On average our consultants have found financial organisations liable for US$3.9 Million in back fees per audit per data source (i.e. exchange/IDB). When multiplied by the number of data consumers that implies the overall total amount Banks can potentially owe their data suppliers counts in the Billions. Frightening isn’t it.

In general, the vast majority of financial institutions try hard to be compliant with their contracts with data suppliers. Inevitably, the majority under-resource their teams tasked with the job.

This means there is usually limited internal access to compliance expertise, and the time available to conduct a proper internal assessment of potential liabilities is not available.

Naturally the larger the institution the greater the number of sources, vendors, external links and internal market data flows. This produces a complex, fluid environment increasing the difficulty in managing market data on an enterprise basis. The result is the almost definite certainty that there is a lack of compliance somewhere within the organisation.  Both the auditors and the audited parties know this, but do not necessarily know where leakage is occurring.

This promotes a mutual acceptance of coming to a mutual agreement through a negotiated settlement. This results in:


Traditionally exchanges have been consistent in their strategy, go after the big financial institutions, then keep returning. As these Banks are usually concentrated in New York and London plus a few other centres, it has become an audit carousel. Some Banks are forced to manage 20+ audits simultaneously.

However, now the Big Banks are demanding, and getting, audit breaks, i.e. an exchange will not return for an audit for the next 3 years, or even longer.

This forces exchanges to seek new audit candidates, and are taking aim at a wider range of Tier 2 Banks, asset managers, hedge funds, retail brokerages and institutions, especially those based outside the main centres.

And these institutions are generally ill-prepared.

They lack the internal resources and expertise to defend themselves, and without experienced advice are all too willing to accept an exchange’s audit findings without question, or adequate validation.

The audit dragnet is growing in both breadth and depth of coverage. More institutions are being impacted and they need to be better equipped than they are today.


The level of audit competence varies significantly with the best setting high standards. But many auditors have little formal training, while motivation for others can be driven more by their commission opportunities than professionalism.

Some exchanges push the envelope in auditing to a degree that could, indeed, should be ethically questioned. In a desire to identify findings, interpretation of policies becomes elastic.

Other exchanges pay (usually external) auditors a bare minimum, with the resultant audit reports proving the old adage, ‘You get what you pay for’.

The result is the current practice of market data audits is broken because the process is often mutually antagonistic. Exchanges do not see the full results of the work while the data consumer is forced to invest in significant resources to manage and mitigate audit defences.

While market data audits are a necessary evil, and we are definitely not arguing they should be eliminated completely, MDG believes better ways exist for compliance to be policed which are not intrusive, are quicker to provide results, and promote engagement. We shall discuss how this can be achieved in the near future.

Our Interest

For transparency purposes, I must make clear that we as consultants have undertaken both audits and audit defences. It is a point of pride to say we have acted on the basis of absolute professional integrity, and great success.

We advise on market data strategies, sourcing, and cost savings. Contact us today to arrange for innovative unbiased advice.

Keiren Harris

31 August 2023

For our information on our consulting services please visit www.marketdata.guru/data-compliance

Or Email knharris@marketdata.guru

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