Market Data Guru has identified an average revenue leakage of 22%+ per annum for exchanges, inter-dealer brokers, other data sources and vendors. The corollary of this means the data consumers, i.e. financial institutions and other market participants are not paying for all the data they are using.

In a recent post MDG estimated financial institutions exposures caused by out of scope, i.e. non compliant data usage to be at a minimum of $1.7 Billion per annum, with another average of $3.3 Million per audit finding. You can read more here.

In the past Market Data Managers could mitigate the problem by negotiating settlements with data source owners like exchanges with payments far lower than the calculated monetary exposure. This resulted in gained data usage at significant discounts rewarded by grateful bosses.

However regulators now increasingly view this as providing an unfair competitive advantage to banks willing to tolerate lax data compliance and poor behaviour compared to peers making the effort to be compliant (Which is the majority). This means the days of freebies are being replaced by payment in full, something that will come as an expensive shock to many financial institutions.

This should lead to financial institutions working towards better data compliance and eliminating the problems before they get out of control. Unfortunately there will always be a minority that ignore the risks or believe the odds of being caught to be negligible.

Such attitudes will backfire, exchanges and vendors are finding traditional audits don’t deliver and are even counter-productive. The alternative means adopting more pro-active compliance measures increasing the chances that non-compliance is both identified with 100% of liabilities paid.

Smart data consumers and banks will pre-empt the problem and associated costs by ensuring data compliance.


The root causes of non-compliance stem from mis-reporting and under-reporting of their data’s usage by end user institutions and vendors. Too often internal issues exacerbate the problem through:

1.Not knowing where data is being distributed to, or how it is being processed

2.A lack of tracking data workflows

3.Unmanaged data requests for usage (especially for new applications and IT development purposes)

4.Data consumers have finite resources and time to be able to resolve these issues, lack training, often because bean counters rarely invest in market data management, their expertise and experience in knowing where the bodies are buried. Employing cheap under-skilled labour for such highly knowledge based roles introduces unacceptable risk.

Despite the availability of first class tools (MDSL/TRG Screen) the result is end user and vendor usage reports for internal and external review are opaque, incomplete, nor structured for effective analysis, even when they are requested or otherwise provided. This is especially prevalent in the areas of Non-Display Usage, Derived Data Creation, CfD Creation, Index/Financial Benchmarks, and Digital Media.

Reporting ends up being siloed and reactive, especially for discretionary data usage, i.e. corporate actions, reference data that is requested on demand and charged on a per unit basis. Result, unnecessary costs.

It does not help that many exchange’s pricing models can be over-complex and policies sometimes deliberately vague ensuring true compliance is not achievable. Then there is the lack of global standards in terms of definitions concerning usage. Many exchanges still do not understand that for instance derived data and non-display usage are completely different beasts and ought to be treated appropriately. They are not the same thing, and regulators have yet to identify this as an issue they can address.


The great thing is data compliance does not have to be a financial burden if properly implemented through a regime of due diligence encompassing the following eight steps:

1.Identify the extent of the data non-compliance and calculate in dollar terms

2.Identify where out of scope data usage is occurring, and by whom, with supporting evidence

3.Develop and implement a strategy to bring the data end users into compliance

4.Develop policies and procedures to avoid future non-compliance

5.Put in place the administrative tools to provide accurate and complete reporting of data usage

6.Conduct regular validation of data and licence requirements

7.Proactively mitigate data non-compliance

8.Employ, when necessary, experienced external resources like consultants (Market Data Guru for example) to review, analyse, report, and mitigate data compliance and potential dollar cost problems

Financial institutions and data consumers must realise best practice data compliance is always cheaper than letting risks fester both in terms of unnecessary and expensive dollar costs and the reputational damage it causes because of the usually correct assumption that if one area has a problem, then so does others’.

Keiren Harris 24 May 2023

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