Data quality
Secure data quality within the pension industry.
Data quality framework
High data quality is essential for pension funds to ensure sound and controlled operations. The introduction of the Future Pensions Act (WTP) further emphasises this importance. Pension funds must meet certain data quality standards before the new pension system comes into force. The Pension Federation’s Data Quality Framework and DNB’s Good Practice Data Quality offer pension funds guidance in this challenge.
The good news is pension funds do not have to start from scratch. Instead, we look at how to apply the framework to activities previously undertaken. Projective Group offers a helping hand in this process.
What to expect
The Decree on the Future of Pensions requires pension funds to demonstrate that data quality is guaranteed before the new pension system can take effect. This is a requirement for making a balanced entry decision and for calculating individual pension assets correctly.
The challenge for pension funds lies mainly in legacy systems, the period, and workarounds. The Data Quality – WTP Framework helps with this. The six stages from the Framework provides a consistent and measurable way to prove and guarantee data quality. Now is the time to complete these steps. The activities carried out earlier, should be included in this. This means that earlier work is not lost. Indeed, this insight is necessary to go through the six stages and make corrections and repair actions.
The deadlines for the activities, including improving data quality, are clear. Before the new pension system takes effect, all activities must be completed.
What we do
Projective Group supports pension funds and pension administration organisations in the execution, coordination, and implementation of the Data Quality Framework. With more than 25 years of experience guiding funds, pension managers, asset managers and pension insurers, we ensure a structured implementation of the Framework. Our approach implements the six phases of the Framework.
Baseline measurement
Providing insight into data quality activities carried out. This forms the basis for going through the Framework.
Phase 1 Policy
We guide pension funds in drawing up the data quality policy and defining the Critical Data Elements (CDEs).
Phase 2 Risk assessment
We identify relevant risk factors, including the current data quality management framework. We identify specific participant risks and provide guidance on defining the Maximum Permissible Deviation (MPD).
Phase 3 Data analysis
We analyse data to assess plausibility and accuracy. To do so, we perform data profiling to identify outliers and errors, and we conduct partial observations on CDEs and risk groups.
Phase 4 Reporting
We prepare detailed reports for the board on work carried out, outcomes and conclusions. We also help review these findings and prepare an action plan to bring data quality to the required level.
Phase 5 Accountant
We work with the accountant to carry out the agreed specific work on the basis of which the board can form an opinion on data quality.
Phase 6 Decision
Based on the work carried out, the board makes a decision on data quality. The applied MPD of the individual entitlement is considered and documented in this.
We follow the regulator’s guidelines and consider the proportionality of the pension fund when going through the Framework. To this end, we work closely with the key function holders and the auditor who will perform the Agreed Upon Procedures (AUP) and ensure that the board is in charge when it comes to data.
Projective Group coordinates The Framework and has the tools and expertise to conduct data analysis. We can take the entire implementation of The Framework off your hands.
