HMRC Competition to Identify Deliberate Evasion and Help Close the Tax Gap

Description

Small business accounts for approximately 60% of the UK tax gap. This is driven by a range of customer behaviours from simple error through to deliberate evasion. Identifying deliberate evasion is inherently difficult across a very large population of more than 5m customers. By its nature its intent is to hide and deceive. This can lead to risk targeting and response being more costly for HMRC which impacts on our ability to close the tax gap and can increase burdens on compliant customers.
Using data to identify potential deliberate evasion in our analytical risking processes may help improve HMRC's approach to managing this risk and the customer impacts of that. We would like to explore novel analytical techniques and data that help identify indicators of potential evasion in our risking processes. 
We are seeking solution(s) that can help close the tax gap by identifying deliberate evasion behaviour among small business customers.
We are open to exploring a variety of potential solutions that achieve this objective. While not a formal requirement, we anticipate that some solutions will:
(a)	Identify or confirm potential evasion, by predicting behaviour,
(b)	Explore different uses of data available to HMRC or third parties.
Further information and context on this problem statement is available in the tender documentation.
The challenge to identify indicators of evasion:
•	There are an estimated 5.45 million small businesses in the UK (0 to 49 employees).
•	Small businesses operate in all of our main tax regimes: Corporation Tax, VAT, PAYE, Income Tax Self-Assessment.
•	Small business operate across almost all sectors of the economy and evasion can be more prevalent in some sectors and populations than others.
•	We have access to significant amounts of data provided by customers in their tax returns which can be monthly, quarterly, annual and transactional depending on the tax regime.
•	We also have access to some Third Party Data, e.g. Merchant Acquirer data.
•	We use at - scale analytics to detect anomalies as indicators of risk for further investigation.
•	Analysis to detect indicators of behaviour, specifically evasion behaviour, is challenging.
•	This can lead to risk targeting and response being more costly for HMRC and burdensome for the customer.