Outrun: Bordereaux Accuracy – An Unfixable Problem?

It isn’t a process flaw, it’s a data architecture problem

The market often talks about the need to improve bordereaux processes in order to deliver high quality, accurate data to capacity providers. The real issue though lies deeper. It isn’t about better checklists or stricter review; it’s about the underlying data architecture. And until that is addressed, bordereaux accuracy will remain a recurring headache.

The root of the problem: siloed systems, fractured data

For many MGAs, data lives in multiple unconnected systems. Policy administration, underwriting, transaction data is often in different platforms and spreadsheets.

When a policy is modified, whether by endorsement, cancellation, or mid-term adjustment, that change may be updated in one system but easily overlooked in another. A premium entry may be posted to accounting but not linked to the correct risk. A risk cancelled on the policy admin system may still exist in its uncancelled state on the system used for bordereaux production.

Those kinds of inconsistencies aren’t immediately identifiable; they quietly build up in the background until a monthly bordereaux or broker statement is produced with errors. Every underwriter, as well as every operations and finance person, knows the pain of manually digging into discrepancies to identify and resolve these data issues. For some organisations, bordereaux management has become a reactive firefight rather than a routine exercise. That’s not just inefficient; for MGAs wanting to scale quickly, it can be debilitating. Operational teams end up spending vast amounts of time “unpicking what went wrong”, rather than focusing on underwriting, growth and delivering new products.

Why most bordereaux delivery remains fragile

Even in firms that recognise this risk, many “bordereaux solutions” only paper over the cracks. They pull data from several sources, merge them, and produce a report that looks right. But because the underlying data still lives in silos, each bordereaux becomes a fragile construct, vulnerable to human error and late adjustments.

The moment a cancelled policy line is removed manually, or an amendment is applied after a bordereaux snapshot is taken, the integrity of the document becomes suspect. In the most frustrating cases, error detection only happens once capacity providers or brokers query a discrepancy.

A better way: unified data, live bordereaux

This is where Outrun takes a fundamentally different view. From the ground up, Outrun is built around a unified data model. Client, policy, risk, and transaction data all live in a single source of truth, not in separate unconnected systems.

That means that when a policy is cancelled, the cancellation is reflected everywhere at once. When a transaction is posted, it’s automatically tied to the right policy and version. When risk data changes, e.g. an MTA for increased sums insured, the change is immediately visible across the platform.

Crucially, bordereaux and broker statements are produced directly from live data, not from a manually compiled export. No more spreadsheet stitching. No more post-production edits or ad hoc line removals. What is produced is a real time, accurate representation of the risks on cover.

The benefits: less friction, more trust, faster growth

Implementing a true unified data architecture brings benefits across the board:

Operational efficiency: Bordereaux delivery becomes a by-product of the live system. No more “reconciliation days” or heavy report preparation cycles.

• Reduced risk of errors: Eliminating manual intervention and data duplication removes the key sources of error. What’s in the system is what gets reported.
• Scalability without friction: As MGAs grow the data model scales automatically. More business doesn’t increase manual workload.
• Stronger capacity relationships: Insurers and capacity providers increasingly expect accurate, timely, audit-ready reporting. Consistent, reconciled bordereaux demonstrate operational maturity and reliability, building trust and smoothing capacity negotiations.
• Time to focus on value-add: With less resource spent on admin and clean-up, MGAs can redirect effort toward underwriting excellence, product innovation, and broker relationships.

Why “fixing bordereaux” isn’t enough; fix the data

The industry tendency to treat bordereaux issues as process flaws or people problems is understandable, because those are the symptoms. But without addressing the fragmented data architecture root cause, any process improvement is bound to be temporary. Platforms that simply aggregate data from separate systems and output bordereaux are like building a composite picture from mismatched jigsaw pieces. It may look like a full image, but it lacks structural integrity.

Outrun offers a different foundation: a single, consistent dataset powering everything – underwriting, policy admin, accounting and reporting. For MGAs serious about operational resilience and scale, unified data is essential.