London, 10 February 2020: Analysis of current pension data quality by PensionBee estimates that savers would find just six out of ten of their pensions upon logging in to the Pensions Dashboard when it launches in the 2020s.
PensionBee, the UK’s leading online pension provider, has found that pension savers would only locate 61% of their pensions when they log in to the Pensions Dashboard for the first time unless drastic data cleansing actions are undertaken by the pensions industry.
Percentage of pensions found based on matching
|Major master trusts||Other providers||Total pension sector|
|Outcome||Pensions (%)||Pensions (%)||Pensions (%)|
|Found||1,758 (79%)||2,298 (52%)||4,056 (61%)|
|Partially found||320 (14%)||557 (12%)||877 (13%)|
|Not found||137 (6%)||1,605 (36%)||1,742 (26%)|
|Total||2,215 (100%)||4,460 (100%)||6,675 (100%)|
Source: PensionBee, based on 6,675 pension transfers initiated between July and November 2019. “Found” indicates pensions that are identified based on a match of name, address, national insurance number and date of birth. “Partially found” is where only some of this data matches a pension record and a customer is required to take corrective action. “Not found” indicates the pension has not been found although PensionBee had good reason to search (e.g. the customer gave a provider name or an employer name that is in our database). Major master trust providers are National Employment Savings Trust (NEST), B&CE The People’s Pension, Smart Pension and Now Pensions. Other providers are Accenture, Aegon, Aon Hewitt, Aviva, AXA, Barnett Waddingham, BlackRock, Canada Life, Capita, Civil Service Pensions, Clerical Medical, Corpad, DHL, Equiniti, Equitable Life, Fidelity, Friends Life, Friends Provident, Hargreaves Lansdown, Hymans Robertson, JLT, Legal & General, Local Government Pension Scheme, Mercer, NFU Mutual, Nutmeg, Old Mutual Wealth, Phoenix Life, Prudential, Punter Southall, ReAssure, Royal London, RPMI, Scottish Widows, St James’s Place Wealth Management, Standard Life, Sun Life Financial of Canada, Tesco Pensions, Towers Watson, True Potential, Virgin, Xafinity, Xerox, Zurich and others. Percentages are rounded to the nearest whole number.
To gain an understanding of data quality by provider type, PensionBee analysed the data of over 6,500 instances where it was required to contact a pension provider, in search of a mutual customer’s pension, between July and November 2019. It looked at the number of pensions that could be matched on first try, those that could be matched based on partial identification, and those that could not be matched despite the belief that a pension pot exists. PensionBee excluded pensions where it had enriched data, including policy numbers and additional information, which results in a higher location rate for its own customers.
In each instance of this analysis PensionBee used the four key elements of data required to uniquely identify a consumer’s pension: name, date of birth, National Insurance number and address. Data was supplied in the most up-to-date format, as recently shared by customers, reflecting the level of data accuracy a consumer will use when accessing the dashboard for the first time.
The government plans to use digital ID to identify a consumer’s pension, but this is not likely to be available in time for the launch of the Dashboard in the next few years. Therefore the dashboard will likely provide data to consumers based on matching, much as pension data is shared today.
The findings show a clear distinction in data quality between newer master trusts and older contract-based schemes, differences which can be attributed to the variance in both the quality and availability of scheme data. Master trusts’ better quality data is driven by factors including the rollout of Auto-Enrolment in 2014, and the use of newer systems and data maintenance protocols, such as GDPR, which greatly benefit consumers and significantly improve the likelihood of finding a pension.
Analysis shows the success rate for major Auto-Enrolment master trusts, NEST, B&CE The People’s Pension, NOW Pensions and Smart Pension, is fairly high. 79% of these pensions were identified on the first try, 94% were identified either fully or partially, and only 6% could not be identified at all.
Of the older providers of contract-based schemes, such as those listed, only 52% of pensions were identified on the first try, 64% were either fully or partially identified, and 36% could not be identified at all.
Clare Reilly, Head of Corporate Development at PensionBee, said: “By the time it launches, savers will have waited more than 20 years for a dashboard so it needs to be fit for purpose from day one.
“This data should be a huge wake up call to the pensions industry. Those with legacy books of business, spread across systems and geographical locations around the country need to finally get their houses in order. The reputation and future of pensions depend on it.
“Whilst they do this only a staged approach can avoid what would otherwise be certain delay. If we want to launch with the best quality data, it’s clear master trusts lead the way.”
Notes to editors
The research and analysis conducted by PensionBee is independent and does not reflect the views of the Pensions Dashboards IDG Steering Group.
The Pensions Dashboard is one of the most highly anticipated and long overdue projects of recent times. First proposed by Tony Blair’s government in 2002, the dashboard project has since been passed to a series of pensions ministers.
In 2020, having long been overtaken by Open Banking and various other Open Data initiatives, DWP finally proposed the legislation needed to move the project forward by forcing all providers to share customer data.
But only now does the hard work really begin, as we enter the implementation phase. It is widely accepted that the ‘big bang’ method of fully populating all of the dashboard data on day one is not feasible. This is because of the variance in scheme data from provider to provider, in both quality and availability.
Data quality relies on a number of things, but most importantly it relies on being correct in the first place. This often isn’t the case due to the involvement of employers or unhelpful workarounds like dummy National Insurance numbers. Most savers have moved house at some point or changed their name after marriage or divorce and many forget to update their old providers when this happens. Additionally, some older schemes from pre-2001 may still not have fully digitised records. In summary, there are varying amounts of work for providers to get their data houses in order for launch. For some legacy providers with old books of business and old systems, it will take years and could cost millions.
The way around this is staging. By asking the providers with the best quality data to go first, consumers will have the best chance of correct matches and will be more inclined to log back in later. The providers who need longer to clean or correct their records will have slightly longer and will be phased in later. Eventually, the plan is to use a form of Gov.uk digital ID to reconnect customers with their pots (the current Gov.uk digital ID is known to have a poor adoption rate).