Stephen Martin

MM & PASA Guidelines and Data Standards

PASA have released their latest Data Accuracy Guidance about the importance of accurate data for pension schemes and provides guidance on how trustees can improve data accuracy. The guidance was created as a collaboration between various organisations including our own. Dr Tim Drye, MM’s Chief Data Officer.

The guidance lays out that accurate data is essential for pension schemes to navigate through an ever-changing landscape and meet new obligations. 

The Pensions Regulator (TPR) has increased its focus on good record keeping, making accurate data a requirement rather than a nice to have. Complete and accurate data is necessary for various aspects of scheme management, such as dashboards and member access to records. Inaccurate data can lead to increased costs, higher levels of queries, data breaches, and poor decision making. 

Trustees can improve data accuracy by conducting a data quality audit to identify issues and areas of weakness. They should cross-reference data fields, test for validation criteria, and analyse the consistency of data from different sources. Trustees should also consider digitizing paper files and microfiche and storing all data on a single electronic administration platform. The results of the data accuracy review should be summarized in a trustee report, which includes an overall assessment, results for individual data, categories of concern, impact on the scheme, recommendations, and prioritization of actions. 

Trustees should establish repeatable data validation tests, refine tests periodically, maintain a Data Management Plan (DMP), maintain an improvement log, and keep a clear audit trail of data updates and decisions made. Data quality management should be seen as a continuous process rather than a one-off exercise. 

1.        Increased queries and costs: Schemes with inadequate data accuracy will experience higher levels of queries from their administrators, leading to increased costs in resolving these queries. 

2.        Low levels of engagement: Inadequate data accuracy can result in low levels of member engagement, as members may not trust the information provided by the scheme. 

3.        Data breaches: Poor data accuracy increases the risk of data breaches, which can have serious consequences for both trustees and members. 

4.        Inaccurate reporting and decision making: Accurate data is essential for generating accurate reports and making informed decisions. Inadequate data accuracy can lead to incorrect reporting and poor decision making, which can have negative impacts on the scheme’s long-term strategies. 

5.        Delayed risk transfer exercises and wind-ups: Inaccurate data can slow down risk transfer exercises and wind-ups, leading to delays and potentially higher premiums. 

6.        Increased administration costs: Poor data accuracy requires more ad hoc data checking during member events, resulting in increased ongoing administration costs. 

7.        Poor service and increased complaints: Inaccurate data can lead to poor service delivery and more complaints from members about data errors. 

8.        Limited potential for self-service tools and digital engagement: Inaccurate data hinders the implementation of self-service tools and digital engagement options for members. 

9.        Incorrect pension payments: Poor data accuracy increases the risk of incorrect pension payments, which may require expensive future remediation. 

10.   Reputational damage: Inaccurate data can damage the reputation of trustees and employers, leading to a loss of trust from members and the wider public. 

11.   Impaired scheme valuation and funding strategies: Inaccurate data can negatively impact scheme valuation and funding strategies, making it difficult to accurately assess the financial health of the scheme.

12.   Higher ongoing PPF fees or transfer costs: Inadequate data accuracy can result in higher fees paid to the Pension Protection Fund (PPF) or increased costs for transferring data to other schemes. 

Multiple Authors (2024). PASA Data Working Group Produced in partnership with: PASA Experts for Data. Data Presence vs Accuracy. [online] Available at:

Lost in the Inbox: Missing member emails in Pension Scheme Data

In a report prepared for The Pension Regulator by OMB research to gain a greater understanding into pension scheme administration and the challenges faced by Administrators.
The data section of the survey focused on large administrators (100,000+ memberships) and threw up some interesting results.

Whilst the vast majority of these administrators were confident in the accuracy of the data they hold, there were significant issues around historical gaps and lack of email and phone numbers.

These gaps can have a significant impact on a scheme’s ability to contact their members and the figures from the survey are concerning.

All large administrators were asked if they were ‘Confident in accuracy of data for at least 75% of memberships’ for both active and deferred members.

Only 56% of schemes were confident in the accuracy of their active members email addresses, this figure dropping alarmingly to 11% for deferred members.

Mobile phone numbers represent another significant challenge to administrators with only 38% of them confident in the accuracy of >75% of their Active Members. Again the figure is, expectedly, far lower for deferred members at 13%.

These figures represent a fundamental challenge in an administrator’s ability to contact a scheme’s members outside of costly mailouts.

The report also highlights issues with regards to pension administrators’ ‘Dashboard Readiness’ ahead of the Pensions Dashboards Program’s rollout. A quarter surveyed expressing that ‘availability of data, accuracy of data and inability to fill historical data gaps’ being just some of challenges the success of the program will have. Accurate and complete member email addresses will be critical when matching members with multiple pots and reducing the number of partial matches.

MM, are a government-licensed data services company, supplying the pension & insurance industry. Our innovative solutions address this critical gap in member information with a new source of over 50m opt-in email addresses.

Our Email Append Service is designed to solve the very problem outlined in this report by OMB Research. This service seamlessly integrates email addresses into existing data sets ensuring administrators can comply with regulations and reduce operational costs.

OMB Research. (2022). Survey of pension scheme administrators 2020 to 2021 [Online]. Prepared for The Pension Regulator.

Mortality Rates and Deprivation (IMD) in England 

MM are a government approved DDRI licence holder and proprietary data owner, receiving all registered UK deaths on a weekly basis. The month of death, age at time of death and inferred gender can be aggregated by postcode or output area which are more granular than what are made available by the office of National Statistics (ONS). This means that MM can provide actuaries with more flexible, detailed and timely mortality statistics, with the ability to append different variables representing population experience and help improve longevity models

MM has delved into the intricate relationship between average age at death and the Index of Multiple Deprivation (IMD) in England. The IMD, a comprehensive measure of relative deprivation, assesses 39 indicators across seven distinct domains, providing a nuanced understanding of socio-economic conditions at the Lower-layer Super Output Area (LSOA) level.  

Our study seeks to unravel the impact of deprivation on life expectancy as a surrogate for experience data internally available to actuaries when building longevity models.   
Deprivation in England is gauged at the LSOA level, the second smallest geographical area in the UK (Output area being the smallest). Each LSOA, housing between 400 and 1,200 households and a resident population of 1,000 to 3,000 individuals, receives a score based on a combination of indicators. These scores are then ranked and divided into deciles, ranging from 1 (most deprived) to 10 (least deprived). 

Our research reveals a striking correlation between deprivation and life expectancy, underscoring the profound impact of socio-economic conditions on the longevity of individuals. The table below summarizes mortality rates for men, women, and overall populations across the ten deciles: 

This table demonstrates the overall deprivation decile, however MM can be segmented by other available deciles including Income, Employment, health, skills, housing environment and more. The same applies to other available datasets such as Urbanicity code, Council Tax, Health or Income data or third party datasets such as Experian Mosaic.

The data demonstrates that the overall age at death in the 1st decile (most deprived) is 74, meaning 7 years less than their counterparts in the top decile. The disparity is even more pronounced for men, with an 8-year difference (71-79) between the 1st and 10th deciles, compared to a 6-year range (77-83) for women. 

In conclusion, our research underscores the profound impact of deprivation on age at death, which shows the importance of experience data, assessed with appropriate estimates of the prevalence of this experience in the general population outside the schemes member data. 

The disparity in longevity based on the level of deprivation in the geographical area, is a stark reminder of the complex interplay between socio-economic factors and health outcomes. In future additions to our research, we will delve into the seven distinct domains used to calculate the IMD scores, providing a greater understanding of the factors contributing to these disparities.  

MM provides month of death, age and gender aggregated at a geographical level and is easy to implement into existing mortality models. When used alongside scheme experience data this will increase the accuracy and reliability of longevity models and pricing calculations. 

As is well understood longevity models require both infomation about deaths and also the exposed populations to properly estimate life expectancy. MM. also provide these alongside the deceased estimates.

Stay tuned as we unravel the intricate web of deprivation and its implications on health and well-being. 

The Pensions Regulator publishes their General Code of Practice

In a significant development for pension scheme governance, The Pensions Regulator (TPR) has recently unveiled its long-awaited 2024 General Code of Practice. Published on January 10th and due to come into force in March, this comprehensive code consolidates ten of the regulator’s existing codes, providing updates introducing new requirements to improve pension scheme governance.

One key aspect that demands attention is the Administration: Information Handling aspect, especially in terms of Record Keeping.

The new code places a heightened emphasis on the need for robust record-keeping practices within pension schemes. Effective record keeping is crucial for ensuring compliance with regulatory requirements, facilitating transparency, and supporting the overall governance of pension schemes.

This article explores how MM, a leading service provider in the financial and administrative sector, can assist pension schemes in meeting the stringent requirements outlined in the code.

1. Maintaining Robust Scheme Records and Data Monitoring:

Governing bodies are now required to have a comprehensive set of measures in place to maintain scheme records. This includes robust data monitoring and improvement processes. MM offers a suite of solutions designed to streamline these efforts and ensure compliance with TPR’s standards.

2. Demonstrating Processes for Accurate and Up-to-Date Records:

MM helps schemes demonstrate that they operate processes ensuring accurate and up-to-date records. Through innovative technologies and tailored solutions, MM ensures that pension schemes have the capabilities to run seamlessly and efficiently.

3. Error Identification and Rectification:

Prompt identification and rectification of errors in scheme records are crucial for compliance. MM facilitates efficient error resolution, ensuring that any discrepancies are identified and corrected as soon as possible.

4. Common Data for Administrators:

MM recognise the importance of common data for administrators and provides solutions, such as MM Spouse and Beneficiary, to ensure that beneficiaries are accurately accounted for. This feature is pivotal in maintaining accurate and comprehensive member information.

5. Collaboration with Administrators for Scheme-Specific Data:

Working collaboratively with administrators is a key aspect highlighted in the code. MM facilitates this collaboration by providing tools like MM Existence, which aids in identifying, recording, validating, and correcting scheme-specific data. This ensures that data accuracy is prioritized and maintained.

7. Complete and Accurate Record Maintenance:

MM’s solutions align with TPR’s requirements for maintaining complete and accurate records, encompassing both common and scheme-specific data. This not only meets regulatory standards but also provides a foundation for efficient scheme administration.

8. Processes for Monitoring and Reviewing Scheme Data:

MM supports governing bodies with processes for ongoing monitoring and periodic reviews of scheme data. This includes data improvement prioritization for members approaching the benefit-drawing stage, as well as scheduled tracing and existence exercises to validate member data.

9. Comprehensive Solutions from MM:

To address the requirements outlined in the code, MM offers a suite of solutions, including MM Spouse and Beneficiary, MM Existence, and MM Residence. These solutions collectively ensure accurate member data, validate information, and maintain correct contact details.

As pension schemes navigate the complexities of the new General Code of Practice, MM stands as a reliable partner in ensuring compliance with the Record Keeping and Data Monitoring standards set by The Pensions Regulator.

By leveraging MM’s innovative solutions, pension schemes can not only meet regulatory requirements but also enhance their overall efficiency in managing member data and scheme records.

Contact us to discover how MM can empower your pension scheme with cutting-edge solutions tailored to meet these evolving regulatory challenges.

MM Spouse: Marital Status Predictor & Member Spouse Tracing 

If the scheme is unaware of their member’s marital status and associated Spouse in, this can lead to the risk of unexpected and potentially unknown liabilities, particularly for DB schemes.  

MM Spouse is a proprietary solution built on a foundation of billions of historic records and data different data sources from other options in the market. This approach is resulting in consistent uplift in traced spouses compared to LexisNexis De-Risking Solutions, particularly when the member is gone-away from the address on file. 

In order to replicate current pricing models, MM have maintained similar categories to traditional market options. 

Living with Family 
Living in Long-Term Relationship 
Shared Living 

As well as proven uplift in matches spouses MM also offer additional data which is valuable to schemes and insurers as a standard with our marital status predictor. 

Gone-away indicator  Locate and update contact information for ‘gone away’ individuals are essential components of responsible scheme management. This is particularly important for a write-out campaign during a risk transfer. 
Separation Indicator Help protect the rights of all parties involved. Keeping track of divorce or legal separation ensures compliance and supports the individuals.  
Deceased flag Maintaining up-to-date records on the deceased status of plan members is essential for effective and responsible administration. MM are a DDRI license holder. 

Along with billions of historical records of UK residents, MM Spouse leverages actual marriage data, increasing confidence and improving results for our clients. 

Our Secure File Transfer (sFTP) product ensures that all files are securely transferred and returned to our clients within 24hours in accordance with MM’s accredited ISO 27001 information security management system.

During recent data tests, MM. Spouse was found to deliver, in comparison to other providers:

  • 8% uplift in matched spouses  
  • 10% reduction unmatched members
  • Over 40% increase in members matched as living in ‘Living in long-term relationship’

The risk of increased liabilities can be a major concern. That’s why our service is specifically designed to identify spouse and cohabitee information, which can be useful in identifying possible beneficiaries. Providing increased certainty over your liabilities. 

Contact MM. today to see how we can help your scheme unlock the undeclared marital status of your members.