Schemes are falling short on data. Here are five reasons to improve

A further 11 per cent of schemes do measure common data but told the regulator they do not know their most recent score. This means around 20 per cent of schemes have no idea of their current common data score.

Conditional data fares even worse, with 42 per cent of schemes confirming no activity in this area and 17 per cent claiming it is measured but the current score is unknown. Therefore, almost 60 per cent of schemes have no idea of their current conditional data score.

Although data quality is creeping in the right direction, it is clearly not enough.

The main reasons given by administrators for the non-measurement of common and conditional data are ‘lack of time’, ‘not a priority’, ‘no need to do this’ and ‘not relevant’.

Trustees must be genuinely convinced of the benefits to their scheme and members of excellent data quality. Trustees know it reduces error rates and facilitates liability reduction and derisking exercises, but what are the wider benefits?

Fraud prevention

There were more than 220,000 reported fraud cases in 2013; that is 25 every hour. Forty-nine per cent of all fraud is identity fraud.

Schemes that have lost contact with members are more susceptible to potential fraudsters. Every scheme should have an anti-fraud policy, but few do, and common data is a vital ingredient in the fight against identity fraud.

Budget reforms

The guidance guarantee is likely to bring with it an upsurge in member requests for retirement quotations and projections, and other queries. Schemes that struggle to meet the demand due to gaps in conditional data may fall foul of the spirit of the guidance guarantee, not to mention risking increased administration costs and member complaints.

Beating the GMP rush

HM Revenue & Customs has introduced a guaranteed minimum pension reconciliation service and the intention is to enable reconciliation of GMPs before December 2018. Schemes with excellent common data scores will have a massive head start on the member reconciliation part of this work, therefore minimising the time (and cost) spent on it by their administrator.

Going digital

Excellent administration includes web-based access where members can log in and view their profile, update their details and request and run retirement calculations.

The introduction of the flexibilities from April 2015 is likely to increase online member demand, and poor common and conditional data scores are potential barriers to its success.

Consolidation of member files

Member files exist either in paper form, electronic scans or older microfiches. However, the common and conditional data scores are a test against the administration database only. 

If conditional gaps in the database can be filled by reference to member files, in whatever format, then the reliance on such files – which can be lost, and cost money to keep and refer to – is diminished.

As well as publicising the above wider benefits, it would be helpful for the regulator to define the scope of data items covered by conditional data – with trustee freedom to tailor some data items as applicable to their scheme – rather than leaving the specification solely to trustees.

This would also enable the regulator to publish a target score for trustees to work towards. It would provide clarity and focus that so far has only been seen with common data work.

The regulator could ask the Pension Protection Fund to consider including data scores as an element of the PPF risk-based levy.

Trustees who take action to improve their scores should receive financial recognition. This would certainly put data quality more in the spotlight for the benefit of all, not least the members.

Rob Saville is a client manager at consultancy Punter Southall