Data Normalisation

One trade. Twenty platforms. Twenty versions of the truth.

A single trade moves through front office, middle office, custodians, clearing houses, and regulators, each holding its own copy, in its own format. Data Normalisation converts every one of them into a single CDM-standard Unified Trade Record, so every downstream workflow finally works from the same data.

$12.9M

Average annual cost of poor data quality (Gartner, 2020 Magic Quadrant for Data Quality Solutions)

20+

Systems a single trade typically passes through before settlement

Reduced reconciliation overhead: one record replaces a patchwork of incompatible ones.
Errors caught at entry, not at settlement: the 1-10-100 rule: the later a data error is found, the more it costs to fix.
Faster downstream processing: every other Tokenovate workflow reads from one standards-based record.

Accepts Email CSV FpML FIX ISO 20022

Preview of the Trade Data Normalisation one-pager

Get the Data Normalisation one-pager

A concise breakdown of how Tokenovate turns fragmented trade data into a single CDM-standard record.

How Data Normalisation works

Three functions, one pass: upstream of every other Tokenovate workflow.

01 — Ingest

Universal ingestion layer

Email, CSV, FpML, FIX, and ISO 20022 accepted natively, regardless of source system.

02 — Validate

Validation & enrichment

Rules-based checks and reference data applied automatically, before an error can propagate.

03 — Standardise

Schema translation

Every input converted to a single CDM-standard Unified Trade Record.