The traditional approach to the assessment of pension scheme data is a reactionary one. A member approaches retirement and the administrators check their record and history to ensure that the benefits communicated and paid are correct, or the Regulator sets record keeping guidelines and schemes respond by implementing testing and reporting that provides a benchmark against the guidelines. I have often heard the former approach referred to as a “just in time” approach, but I think you could group both under a “just about enough” approach.
But the world is changing, and whilst not at the same pace as some sectors, pensions are changing too. Automation and digitisation are already commonplace, and I see no reason for their influence to reduce over coming years – quite the opposite in fact. Focusing purely on the fiduciary duty to pay the correct benefit to the correct people at the correct time, the methods used to achieve this in 2016 are vastly different to when schemes were set up and began to store and maintain data. The “just in time” approach is inefficient and exposes a scheme to unquantified risk – how can the liabilities be accurately valued if every time a benefit is to be crystallised a thorough manual check is needed to ensure that the records held aren’t flawed? And if the valuation is based on flawed data, how well matched is the investment strategy to the actual liabilities?
Then overlay any of the plethora of strategic projects that might be on a scheme’s flightpath; bulk-transfer exercises, pension increase exchanges or partial buy-ins to name but three. These all rely on varying specific datasets in order to be a success, and a “just in time” approach here is likely to represent a full-blown data-cleanse project in itself! What about the security of your scheme data? A few years ago, a pensions data audit was almost certainly focused on presence and accuracy. Today, the robustness of infrastructure, risk of hacking and controls around personal data being held is an increasingly common focus, in an area where a reactionary approach can be concerning and embarrassing for members, managers and sponsoring employers.
So what is the answer? How do you ensure you have identified all the risks your data might be exposing you to? How can you trust your data to support activities needed to achieve the best member outcomes? Don’t be reactionary. Think about data in the context of the wider scheme objectives, create a data management strategy that sets the path for achieving them. Make people accountable for its delivery, report on progress regularly and continually challenge and revisit it to ensure that if your objectives, or the landscape in which you are working change, your strategy reflects them.
Pension schemes can only ever be as successful, accurate and flexible as the data they hold, so the “in plenty of time” approach to data management is the only way to think, starting now.
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