Adoption challenges of robo advisory
The extent of transformation of robo advisory will depend on how the ecosystem evolves around the adoption of algorithm driven platforms, regulatory support, creating broader fund features and addressing technology led concerns.
- Algorithm driven platforms: An elementary robo advisor delivers digital advice by asking users to answer a few questions related to his financial goal, risk appetite and other basic financial details. Robo advisors use a human created algorithm or a mathematical formula that considers key elements viz. the historical long-term performance various asset classes like equities, bonds & commodities, information the user provides about investing goals, timeline, risk loss tolerance, investible corpus and underlying investment options primarily index funds and ETFs. Algorithms assign portfolios based on financial requirement and expected risk return profile of the individual client. An important aspect of the whole robo advisory is the continuous monitoring and regular rebalancing of portfolios. There are various ways in which a robo advisory works but primarily it gets classified into two categories viz. fully automated model and hybrid or assisted model wherein the latter has more human intervention/support.
- Funds features: Robo advisors were originally designed on the premise of passive, low cost investing. Some new online broker services go beyond just ETFs and offer actively managed funds. A few robo advisory services allow clients to pick between an all ETF portfolio or a hybrid that includes managed mutual funds and ETFs. In terms of ticket size, brokers require minimum investments of $5000 compared to their start-up counterparts who have even offered services with minimal investment criteria. The mass adoption of robo advisory, therefore, warrants its expansion across asset classes
- Fees: The fees charged by each broker for its robo advisory services is relatively competitive. Globally, the all-in fee ranges from 0.25 -0.4% of AUM, with a few charging no advisory fee but having certain expense ratio. There is also certain tiered structure offered that ranges from 15 to 35 basis points. This fee is relatively lower than the traditional fee which ranges at ~1-2% of the AUM
- Thin margins warrant higher scalability to sustain: The basic premise of a robo advisory is to offer investment advice in a cost-efficient manner to a larger section of investors. Therefore, given the thin margin nature of the business, the scalability is of prime importance for sustainability of such a business model. It is to be noted that concerns on thin margins would be addressed as the robo advisory model is adopted by mainstream financial services companies, thereby making it a large scale play
- Technology trust deficit and missing human interface: One of the major concerns of any fintech service has been the technology trust deficit. The need for regulatory supervision in robo advisory also emanates from its lack of ability to make human judgements in asset management algorithms. Therefore, with stringent regulatory requirements as seen in the US and Europe by SEC and European supervisory authorities, it is likely that the same would be addressed by everyone (including India) for wider adoption. Similarly, the absence of a human interface can be overcome by focusing more on a hybrid model, which brings in the best of both worlds i.e. traditional and robo advisory
Robo advisory in India – still at nascent stage
Robo advisory is at a nascent stage in India and has just started gaining traction in India with many startups and a few brokers launching the model. Most players who have started giving automated advice are currently following a basic model of asset allocation based on the risk return matrix. Currently, most robo advisories are being offered in mutual funds while an advisory on direct stocks or other asset classes is yet to witness a kickstart. In India, a commission/brokerage model is the prevalent model for robo advisory. There is still some time to move to a fee-based model.
Robo advisory to complement traditional wealth management
The rise of robo-advisory services has challenged the traditional financial services providers to recalibrate how technology can improve their current service offerings. With wider adoption of robo services, it can bring on board small scale investors and thereby boost the economy by enabling wealth planning to become mainstream. We believe the robo advisory will complement the financial advisory landscape, paving the way for enhancing the financial inclusion of small investors. The way forward in the investment advisory business model will be the hybrid model, which offers the best of both worlds where the advantages of technology are combined with human wisdom.
Shilpa Kumar, Co-Chairperson, FICCI Capital Markets Committee and Managing Director & CEO, ICICI Securities Limited writes piece for us.
