In an era marked by evolving demographics, and ever-shifting regulatory frameworks, the world of pension management faces unprecedented challenges. For both organizations and individuals, securing financial stability during retirement has become an increasingly complex and multifaceted undertaking.

This is particularly true for schemes tasked with managing pension plans, who must navigate the intricate labyrinth of pension de-risking strategies to safeguard their members’ financial futures.

Traditional defined benefit pension plans, once seen as the gold standard for retirement, now face significant challenges in an ever-changing economic and regulatory environment. It is within this landscape of uncertainty and transformation that pension buy-ins and buyouts have emerged as increasingly popular strategies for securing those financial futures of scheme members.

The concept of pension buy-ins and buyouts is rooted in the imperative of reducing pension scheme risks and liabilities, while simultaneously enhancing the financial stability and predictability of retirement benefits. These strategies involve transferring the responsibility of paying out pension benefits from the sponsoring organization to insurance companies, thereby offloading the risks associated with investment performance, longevity, and market fluctuations.

Who are MM?

MM. was established in 2006 as one of the original adopters of the UK Government’s DDRI licence, providing mortality screening solutions to pension funds. We have grown and developed as a data services organisation providing products like MM. Spouse, MM. Beneficiary & MM. Residence which are business critical to our clients responsible for ongoing data management and data preparation for end-game or pension dashboards.

MM. has built an experienced professional services team who help clients resolve issues around loss of contact with members. This team also help our clients manage data quality problems found during the Pension Dashboard roll-out or those going through a risk transfer process.

MM. are dedicated to Information Security and are ISO 27001 certified.

What is the purpose of this whitepaper?

This white paper details the average member-data quality standards across scheme databases analysed over the past 6 months. MM. are linking scheme member data to sources of truth to highlight the quality of the data provided and potential improvements that can be achieved.

The purpose of this report is to highlight the typical data quality problems faced when preparing for endgame and the impact this may have on both valuations and write-out’s during a buy-in/buyout.

A background of Bulk Annuities sector

To date there have been 103 transactions in 2023 which total over £23bn of risk transfer between a scheme and an insurer. The calculation of future liabilities and the accuracy of longevity models for the member and their dependents are vital when valuing the scheme.

A typical defined benefit scheme often relies heavily on the data provided by the member at the point of joining the scheme. As time elapses data degrades at an exponential rate and the scheme becomes unaware of the relationship status and location of its members. This has a major impact on the longevity predictions and liability calculations of the scheme and its members.

Further to the impact on fund value, the degradation of data also has a major impact on address quality and therefor member communication. As a scheme is legally required to mail out certain documents on a yearly basis as well as needing to write-out to members during a Buy-in or Buy Out to inform of the changes, the quality and currency of the members’ address is critical.

What is MM. Spouse Append?

MM. Spouse identifies whether a member is still alive, their marital status and if the current address is up-to date. The service categorises members’ relationship status into the below categories and appends the given spouse’s personal information.

If a member and their beneficiaries are entitled to future payments this will have a significant impact on calculating future liabilities. The accuracy of this calculation is of paramount importance to ensure value for money is being achieved for both parties.

The socio-demographic indicators of a member such as their age, where they live, their profession, whether they are married and the number of persons living in the house has a material impact on longevity calculations for both the member and their spouse. MM. Spouse will append these details to a member record in a format easily interpreted.

What is the average data quality and completeness of deferred members?

MM. Have collated results from client data over the past 6 months to give an overview of the scale of data quality problems found within a typical scheme member database.

MM. Spouse categorises a member’s relationship status into one of 7 categories, as detailed below.

Append StatusDefinitions%
Living in Long-Term RelationshipMember matched to a person for a continued period at the
same address
11%
Living with
Family
Member has not been matched
as married but evidence of living
at the address with other family members
7%
MarriedMember is married and a spouse
has been identified
36%
Shared LivingMember is found to be residing
at the address with non-family members
5%
SingleMember found but not matched
to anyone at the address
6%
UnknownMember was not found at the
given address at any point in time
16%
WidowedMember matched to a potential spouse who is deceased20%

Address Quality

Of the member records that form this sample, only 59.33% of the records were verified according to PAF without any corrections.

39.95% of the address records required some level of correction ranging from spelling errors to incomplete or incorrect data.

Definition% of Total
Address verified59.33%
Address verified but some corrections required37.64%
Address verified with some correction, looking
wider that just the specified postcode
1.49%
Address verified to Street Level, the property was not on PAF, but a unique match to the street identified on a single postcode0.53%
International Address0.50%
Address verified from a postcode which was substituted due to a Royal Mail
recoding and now matches the PAF
0.30%
No Match Found – Unable to match the record0.21%
Ambiguous Postcode Match – Matched record to Street Level but cannot determine Postcode. Multiple possibilities returned.0.01%

How many members are ‘Living as Stated’?

Most DB member data was collected a long time ago meaning many members will have moved home and not informed the scheme. A change in address will impact the efficiency of write out communication, impact the longevity calculations if the member has changed socio-demographically and increase operational cost to communicate with the member.

Category%Definition
Gone Away21%Evidence to suggest the member is no longer at the given address.
Member Deceased6%Member has been matched to the DDRI.
Potential Separation16%Of those members considered to be either ‘Married’ or ‘Living in Long Term’ Relationship’
evidence to suggest that they are now separated.

Implementation and Best Practices

As part of a risk transfer transaction, it is critical that both the scheme and insurer conduct a comprehensive data-cleansing exercise to ensure both parties are working with the most current and up to date data available.

Partied involved in a risk transfer will conduct a data cleansing exercise leading up to a transaction, which can be offered as a managed service.

Administrators or ISP’s responsible for ongoing data management or multiple bulk annuity transactions are required to implement ongoing processes to reduce risk and ensure high data quality standards.

A scheme should regularly clean member data to ensure efficient communication and compliance with regulations. When de-risking upto date member data is critical to both the scheme and insurer when calculating accurate liability calculations and valuations.

Does your organisation want to avoid sending client data to third parties?

Recent research shows that cybercrime is increasing with over 2,893 incidents reported by the ICO in a 3-month period during 2023

The most effective way to reduce the risk of member data being stolen by bad actors is to contain it within the scheme, insurer, or administrator’s environment.

As a result, MM. have designed our solutions to be delivered on premise giving full control and peace of mind to our clients. This solution negates the need to send sensitive client information to a third party while ensuring member data is up-to date and complete in line with the standards required to achieve accurate scheme valuation.