With technology playing an ever increasing role in our lives, it is now becoming not just a question of the benefit that technology can bring but instead a question of how big a risk it is if an investor does not adopt technology into their organization. Amongst other things, technology empowers investors by: giving greater transparency on risk at the holding and portfolio levels, across multiple time horizons; allowing clarity on whether external managers are earning their fees and behaving in aligned ways; generating operating alpha – i.e., risk-free increases to returns through efficiency enhancements; enabling portfolio construction and manager selection that results in better ‘matches to mission’; freeing people up to grow and innovate in ways that bring more long-term value to the organization.
Off the shelf technology products however do not take into account the unique characteristics of investors, whether that be the resources on hand including operating and governance processes, expertise, risk appetite, innovation skills or the different strategies (active vs passive, hedging, alternatives etc.) of an investor. Furthermore, technology systems in institutional investor organizations are quite often work flow centric as opposed to integrated data centric systems. This creates data silos which can lead to data accuracy, completeness and consistency issues.
Despite the diversity of contexts, most institutional investors share some common functions: portfolio allocation; portfolio analysis; risk management; performance attribution; reporting; asset and liability modeling. There is however a lack of multi asset class support in off the shelf technology solutions for institutional investors which has led to asset class specific front to back solutions. Front office teams chose to service their own data and technology needs by building applications using Microsoft tools and other technologies. This has further led to a data silo’d environment. Enterprise data buses, data marts and warehouses have helped with data consolidation, but given the data architecture constraints and scalability of technology used, these systems failed to provide the functionality and time to market has been an issue.
Given the trend to increase the % of a portfolio managed in house as well as adoption of factor based portfolio construction techniques, there is a greater need for a data driven investment approach. This requires a data centric architecture as opposed to a workflow centric architecture. Vendor platforms are also realizing this and are transforming to a front to back integrated offering. They are evolving but as yet don’t support all functional needs.
There is thus a pressing need for a capability to quickly integrate data between as well as aggregate data across systems. Cloud native data technologies have lowered barriers to entry to create a flexible and infinitely scalable data platform. One which is the integration point and aggregation point for all data sets of value. To create such a platform, the majority of effort centers around creating a secure cloud based data platform. Most asset owners however do not have the talent or resources to achieve this in a cost effective manner in a meaningful timeframe.
Data driven investors take advantage of a new Process, organizational alignment, and technologies to facilitate relationships between everyone who handles data by closely connecting the people who: Collect and prepare the data; Analyze the data; Put the findings from analyses to good business use internally and externally. This is in contrast to traditional data management and operations IT teams who act as ‘order takers’, ‘behind the scenes’ and have zero to minimal executive visibility.
We at RCI, believe there are certain qualities that characterize a data-driven asset owner:
Our total fund projection software system, focuses on transitioning asset owner organizations that rely on the flat data structure of spreadsheets which are prone to duplication errors, and have limited analysis capability to a system that has relational data, a single source of truth and is more easily able to be sliced and diced. In contrast to silo’d single computers in different divisions, RCI’s system is integrated through cloud computing, API’s with real time capability, and is accurate and granular. It also provides more automation for modeling, enabling more time for analysis.
RCI is committed to helping asset owner investors along the journey to becoming data driven organizations, to help facilitate better decision-making and achieve long-term objectives for their beneficiaries.