PC still presenting unreliable SMSF data: Class

class SMSFs self-managed super funds ATO productivity commission PC superannuation APRA funds super funds fees

18 January 2019
| By Hannah Wootton |
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After agitation from Class on the methodology by which the Productivity Commission calculated self-managed superannuation fund (SMSF) returns, the Commission modified its earlier findings to better reflect true returns in its final superannuation report, but Class has warned that aspects of its calculations on SMSF costs remain unreliable.

Class was last year concerned that the Australian Taxation Office’s (ATO’s) calculated SMSF returns, on which the Commission relied, were systematically understated compared to Australian Prudential Regulation Authority (APRA) funds, as different calculation methodologies were applied.

While the Commission responded to these concerns, Class still believed that its research findings were not fully reflected in the final report.

Notably, it said that instead of adjusting the ATO’s measure for contributions tax and insurance along with the denominator effect, the Commission adjusted findings solely for the latter factor. Class found that this was an adjustment of 0.44 percentage points rather than 1.15, warning that this represented less than half the actual impact.

The Commission also used the ATO’s ‘Expenses’ without adjustments as a measure of fees associated with SMSFs, which Class questioned as there are a number of items, such as insurance, interest and capital works, that the ATO classifies as expenses but are not fees.

In a submission to the Commission, Class pointed out that combining expenses and fees could overstate SMSF costs across all fund sizes.

Speaking on the submission, Class acting chief executive, Glenn Day, said: “Industry discussion continues around the need for increased member education when establishing SMSFs …  however there remains a separate need to understand the economic efficiency and viability of operating SMSFs at various net asset levels, using like-for-like comparisons and measures to avoid drawing incorrect conclusions on returns and costs, particularly for smaller SMSFs.”

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