The Australian funds management industry is seeing a major shift from collective investment products such as unit trusts to more individually oriented separately managed accounts (SMAs).
New financial advice provided by financial planners now directs one in every two dollars of client money into the burgeoning $200 billion managed accounts sector. Responding to the lack of standards across SMAs for naming identical portfolios, calculating and presenting fees, classifying and reporting asset allocations, and tracking the roles of service providers, this collaboration will leverage new AI technologies that have powerful reasoning capabilities over large amounts of unstructured data. The outcomes are AI-enabled tools that provide rich user interfaces with the ability to continually integrate newly developed data standards and facilitate consistent SMA information provision to retail clients and institutional investors such as superannuation funds.
Project aims:
Despite its growing popularity, the SMA market is still struggling with identical portfolios having different names across platforms, fee structures that are impossible to compare, asset allocations that are reported using completely different methodologies, and inconsistent attribution of fiduciary roles between consultants/investment managers and platform operators. These problems pose major risks to financial advisers who are not able to meaningfully compare SMA products when selecting investments and tracking performance on behalf of investors. Led by the major players in the financial advice sector, SMA providers have adopted an industry-initiated set of data standards, the Separately Managed Account Standards (SMARS). The proposed PhD project:
- interrogates gaps in the nascent standards,
- develops protocols and AI-driven tools for their maintenance, and
- performs a series of empirical studies utilising the newly standardised SMA data to provide evidence-based validation of investment outcomes, including risk-adjusted and post-fee performance rankings and performance attribution.
Research team:
Jerry Parwada (Lead – ºÚÁÏÍø´óÊÂ¼Ç Business School); Fethi Rabhi (Co-Lead - ºÚÁÏÍø´óÊÂ¼Ç CSE), TBA (PhD student)
Industry partners:
Adviser Ratings (Pty) Limited