Around the world there has been a shift from defined benefit pension provision to defined contribution pension provision. The overall outcomes experienced by individual members of defined contribution arrangements are impacted by the design of such funds, how they are run in practice, the extent to which engagement programmes work, the extent to which default arrangements are utilised and the choices made by individual members. Over the years regulators and practitioners have been working on ways to improve the outcomes from such arrangements. Yet, in practice many arrangements still fall short to provide individual members with sufficient income in retirement. Building on experience from the South African pensions industry over a 30-year period the paper sets out a dynamic evidence-based framework on how data analytics can be used in practice as an ongoing monitoring and benchmarking tool to assist stakeholders who manage these arrangements to focus efforts in areas that improve outcomes. The key areas that need to be monitored in this framework, the types of data required, practical examples of the types of analytics that can be used by various stakeholders and visualised is set out. The approach provides a practitioners guide on how evidence-based analytics, including the use of predictive analytics, can help to improve the focus areas of key stakeholders as well as informing better engagement and solutions which ultimately improve individual member outcomes. Although the role of the actuary in respect of traditional pensions work has diminished with the shift from defined benefit to defined contribution provision, the framework presented demonstrates the significant role that actuaries can play in the ongoing management of defined contribution funds, applying actuarial and data analytics techniques to monitor the overall funding levels of individual members and ensuring practical recommendations and ongoing refinements can be made to improve their positions.

Find the Q&A here: Q&A on 'Pensions - Inflation and Data Analytics'