Regulatory data quality for

MiFID II and its related regulation, MIFIR, was one of the first wide-ranging financial directives to put significant focus on post-reporting data quality checks, requiring front office records against data reported to the regulator.

However the scope and obligations of MiFID reporting present inherent data risks, especially when reporting through a third party. This means firms need to carry out pre- and post-submission reconciliations to check original data against the final submission.

Who has to report?

Buy-side and sell-side firms reporting on their own behalf or through a third party/ARM

Exchanges and ARMs reporting on behalf of members

Meet the challenges of
MiFID II post-reporting reconciliations

Many firms are still struggling with MiFID II data quality controls. Embedded or legacy reporting tools may not have the robust match rates and reconciliation capabilities you need for post-reporting checks. They may also require long projects or manual workarounds when business needs or regulations change. And with MiFID III on the horizon, fields will likely be changing again.

Now is the time to rethink your model and find a tool that has the flexibility you need to stay compliant while adapting to business and regulatory changes.


Enrichment leads to data risk

Legacy systems often can’t handle the data transformation and enrichment that happens prior to submission. Reference data like LEIs and ISINs, and 3rd party processes make it hard to trace errors back to source, but missing them can lead to audits and fines.

Filter out enrichment noise

Set up pre- and post-submission reconciliations quickly and easily. Configure reconciliations between the transitions to ensure consistent data throughout. With enhanced workflow, you can link outputs to navigate to underlying issues easily.


Ensuring data quality

Data elements like instrument ID code, maturity date and expiry date formats will differ by asset class. Each asset class will likely need its own reconciliation, which can be challenging to set up and manage on legacy systems with inflexible schemas.

Increase agility and ditch ETL

With Duco you’re not constrained by restrictive data models or lengthy ETL processes. You can take in asset classes or market segments quickly, while retaining visibility of the processes where data could break down.

Book a regulatory data quality workshop

Want to discover how firms just like yours are tackling the challenges of meeting regulatory data quality requirements?

Book a one-to-one data quality workshop to uncover your true reconciliation footprint, revealing:

How much time and money your business is spending on data quality and reconciliation for regulatory data

The volume of data you’re processing and the chokepoints between systems

The impact of automating these reconciliation and data quality processes