Dealing with GMP Reconciliation

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Phil Bradish, Head of Pensions Administration dicsusses how The Pensions Trust is approaching GMP reconciliation.

GMP reconciliation is just over two years away but The Pensions Trust committed to reconciling its GMP data in early 2014. Our goal is to complete this task pragmatically whilst still acting in the interest of our Members and Employers.

We began by comparing our data, at a high level, with HMRC’s figures, reviewing the membership status and different tolerance levels that could be applied. This high level analysis enabled us to understand the scale of the work involved and plan the resource required.

We set our tolerances at £2p.w. following a review of the data and set a timescale of 18 months to complete the work. We felt this level was fair to avoid unnecessary effort on small value cases, so we could focus on the more serious cases and keep costs down for our Employers.

Once we’d carried out our analysis we agreed our priorities for the reconciliation stage which included:

  • Extinguishing liability for non-members and ex-members.
  • Querying GMP over £2 p.w. tolerance.
  • Rectifying GMP on our administration system within £2p.w. tolerance for non-pensioner members.

    Our first tasks were to:
  • Close cases where we agreed all elements.
  • Send receiving scheme details to HMRC for historic transfers out.
  • Request the contracting-out earnings for those members who appeared over the tolerance level to compare with our records.

We’ve encountered issues along the way and the data provided by HMRC could be better - just having DOB and gender would help. Some schemes remain open to accrual and members have changed status since the data was requested.

We have many multiple memberships and needed to ensure we assigned the HMRC record to the correct membership. Also a lot of data provided is for active members who have switched from the DB to the DC section of a scheme. We work with our Employers to make this process as smooth as possible and so we hold a lot of data on members across various schemes.

However, our overall impression of HMRC has been good and we have a good relationship with the team there.

Since commencing the exercise we have agreed over 85% of our records, which is an excellent start. We’re about to begin the second stage investigations and our biggest concern is how we prove to HMRC that an individual is no longer, or never has been, a member of our schemes. Old data or a lack of historic data will make this difficult and how do you convince HMRC that they have incorrect information?

Following reconciliation will be the rectification process. If GMPs are incorrect the historic increases applied will be incorrect.

There are numerous approaches to this exercise each with its advantages and disadvantages but we want to be fair and pragmatic.

It’s essential to limit the communications and ongoing workload so it’s important to get this right first time.

We need to consider

  • The impact on scheme liabilities.
  • The numbers affected by any decision.
  • How we manage underpayments and overpayments. 
  • Whether to apply a triviality threshold.

This is a real chicken and egg situation. Rectification work needs to be completed using different methods to understand the best approach to take. Therefore, we are testing different methods to select the best approach.

Clear, timely communications will be important. Employers should be aware that HMRC will be writing to millions of people from December 2018 and we are all going to need a clear strategy to co-ordinate with this. We want to make sure we have everything ready to offer an efficient service for our Employers and Members. We also want to limit the impact on our administration and compliance teams when managing any queries.

The Pensions Trust is committed to ensuring that our data quality is excellent and that we act in the best interests of all who are impacted. This exercise will help us to provide an efficient and effective response in 2018, which is just what our Employers expect from us.