Technical & training
IGRAP 1: Revenue recognition (Traffic fines)
July 14, 2014
DUCHARME ACCOUNTING, FINANCIAL MANAGEMENT & GOVERNANCE SUPPORT
IGRAP 1: ASB & National Treasury considerations on traffic fine revenue recognition
Accounting article: Impact of IGRAP 1 on Revenue considerations:
Many public sector entities are required in terms of legislation to provide non-exchange transactions, such as the levy of property rates, taxes, fines (traffic fines / library fines), licence fees, grants, subsidies and others, which results in revenue that needs to be appropriately recognised in terms of the Standards of GRAP. However, many times there are great uncertainty as to timing and extent of the collectability of these non-exchange revenues, resulting in possible material impacts on the revenue amounts disclosed in the annual financial statements of these public sector entities.
In May 2014, the Accounting Standards Board issued an updated Frequently Asked Questions on the Standards of GRAP (ASB FAQ), clarifying the recognition of Revenue from Non-Exchange Transactions in terms of GRAP 23 and iGRAP1 and as it pertains to revenue recognised.
In July 2014, National Treasury further issued an Accounting Guideline which outlines the principles that should be applied in accounting for traffic fines, based on where an entity acts as principal in relation to the issuing of traffic fines.
Ducharme prepared a summary article which sets out (i) a summary of iGRAP 1, applying the probability test on initial recognition of revenue; (ii) the ASB FAQ as to effect of iGRAP 1 on traffic fines as per Question 4.4. (May 2014 update); (iii) NT’s traffic fine accounting principles; and (iv) Ducharme’s summary of implementation issues / matters to consider regarding traffic fines revenue.
For the article, please click the PDF download link below to read more…
In essence, revenue recognition for non-exchange transactions can be summarised as follows:
- Initial recognition based on the probability of entitlement to collect; and
- Subsequent measurement based on the probability of collection.