Validate bordereaux Premium BDX template

London Market Bordereaux Data Quality Guide 2026

Bordereaux quality has become a practical underwriting issue in the London Market. For delegated authority business, MGAs, coverholders, brokers, and capacity providers, poor BDX data is not just an operational annoyance. It slows renewals, weakens portfolio insight, creates audit questions, and makes it harder to prove performance by binder, class, territory, transaction type, and claim cause.

London's digital modernisation has shifted away from a single-platform promise and toward standards, interoperability, and better market plumbing. That makes basic data quality more important, not less. If systems need to talk to each other, the fields must mean the same thing.

What a good London Market bordereaux file proves

Quality question	Why it matters	Example evidence
Can every row be understood?	Underwriters and delegated authority teams need to know what transaction each row represents.	Unique risk reference, policy number, transaction type, effective date, expiry date, and reporting period.
Can premium be reconciled?	Capacity providers need confidence that gross, commission, taxes, fees, and net premium are not mixed together.	Gross written premium, commission amount, brokerage, tax, fees, net premium, currency, and settlement basis.
Can claims be interpreted?	Claims bordereaux need to show frequency, severity, reserve movement, closed claims, and large-loss drivers.	Loss paid, reserve, incurred, claim status, cause of loss, loss date, notification date, and recovery fields.
Can exposure be segmented?	Portfolio decisions depend on class, geography, limit, deductible, occupancy, construction, peril, and attachment.	Territory, class of business, limit, excess, location, occupancy, construction, and risk category.
Can exceptions be explained?	Missing or unusual data is manageable when it is identified before renewal or audit.	Exception log, validation notes, source system, manual override reason, and correction date.

Common bordereaux errors that weaken a renewal

Date confusion: inception date, transaction date, accounting date, loss date, and notification date are mixed or left blank.
Transaction ambiguity: new business, renewal, cancellation, endorsement, reinstatement, and adjustment rows are not clearly labelled.
Currency inconsistency: premium or claims values use different currencies without a currency field or conversion basis.
Premium leakage: gross premium, net premium, commission, tax, fees, and brokerage are combined in one field.
Claims reserve drift: open reserves move but there is no explanation of large changes or claim status.
Territory vagueness: country, state, postcode, or risk location is too broad to support accumulation or catastrophe review.
Free-text overload: key underwriting fields are buried in notes instead of structured columns.

Premium vs claims bordereaux: different jobs

Premium bordereaux should help the market understand written business, exposure mix, commission economics, binder usage, cancellations, and portfolio growth. Claims bordereaux should help the market understand loss emergence, reserve adequacy, frequency, severity, cause of loss, recovery, litigation, and large-loss movement. Combining those jobs into one loose spreadsheet often creates confusion.

A stronger process keeps premium and claims files separate, then connects them through stable references such as policy number, risk reference, binder, insured name, territory, class, and reporting period.

A practical validation workflow

Standardise headers: use consistent field names before anyone starts manual review.
Check required fields: flag missing policy number, transaction type, dates, premium, currency, territory, and class.
Validate dates: check date order and separate accounting, policy, transaction, loss, and reporting dates.
Reconcile money fields: confirm premium, commission, tax, fees, net amounts, paid losses, reserves, and incurred values.
Find duplicates: identify repeated rows, repeated policy references, and duplicate claim references.
Log exceptions: keep a record of missing values, corrected fields, and known limitations.
Summarise for renewal: show portfolio movement, loss development, data issues fixed, and issues still open.

Why this matters for London Market searches in 2026

Brokers and coverholders researching "bordereaux data quality" are usually not looking for a definition. They are trying to fix a market-facing problem: a renewal, audit, binder review, claims meeting, capacity conversation, or system migration. The useful answer is not a generic data-quality essay. It is a practical list of what the market needs to see and what errors will slow the file down.