Size of Investment and Wealth Management Market

Autonomous Research has estimated the size of the US wealth management industry to be $376 billion in revenue in 2016. This figure is derived from investable assets of $37 trillion, which are defined as household net worth less illiquid assets such as residence and private company shares. The resulting industry pricing is slightly below 1% in fees across the ecosystem. Investable assets are derived based on the distribution of households in the United States, of which there were 124 million.

The overall market is separated into the following segments: (1) retail households with <$100k, (2) emerging affluent households with $100k-250k, (3) mass affluent households with $250k-1mm, (4) high-net worth households with $1-10mm, and (5) ultra high-net worth households with $10mm or more. Different firms use slightly different terminology and cut-offs for these populations. Our methodology reflects how most industry participants structure their service offerings and channels to target the quantified segments. The first chart shows households, investable assets and revenue pools by household segment.

On the second chart, we looked at the asset management side of the equation. Asset management is the manufacturing part of the investment management industry. Within fund management in particular, we find an 8.3% CAGR between 2008 and 2015, which is the period defined by the recovery from the financial crisis. For the same period, exchange traded funds grew at a 21.7% CAGR. The story that passive index investing and ETF investing have grown faster than the rest of the industry is shown here quantitatively. Whereas mutual fund growth is beginning to stall, ETF growth continues to expand.


Analysis of Venture Investment Activity for Digital Wealth Start-ups

Autonomous Research has analysed Venture Investment Activity within the digital wealth sector starting from 2008.  The findings show a surge in venture funding with investments reaching $615 million in 2014 compared to $194 million in 2013. The vast majority of capital was raised in North America, giving rise to digital wealth management start-ups such as Wealthfront and Personal Capital. In 2015, venture funding doubled to $1.3billion resulting from increased investment in Asia and start-ups such as Chunhua Wealth and entered the scene. With considerably smaller venture activity in Europe (and other regions) and investment reductions in Asia in 2016, North America is accounting for the majority of support for digital wealth entrepreneurs.

The second chart analyses the number of companies with seeding rounds targeting digital wealth start-ups across the same time period. We find a surge in companies providing venture funding across all regions from 2014: 56 companies in 2013 to 115 in 2016. Breaking down the companies by region re-affirms that North America offers the majority of venture funding in the wealth tech sector and support of digital wealth start-ups.

Short-Term and Long-Term Projection of Digital Assets Under Management up to 2030

Autonomous Research has estimated the growth of Digital Assets under Management in the short-term and long-term respectively. The short-term base case projection estimates $1.5 trillion in digital AUM by 2020. This figure is driven by our expectation of an increased adoption of Roboadvisors as a result of fiduciary requirements shrinking transactional businesses. In the case of a delayed adoption, our conservative projection estimates $0.5 trillion in digital AUM by 2020.

In the longer term, our base case projection reaches $4 trillion in digital AUM by 2030. However, with growth and ETF-like adoption, where Roboadvisors use passive ETFS to shrink industry fees, we estimate $8 trillion in AUM.  Finally, our Bull case occurs with digital wealth growing into HNW with early adoption across orphan accounts and the high-end mass affluent. This would lead to $17 trillion in digital AUM by 2030.

Fund Pricing Trends and ETF Selection by Roboadvisors

The first graph details how fund prices for equity and bond funds have fluctuated between the years of 2008 and 2015. It can be noted that the fund prices have been falling incrementally each year, but the notion that this is solely due to Roboadvisors is untrue as it can be seen that this trend was occurring before they had hit the market.

From the second graph it can be seen that the most popular ETF providers have the lowest transaction funds, with typically no transaction cost for custodian platforms. These are the ETFs most frequently adopted by Roboadvisors, which can largely be put down to the fact that management fees are a key contributing factor to the total cost of ETF ownership. Index ETFs will become increasingly popular as digitalisation encourages greater distribution and as ease of implementation becomes more of a necessity.

Impact of Roboadvisors on Overall Pricing Structures and Infrastructure Stack Pricing

Autonomous Research has analysed and compared the change in pricing structure between a traditional advisor, at 150 bps, a hybrid advisor, at 45 bps, and a B2C Roboadvisor at 25 bps.  The costs have been calculated using three pricing factors: (1) back and middle office, (2) asset management and (3) distribution. With the addition of a Roboadvisor, including the case of a hybrid advisor, it is evident that back and middle office functions are significantly reduced in cost. A decline  from 50 bps for a traditional to 10 bps for a hybrid and 5 bps for a B2C Roboadvisor. Distribution and asset management were still heavily impacted, each falling from 50 bps to 10 bps when changing from a traditional advisor to a B2C roboadvisor.

The second graph illustrates the difference in infrastructure stack pricing between a traditional advisor stack and a B2B private label stack. Within the traditional advisor stack in particular, we find the cost to be 50 bps but this figure is halved when compared with B2B private label stack. This is primarily due to custody costs being reduced to zero from 15, as it becomes monetized through asset management and does not require transaction fees for ETFs. Whilst most costs fall, there is a notable rise in client portal pricing that can be explained by Roboadvisors requiring more accessible platform for clients due to the lack of human interaction available.

Impact of Roboadvisors and Blockchain on Revenue Pools by Industry

Autonomous Research estimates that the Blockchain and Roboadvice technologies will impact over $900 billion in revenue, reducing it by approximately $250 billion. The revenue pool from 2016 is derived from revenues in: (1) business cross border payments, (2) investment management, (4) remittance payments, (5) capital markets and (6) title insurance. It is estimated that the impact of Fintech will consist of reductions of $44 billion from Roboadvice and $204 billion from Blockchain in the form of digital ledgers.  All areas of the revenue pool will be reduced as a result of these technologies, with the exception of capital markets as their revenues rise from $212 to $234 billion.

On the second chart, we looked at the specific impact each technology will have on the respective industry. It shows that Roboadvice will solely affect inventory management as it reduces the industries revenues by $ 44 billion. Alternatively, distributed ledgers will lead to reductions in B2B Cross Border, remittance payments and title insurance. The reasoning for these reductions can be associated with the concept that the digitization of finance is typically a revenue-contracting development. Despite this, it can be noted that capital markets received an increase in revenue from Distributed Ledgers due to the fact that in secularly shrinking markets we equate cost-savings with expansion.