The pensions industry has to deal with voluminous and incremental datasets. This requires the application of complex data analytic methods on data ranging from individual data of the employed as well as retirees to portfolio management and other types of data that need to be federated from various sources.
This article provides a survey of the literature and reviews the current state and future opportunities for big data in the pensions domain. It explores the various types of big data generated in the pensions industry and corresponding data analytic methods. It thereby derives insights on the applicability of the available big data tools and the issues pertaining to big data in pensions. The article discusses the benefits and challenges of big data in the pensions industry, examine various big data techniques and tools used in the pensions industry and their impact on performance and security and opportunities for further applicability of big data in pensions.
As such, we identified 11 types of pension data that can be classified as big data and six areas in the pensions industry where big data analysis are applicable to derive insight from data. A summary of techniques and tools to realize big data analysis have been discussed together with broad categories of challenges and issues pertaining to adoption and deployment of big data systems in the pensions industry.
This article can serve as a starting point for practitioners and researchers to gain understanding on the applicability of big data in pensions.