The Declining State of Data Hygiene in the Pensions Industry

Gain valuable insights into the pivotal factors influencing data hygiene in the pensions industry and learn actionable steps to drive positive change.
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Data hygiene continues to decline at around 16.5% per annum

Public data suggests details for 1 in 6 members will change every year.

According to publicly sourced data, pension schemes can expect the details they have for members to change for 16.5% each year, or 17.5% if you factor in errors at input. 

That’s more than 1 in 6 member records that are likely to contain outdated or inaccurate data every year, which then compounds over time, creating more severe data challenges further down the line.

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Each year in the UK:

5% of the population moves to a new address

Most people in the UK will move house around 8 times during their lifetime[1]. Within a year roughly 1.2 million households will move home. Assuming an average household contains 2-3 people[2], that’s almost 3 million people a year moving to a new address, or 5% of the UK population[3]. This figure is likely to be higher for younger savers, who may be renting and may therefore change address more frequently.

1% of the population dies

According to the latest ONS data, there are on average 1,014.3 deaths per 100,000 people in the UK.

10% of the population changes job

So for workplace pensions in particular, softer contact details such as emails and mobile numbers provided may well change. The average person in the UK changes jobs every 5 years. Approximately 2.7% of people employed in the UK moved from one job to another in the first quarter of 2023 - the lowest rate per quarter since the second quarter of 2021[4].

0.5% of the population changes their name

In an average year, around 0.6% of the population gets married[5], whilst 0.4% get divorced[6]. In addition, around 0.1% of people in the UK change their name by deed poll each year[7].
Customer Data Management

Data Cleansing

Customer data drives critical business initiatives. Yet decisions are only as good as the quality of the data they rely upon and we regularly work with organisations that struggle with their data hygiene and subsequent customer analysis.

1% of member data contains inaccuracies.
The typical error rate in manual data entry is between 1-4%.

In an ideal world, members or their families would update personal data in a timely manner, but less than half actually do[8]. So, each year, schemes could be working with outdated, incorrect personal information for over half of their members whose details have changed. In addition to this, data will stagnate if left for long periods of time.

Traditionally, pension providers have had very few required touchpoints with members – perhaps only when they reach retirement, which means data hygiene can be left to worsen over long periods of time. However, with a major shift to digital and a more demanding member base seeking improved customer service and return on investment, the landscape has become far more competitive. The introduction of the Pensions Dashboard will also see an uplift in pension consolidation.

With many new retirees potentially having had no contact with their pension provider since policy inception, there’s a high probability that personal details will have changed in the interim, including vital address and contact details. Without a data cleanse, reconnecting with members and encouraging active engagement, providers also risk losing profitable customers to other schemes.

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So why should you care about data cleansing?

Missing or partial data also causes problems and inefficiencies, for instance:

Incorrect addresses

Missing or partial address details e.g. missing postcode or first line of address will impact on a scheme’s ability to locate and engage members. Postal costs are wasted; annual statements won't be received; leading to a disconnect and potentially a longer term gone-away problem.

Importance of full names

Failure to capture forenames, middle names or aliases can make identity verification or tracing scheme members who have moved address, considerably less efficient, as teams must manually work through false positives or inaccuracies.

Identifiable by DOB

Partial date of birth details can result in payout dates being incorrect, with major impact to the member.

Alternative beneficiaries

Not knowing whether a person is married or in a civil partnership impacts benefit calculations, which in turn can increase the risk to fund liquidity or potential buy-out price. It can also delay payments to beneficiaries following a bereavement, worsening their experience.

Learn how to improve the health of your pension scheme member data.

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