Letter and recommendations from the Offshore Compliance Advisory Committee

The Honourable Diane Lebouthillier, P.C., M.P.
Minister of National Revenue
7th Floor
555 MacKenzie Avenue
Ottawa, ON K1A 0L5

Dear Minister:

Re: OCAC Activities and the Processing and Analysis of "Big Data" by the Canada Revenue Agency ("CRA")

On behalf of the Offshore Compliance Advisory Committee (OCAC), I am pleased to provide you with an update on the work of OCAC since its last report in fall of 2016. Included in this letter are five recommendations with respect to CRA’s use of "Big Data".

Audit Agreement Policy

In February 2017, OCAC met with CRA officials to discuss their approach to agreements to resolve issues at audit stage. The committee members discussed a number of hypothetical fact patterns and the proposed resolution of those scenarios with CRA officials. As well, OCAC considered a CRA proposal for a new committee to examine settlement proposals made at audit stage where those settlements are material or precedent-setting. OCAC believes that such a committee would be a positive step in promoting principled and consistent audit resolution outcomes and we advised your officials accordingly. We understand that the CRA will be convening the committee this fall as a pilot project with a view to establishing final terms of reference and procedures for the committee in 2018.

Big Data

OCAC has also been examining CRA's developing practices with respect to the use of what is sometimes referred to as "big data" in its International and Large Business Audit Programs as well as its Offshore and Aggressive Tax Planning Programs. In completing this review, the OCAC benefited from presentations given by officials from the CRA. The subject was initially discussed in a general way in a conference call meeting in December 2016 and then the Committee met in person on June 13th with CRA officials to review presentations on this issue.

Big data is a term which is used to describe information flows containing large amounts of financial data relating to taxpayers, in volumes substantially larger than was available to the CRA using previous data sources and less sophisticated information systems. Please refer to Appendix A, which provides the list of "big data" sources considered as part of our review.

The sheer volume of such information (for example, we understand that CRA is now receiving more than 12 million international electronic funds transfer (EFT) reports annually) presents major challenges, particularly in extracting from a large number of mostly tax-compliant transactions those which require a closer inspection and audit. One major concern is that the high volume of data would consume so much of CRA’s available resources that the probability of detecting non-compliant behaviour would be reduced. To the extent taxpayers or their advisors became aware of this, the incidence of tax evasion or aggressive avoidance would likely increase.

The main focus of the June presentations was a description of an "integrated risk-based" approach developed by CRA that is applied to larger multi-national enterprises ("MNE") (MNEs realizing in excess of $250 million in annual gross revenue), and to high net worth individuals and associated trusts. This approach involves the application of the Integrated Risk Assessment System that employs a large number of linked algorithms which aggregate the data from the various sources referenced in appendix A relating to a particular MNE and its constituent legal entity components. The system will analyse the data automatically using the algorithms to produce a measure of the risks that the operations of the MNE pose to the Canadian tax system in different areas, including domestic non-compliance, tax avoidance, transfer pricing, foreign affiliates, and global allocation of income and taxes. CRA has used a multi-disciplinary approach in developing these algorithms, employing not only tax experts, but also economists, mathematicians and computer specialists.

It is important to note that this computer-based analysis does not, in itself, identify tax evasion or aggressive avoidance but it does identify the most likely targets for audit and therefore enables the most effective use of audit resources (and, as a by-product, likely reduces the audit burden on compliant taxpayers which are less likely to face annual or more intensive audits). The analysis encompasses both the MNE as an economic unit and its constituent legal entities. More specifically, it identifies the degree of risk that the MNE as a whole poses and which legal entities (which are the taxpayers for purposes of the Income Tax Act) are associated with the risk. The program also identifies particular areas of risk, such as transfer pricing or non-recognition of foreign-source income, and allocates those risks to the relevant legal entities within the MNE.

An essential second step in the process is the effective use of the information generated by this risk-based analysis by auditors to validate the risks identified by the Integrated Risk Assessment System and, if appropriate, to conduct a full compliance audit. We acknowledge that CRA is aware of the importance of this audit stage follow-up but we wish to emphasize how critically important it is to the overall success of the process. We note also the CRA has hired over 100 additional auditors to examine high risk MNEs and that specialist audit teams, that include lawyers and industry specialists, have been created.

We also reviewed with officials other measures being taken to use the new sources of data. CRA has previously disclosed publicly that EFTs relating to four selected tax haven jurisdictions have been analyzed in their entirety, identifying about 8,000 Canadian taxpayers. Of those, more than half have been sent "nudge" letters suggesting they may want to avoid an audit by making a voluntary disclosure and some are beginning to be selected for audit. The CRA has also increased by over 500% the number of audits of high net worth individuals and has increased by a factor of 12 the number of tax avoidance schemes examined annually.

The OCAC does not have the resources to evaluate the technical aspects of these data analysis processes, but based on the information provided, believes that they can only help CRA to become more effective in identifying the most fruitful audit targets. This will not only result in more efficient use and allocation of resources but will likely contribute to a perception among taxpayers that the risk of challenge to aggressive tax behaviour has significantly increased. This in turn should result in improved compliance. Perception is very important in this context because it influences behaviour and should reduce any incentive to play the audit lottery.

The one caveat we would enter is that the "data mining" process described above is only the first stage in the process. It must be followed up with effective auditing of the taxpayers otherwise these identified non-compliant behaviours will continue. The issues involved here, including attracting, retaining and training of audit staff, are beyond the scope of the OCAC’s review.


In respect of the "big data" processing activities described above, the OCAC recommends that:

  1. Metrics or other evaluation criteria be developed to measure the effectiveness of the data mining techniques now being used and developed.
  2. CRA work with the tax authorities of other countries to benefit from their experience to ensure that CRA’s data mining and analysis techniques become and remain among the most sophisticated in the world.
  3. The additional cost of those techniques be measured in terms of the additional tax revenue they generate. We would note, however, that the cost of these measures set against the additional revenue generated, is not the sole test of effectiveness. An effective program to combat offshore non-compliance will bolster public confidence in the tax system and have a positive effect generally on taxpayer compliance, whether domestic or offshore.
  4. Consideration be given as soon as possible to extending the risk analysis program to taxpayers other than large MNEs and the high net worth individuals associated with them.
  5. The existence and operation of these data mining techniques be given greater publicity to enhance public perception of the effectiveness of the tax system. Public perception is important in this context for at least two reasons:
    • It reminds non-compliant taxpayers that aggressive non-compliance behaviours are more likely to be detected and challenged, and
    • It reassures compliant taxpayers that tax is being imposed fairly so that all taxpayers are bearing their fair share of the tax burden, and consequently reinforces compliance generally.

In this respect, CRA might consider issuing annual or more frequent reports on the number of aggressive strategies which have been detected and assessed. Where such assessments have been upheld by the courts, a press release may be another appropriate action.

The OCAC would be pleased to meet at your convenience to discuss our review and these recommendations, if you wish.

Yours very truly,

Colin Campbell,
Chair, Offshore Compliance Advisory Committee

Appendix A – "Big Data" Sources Considered as Part of OCAC Review

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