Classification and calculation of ‘entertainment’ benefits and how to leverage technology

In a post COVID-19 environment, many organisations have returned to former levels of discretionary spending, including with respect to food, drink and recreation expenditure. 

In this regard, one of the ongoing challenges in preparing the Fringe Benefits Tax (FBT) return is the analysis and classification of these types of benefits—do they constitute ‘entertainment’?—and the calculation of the associated taxable value (Is a per-head breakdown available? Who attended and how regularly/frequently have they been provided with associated benefits? etc.).

For example, in relation to ‘meal entertainment’, the three valuation methodologies available to employers—the actual method, the 50/50 method and the less commonly utilised 12-week register method—each require different levels of record keeping. And the methodology chosen also impacts the availability of concessions. 

To that end, an optimal FBT outcome heavily relies upon the method that is elected and applied, which in turn depends on the data detail available and the capacity and resourcing to mine the same. By way of illustration, the 50/50 method broadly seeks to tax all (well, 50% of) ‘meal entertainment’ benefits irrespective of recipient (employee or non-employee), whilst the actual method only seeks to tax benefits provided to employees and associates and with other exemptions potentially available. The latter method necessarily requires more detailed analysis to identify recipients, hence, is data-dependent, including with respect to the application of concessions. 

The emergence of technology ‘tools’, including artificial intelligence (AI) platforms, has provided a unique and innovative capacity to automate aspects of the FBT data collection and analysis. However, ultimately, the analysis and associated record-keeping is necessarily bespoke to each organisation’s profile and benefits.

The proliferation of customisable expense management systems, coupled with curated general ledger mapping, has significantly improved the scope and quality of data now available to organisations when undertaking transactional analysis. The introduction of AI is seeing further streamlining—some systems now have the capability to review invoices (from photos) and reconcile that against a claimant’s online calendar to pre-populate data fields in an expense claim.

Where your business processes, through use of technology (developing ‘rules’ or ‘parameters’ applicable to your profile and benefits), can leverage this improved data to categorise expenses according to pre-defined criteria, the ongoing challenges and resourcing demands associated with ‘entertainment’ analysis can be reduced.

For example, the ‘rules’/’parameters’ could be built around specific data attributes (‘expense type’ field from the expense management system, vendor allocation, ‘transaction description’ entered by a claimant, destination general ledger posting, etc.), with a focus on hierarchy (i.e. which ‘rules/’parameters’ apply first). 

Generally, there is investment upfront to customise the technology to the organisation’s profile and nature of benefits – for example, an organisation that frequently entertains employees on work premises may seek to develop an upfront ‘rule’/’parameter’ that excludes these food/drink transactions on the basis that it is exempt, through adoption of the actual method of valuation. 

Once appropriately curated, automated classification significantly reduces the risk of human error and the need for oversight, and seeks to apply an indiscriminate, uniform approach, based simply on documented rules and principles without the bias of human discretion. Further, with a continued improvement mindset, the technology can be further customised to identify specific transaction values, suppliers and spending within unauthorised categories. This would allow areas of concern to become readily identifiable in a timely manner which enables employers to undertake prompt corrective or investigatory action.

Commonly, employers who are unable to substantiate key elements of ‘entertainment’-related spend are limited in their valuation methodology (for example, to the 50/50 method – noting that that method is not available for recreational ‘entertainment’ benefits) - and consequently tend to pay more FBT than would otherwise have applied, had appropriate data been collated throughout the FBT year. 

This may also include treating transactions as ‘entertainment’ where it may not be. As set out in Taxation Ruling TR 97/17 Income tax and fringe benefits tax: entertainment by way of food or drink, with respect to food/drink, each benefit should be assessed against the following factors:

1. why the food or drink is being provided
2. what type of food or drink is being provided
3. when that food or drink is being provided, and
4. where the food or drink is being provided.

Further, key exemptions, such as the on-premises exemption (which exempts food/drink consumed by a current employee on work premises on a working day) and the minor benefits exemption (which exempts benefits where the taxable value is less than $300 (including GST) and where, amongst other factors, it is considered that associated benefits are provided infrequently/irregularly) are not available under the 50/50 method.

Therefore, leveraging technology may not only have the benefit of alleviating resourcing and compliance constraints, but may also provide financial advantages due to the accurate classification of transactions and the capacity to access concessions.

Global investment and buy-in from developers and organisations have resulted in a once in a lifetime opportunity to revolutionise the way businesses operate. For example, this is evidenced by the deployment of AI in expense management systems which not only automate claims for employees but also provide richer and more detailed data.

It follows that tax compliance processes are on the verge of transformative breakthroughs—an opportunity to reframe the role of tax by leveraging technology including within core business processes and systems (e.g. expense management systems). Notably, insights from PwC’s 28^th Annual Global CEO Survey ⁠CEO survey reveal that 42% of Australia’s CEOs have observed increased efficiencies in their workers' time over the last year as a direct result of GenAI, with 40% expecting their investments in the technology will lead to increased profits in the year ahead.

For more information on how PwC can support you and your business in this area, please refer to our Workforce Automate website, a modular technology solution which includes automation of expense classification and FBT calculations.

If you have any questions about your FBT obligations, please reach out to your PwC Employment Taxes Specialist.