Pension Funds Insider

Pension Funds Insider brings the latest pensions news and industry insights; from investment and governance updates to new mandate appointments and pensions regulatory information.

Schemes are unprepared for de-risking challenge

Tuesday, August 27, 2013

Image for Schemes are unprepared for de-risking challenge

Despite nearly one in four pension professionals believing that the level of de-risking will increase dramatically, many schemes may be unprepared to de-risk themselves, research commissioned by EDM Group has revealed.

A further 41% pension professional expect a slight increase in the level of de-risking, however the group said that plans to de-risk pension schemes could be hampered by the poor quality of information held by many schemes.

According to the research, only 5% of those questioned believe that the quality of data collection by DB schemes is 'excellent' and only 3.7% say the same about how it is managed.

Sam Ferguson, EDM Group CEO, said: "De-risking presents an administrative challenge to DB pension schemes that some may not be prepared for. Any de-risking solution provider will demand that member information is accurate, complete, up to date, and that the full extent of the member contributions and scheme liabilities are visible.

"Many of these providers will not want the administrative burden of paper or microfilm archives and will insist on electronic data that is more easily ingested and interpreted. However, we believe that in many cases, the collection and management of scheme information is poor, and this represents a huge challenge in terms of meeting any de-risking goals."

He said that he expects to see a huge increase in the amount of organisations spend on improving their DB data collection and information so that they can deal with this problem, and added that "much more" will be outsourced.

EDM Group has said that "far too much" of the information held by DB schemes is either paper-based or on microfilm, and 34% of pension professionals think this makes analysis more time consuming and 32% said it can make it difficult, slow and costly to retrieve. Some 31% said it can be difficult to integrate the data with business applications.

First published 27.08.2013

monique_simpson@wilmington.co.uk