy as best they can. It’s not just annoying — it’s expensive.

Valuable hours are wasted trawling through pages of data packs and flagging what’s missing. And while it’s easy for us to roll our eyes at providers, there’s a deeper problem here — one that’s become too costly to ignore.

Why It Matters: Consumer Duty

This isn’t just operational pain — it’s a regulatory issue.

Under Consumer Duty, firms are now expected to “enable and support customers promptly.” But when LoA responses are inconsistent and unreliable, it delays recommendations, creates confusion, and ultimately harms the end-client.

And let’s be honest: “We’re still waiting on the provider” doesn’t fly when a prospect is sitting in front of you having done everything you asked of them over a month ago.

Lack of standardisation doesn’t just slow things down. It creates a risk trail. And we can be sure the regulator is watching.

The Real Problem: Why Standardisation Is So Hard

Here’s the frustrating part: everyone agrees standardisation of provider data is the goal. But getting there? That’s difficult.

Providers are sitting on their custom, legacy tech stacks. Some of the data advice firms are asking for isn’t stored centrally — in some cases, it’s not stored at all.

Then there’s project prioritisation. We’ve said this before, but why would a provider invest significant capital to speed up transfers? It’s like asking Netflix to design a super-slick flow to make cancelling your subscription as easy as possible. There’s a clear conflict of interest.

Even if a provider team wants to improve things, they still have to get board approval, prove ROI, and compete for dev resources. In a volatile market, who’s voting for a project that makes it easier for clients to leave?

So yes — standardisation is the goal, a noble goal at that - but let’s not kid ourselves about the timeline. We need attention, probably even mandates and legislation, but most of all time.

What’s Happening: Industry Efforts

There are some promising moves.

Criterion’s ‘LoA Standards’ framework is defining a unified LoA Data Checklist — a robust, consensus-driven benchmark for “what good looks like” across the board.

The Fixed LoA Action Group (FLAG) is rallying providers, platforms, tech vendors and intermediaries around the same table. It’s a rare example of real industry collaboration.

But it’s slow. Provider organisations are huge, with billions under management. Add in the regulatory layer, and change becomes a long-game. Even with the best intentions, we’re looking at years — not quarters — before anything resembling full standardisation becomes reality. And that’s if legislation forces it through. If not? Expect glacial progress.

Whilst the talk is great, firms need action.

So What Can We Do Now?

We can’t afford to wait 4–7 years to improve turnaround times. Not for advice firms trying to grow. Not for their support teams. And definitely not for clients.

This is where AI flips the script.

Traditional software relies on rules. And rules break down when faced with 150+ providers, all formatting data differently, all varying in what they include. AI, by contrast, thrives in ambiguity. It doesn’t need every provider to conform — it learns from the mess.

At 4admin, we’ve built AI specifically to process this chaos.

We extract key data points from unstructured, non-standard documents, highlight gaps instantly, and flag follow-up actions automatically. This isn’t theoretical. It’s live, in production, working across thousands of plans. And it’s getting smarter every day.

While the industry debates standardisation, AI lets us move now — saving time, reducing errors, and creating a better experience across the board.

Standards vs Smart Tech — We Need Both

To be clear — we’re bullish on standardisation. It’s still the right long-term goal. But we also need to be pragmatic. That won’t happen overnight. So in the meantime, AI gives us a way to act — not just wait.

It’s not a binary choice. It’s not “either/or.” It’s “yes, and.” Standards + smart automation. Industry reform + practical tools that make a difference today.

All we know is, waiting isn't a strategy.