This article was featured in the November 2019 issue of the magazine. 

Henry Tapper, chief executive officer of AgeWage, discusses the unknown – the accuracy of pension contributions and the extent and impact of error – and invokes Monty Python imagery

In September 2018, the Financial Times reported on PensionSync research: “Millions of pounds of tax relief has been overpaid to workplace pension savers in the UK following errors made by tens of thousands of employers. Regulators conceded this week that workers had wrongly benefited from double doses of pensions tax relief due to employers making mistakes. The revelation came as new analysis suggested half of pension data sent to providers by employers was riddled with errors, including contributions being too low.”

The ‘Regulators’ in question was Neil Esslemont of The Pension Regulator (TPR) who was quoted in the article as saying only a “small percentage” of the 1,000,000 employers now offering workplace pension schemes “might be making mistakes” on tax relief, and were typically smaller employers without the help of a payroll team or pension advisers. He said errors could also mean some workers were not receiving tax relief they were entitled to.

Neil thought he knew that 95% of contributions had been compliant, but Ros Altmann and Pensionsync pointed out that we may never know if we got too little or too much money in our pot and whether we paid the right tax for the amount we contributed. Neil and Ros have moved on from the positions they held at the time of the article, but the unknown unknowns remain.

...those who hunt the holy grail of 100% accuracy are likely to be ambushed by the Knights of Ni...

 

Pensions data is like that, and those who hunt the holy grail of 100% accuracy are likely to be ambushed by the Knights of Ni – they are on a fool’s errand. TPR’s system of deterrence seems to be working but we must accept we will never know most of the winners and losers. The cost of audit and rectification may be greater than the cost of the original contributions.

As payrolls find better ways to integrate with HM Revenue & Customs (HMRC) through the provision of real time information, providers find better ways to integrate their record-keeping systems with the payment systems of the employers who participate in their workplace pensions. This process of continuous improvement will undoubtedly spit out some examples of bad practice and some of deliberate fraud. However, relations between providers and payroll have settled down, the miscreants of the early years of staging are in recuperation, and we have not seen any major casualties either in the worlds of pension provision or payroll.

So, some will say that baroness Altmann’s dire prognosis in September 2018 was alarmist. I will side with Ros in refocussing on the ‘nuts and bolts’. Without confidence in the fundamental mechanics, we cannot enjoy the journey; the engine of the car may be investment, but the chassis is data management.

If proof is needed of the importance of getting things right first time, look at the issues surrounding contracting out of the state earnings related pension scheme. Employers could elect that they and their staff paid reduced rate National Insurance contributions (NICs) for taking on the payment of guaranteed minimum pensions (GMPs) that would otherwise be paid by the state.

But the management of the data needed to record what was due was often woefully inadequate. Many pension schemes have had to go through what nerds call ‘GMP reconciliation’ before they can make sure that they comply with the rules for GMP equalisation. Actuaries will tell you that by the time these processes are completed, any commercial or personal advantage of contracting out will long since have disappeared.

 

...the money we are discussing belongs to people who will rely on its investable value in later life

 

This has led to some pension experts questioning whether compliance with this arcane area of pension benefits might not be consigned to the unknown-unknowns bin. That in search of data integrity we may be searching for a holy grail that is a phantom of spurious accuracy.

And skulking in the deep recesses of data management is another of pension’s dirty beasts: the money purchase contracting out regime where companies and individuals elected to contract out, not to guarantee a pension but to float their pension rights on the investment markets as ‘protected rights’. Whether the amounts paid as NICs rebates by the Newcastle offices of the then Department for Social Security are surely unknown unknowns. The only certainty we have is that we have no resource to reconcile these payments with people’s entitlements as identified by historic payroll records.

Ros Altmann was right to point out that we are taking much for granted with automatic enrolment (AE). She had commercial reason to do so, she was chair of a company that managed the compliance of contribution and data management for small employers participating in AE. The hope is that with most payrolls and providers moving to straight-through processing using APIs (application programming interfaces) rather than spreadsheets, with HMRC working with TPR, supplying real time information, and with open banking standards improving the timing of contributions, the scope for errors is reducing.

But there remain ‘unknown unknowns’: areas where payroll, providers and regulators trust rather than know. I suspect that – as with protected rights – the pragmatic approach will prevail and we will not seek to upturn every stone in the pursuit of 100% data integrity. But equally, I hope that there will be more like Ros Altmann reminding regulators and employers that the money we are discussing belongs to people who will rely on its investable value in later life. It is their data and it needs to be treated with respect.

These may be ‘nuts and bolts’ issues, but they secure the chassis of the car. If those nuts and bolts come loose, the journey could be most unpleasant. We need to know the scope of our unknowns and seek to eliminate uncertainty rather than wallow in data complacency. 

• Policy article
• Professional magazine
• Pensions