For effective pension administration, the accuracy of Personal Identifiable Information (PII) and data in general is paramount. In this article, Heywood Propositions Manager, Phil Needham, highlights why maintaining precise and up-to-date PII for pension schemes is so important, and explains the challenges and costs associated with inaccurate data, and how specialised software solutions can effectively address these issues.
This article also explores why pension administrators must prioritise PII accuracy, the potential risks of neglecting data quality, and the significant cost savings and efficiency gains achieved through effective PII data management.
The pensions administration industry, particularly Defined Benefit (DB) schemes, is facing unprecedented challenges. Administrators are grappling with increased workloads, constant firefighting, a shrinking skilled workforce and limited operational funds. And let’s not forget about McCloud, GMP equalisation and pensions dashboards either…
While administration is the lifeblood of all schemes, we know that it can often be undervalued and underfunded. In this challenging environment, the accuracy of Personal Identifiable Information (PII) becomes not just important, but critical for operational efficiency and cost-effectiveness.
Accurate data is the foundation for correct benefit calculations. Even minor errors in dates of birth, employment history, or salary/contribution records can lead to significant miscalculations. Schemes must ensure they can effectively validate data to ensure that benefit calculations are based on the most current and accurate information, reducing the risk of costly overpayments or underpayments.
Correct contact details are essential for maintaining efficient operations and reducing unnecessary costs. Inaccurate addresses, email addresses, or phone numbers result in wasted resources on failed communications. Not only that but being unable to reach your members effectively leads to poor outcomes.
GDPR and other data protection regulations means maintaining accurate PII is not just good practice – it's a legal requirement. Administrators need to focus on maintaining accurate records, have a mechanism in place to promptly respond to data subject requests, and be able to easily demonstrate compliance to regulators, thus avoiding potential fines that could run into millions of pounds.
Accurate PII is a crucial line of defence against fraud and identity theft. By having up to date and accurate personal data on members would limit identity theft and other aspects of fraud, protecting both the pension fund and its members from financial losses and reputational damage.
Accurate data significantly reduces the time spent on data-related queries and corrections. We expect these to rise dramatically when dashboards go live too, if schemes have not embarked on a data cleansing project. In real-world implementations, we've seen a significant reduction in time spent on data-related tasks, allowing administrators to focus on more strategic activities and reducing the need for additional staff via the effective use of automated data management tools.
Inaccurate data leading to incorrect benefit calculations will likely result in overpayments or underpayments. These errors can be costly to rectify and may damage the fund's financial health.
Non-compliance with data protection regulations due to inaccurate PII can result in significant fines. In the UK, GDPR violations can lead to fines of up to £17.5 million or 4% of annual global turnover. Schemes can protect themselves and demonstrate compliance through robust audit trails.
Dealing with inaccurate data isn't just time-consuming - it's expensive. Returned mail, member complaints, and data correction efforts all come with a price tag. Our clients have reported that before implementing our solution, they spent significant amounts per member per year on these issues. Our automated data management tools have helped reduce these costs dramatically, resulting in significant savings, especially for larger schemes.
Costs aren’t just financial. Errors in PII management can lead to negative publicity, eroding trust in the pension scheme. While member engagement is important, so is reducing complaints and enquiries.
PII naturally becomes outdated over time as members change addresses, marital status, or other personal details. Factoring regular data verification into your routine data maintenance activities will help helps to combat data decay and maintain accuracy over time.
Pension schemes often need to consolidate data from various sources, which can lead to inconsistencies. Administration software, like Heywood’s Altair can provide robust data integration capabilities, ensuring a single, accurate view of each member's information and eliminating discrepancies that can lead to errors and inefficiencies.
While maintaining accurate PII is crucial, it's equally important to keep this sensitive information secure. The pensions industry is not immune to data breaches, which as well as putting members at risk, can bring severe reputational damage and rectification costs. Employing state-of-the-art encryption and access control measures will help to protect member data.
Securing funding for admin improvements can be challenging, though the costs of not maintaining accurate data are arguably larger in the mind-to-long term. Presenting a strong business case to trustees with quantifiable ROI metrics can play a key role in the decision-making process, though. For example, I have had clients previously who were able to demonstrate a 70% ROI within the first year, primarily through reduced error correction costs and improved operational efficiency. This compelling financial case can help overcome trustee or pension committee hesitation and secures necessary funding for critical PII management improvements.
The accuracy of all data plays a crucial role in pension fund valuations, a process that directly affects the financial health and sustainability of pension schemes. Recent trends have shown a concerning decline in data quality across many funds, particularly during triennial valuations. This decline can be attributed to several factors:
The consequences of poor data quality during valuations are significant and can lead to:
When data quality is poor, actuaries must spend extra time validating and correcting data. This additional work can result in significant costs to the fund. For instance, some funds have reported additional actuarial fees approaching £20,000 for data validation and correction - and this figure could rise considerably to over £100k if its extended to calculating and verifying benefit amounts.
Poor data quality often leads actuaries to make prudent adjustments in their calculations. These adjustments can result in higher than necessary contribution rates for employers. The impact can be substantial, potentially increasing employer contribution rates by 1-2% of pay.
Correcting historical data problems is a time-consuming and expensive process. These additional administrative costs further strain already limited resources.
To illustrate the potential financial impact, let's consider a real-world example from a Fund’s annual report:
|
Employer |
Actual Normal Contributions (2013-14) |
1% Saving |
2% Saving |
|
Pension Fund (including schools) |
£17.848m |
£0.178m |
£0.347m |
This example demonstrates that improving data quality could potentially save this borough between £178,000 and £347,000 annually in contribution rates alone.
Furthermore, the introduction of new governance arrangements for the Local Government Pension Scheme, as mandated by the Public Service Pensions Act 2013, places even greater importance on data quality. These new arrangements, implemented from April 2015, subject data quality to increased scrutiny.
By ensuring high-quality data, pension funds can avoid unnecessary costs, optimise contribution rates, and meet increasingly stringent regulatory requirements. The investment in robust data solutions not only pays for itself through direct cost savings but also contributes to the long-term financial health and sustainability of the pension scheme.
In conclusion, the detrimental effects of poor data quality within UK pension funds are far-reaching. From inaccurate benefit calculations to increased fraud risks, these issues not only erode member trust but also impose significant financial burdens on funds. To mitigate these challenges, it is imperative for UK pension schemes to invest in robust data management strategies that ensure data accuracy, completeness, and accessibility. By prioritising data quality, funds can enhance operational efficiency, improve member satisfaction, and safeguard their long-term financial stability.