Mercer slams competition watchdog for data errors in pension fund industry investigation
A leading player in the pension fund industry has slammed the competition watchdog for using inaccurate data in its probe into the sector.
The Competition and Markets Authority (CMA) report released in July found that there was a lack of competition in the investment consultancy which could cause "material customer detriment".
The UK chief exec of Mercer, one of the biggest firms in the fiduciary management (a type of asset management service) sector, Fiona Dunsire, wrote a scathing criticism of the CMA's investigation, saying it included errors which "cast doubt on the credibility of key aspects" of the report.
In a letter to the chair of the CMA's investigation into the sector John Wotton she said:
We have several concerns about the CMA’s data analysis. These include the use of incorrect data, errors in the CMA’s analytical code and reliance on unrepresentative sample
The CMA's data analysis on gains from engagement and on the relationship between quality and market shares – and on which it has relied to reach its provisional conclusion that there is an adverse effect on competition – is flawed, and any calculations of customer detriment are not reliable.
Mercer argued there were flaws in the data used to show how engaged trustees of pension funds were, and that correcting the data demonstrated there was "no statistically significant difference in the FM [fiduciary manager] fees paid by engaged and disengaged clients".
The letter goes on to say the issues were brought to the attention of the case team, who replied by saying they would not make the requested changes.
A spokesperson for the CMA said:
This is an extremely important sector that affects how well millions of people’s pension savings are invested – it’s vital we act to ensure competition is working properly.
We publish data and analysis so that people are able to test our findings and will consider all feedback before publishing a final decision. It’s not unusual for parties to challenge aspects of our analysis given the large and often complex data sets we analyse.