Sameer emigrated from India to the US where he acquired multiple degrees in engineering, management, public administration, and public policy and graduated from MIT and Harvard. He is a recipient of the Alfred Sloan Fellowship and subsequently was also a Fellow of Public Policy and Management at the Harvard Kennedy School of Government for a year. Prior to starting ActiveAllocator, Sameer was a Managing Director on Wall Street and worked for firms such as AR Capital, UBS Alternative Investments, Citi Alternative Investments and others.
In the course of his work he came to realize that main-stream retail investors too stood to benefit from the same analytics driven, fact-based approach to decision making that institutional consultants and large wealth management firms brought to their most sophisticated clients. He felt that the correct business model was to blend the human with the digital. He dreamt of creating a digital platform which fosters advice that is collaboratively arrived at between clients and financial advisors. For financial advisors and RIAs such a platform would drive personalization, facilitate mass customization, promote greater customer intimacy as well as enhance productivity by serving as a strategic business enabler. It would further help them improve fiduciary standards, grow AUA by attracting and retaining clients, include alternative investments purposively in portfolios, and promote differentiation through making personalized financial advice their digital priority. In addition, it would also empower self-directed individuals and help those seeking advice from a financial advisor by providing “trust but verify” tools to assess investment advice. This dream led to the creation of ActiveAllocator.
During the interview, Sameer shared his thoughts on the latest trends and challenges in the wealth management industry, why he believes that current financial advice is largely inefficient, and his attitudes to active and passive investment.
Industry trends and issues
The wealth-management industry is changing rapidly with more and more financial companies offering digital advice. Talking about trends in the industry, Sameer thinks that this is because traditional financial firms can’t provide quality advice to everyone profitably, few customers want to pay for it, and many investors just don’t trust their financial advisors. Meanwhile, traditional forms of asset allocation advice are costly, impersonal and inefficient. To increase efficiency and serve a broader audience, advisors put investors in “model portfolios,” which commoditize and marginalize advisor service and expertise. Model portfolios also fail to adequately account for personal investment views, preferences and limitations. Worse still, clients rarely know how inefficient their allocations really are and have no objective means to measure and value advisor performance.
Sameer noted the potential for WealthTech disruption from newer forms of digital advice and fulfillment platforms:
“Financial advice, retirement and wealth management industries have been spared major change. They have gotten away for their clients have been older and hands off, high regulatory barriers, and high capital requirements. However, the world is fast changing and the forces of digital disruption have now launched a frontal assault on wealth management.”
He pointed out that regulation-driven changes from rules intended to eliminate conflicts of interest in financial advice have been kicked down the road. Sameer highlighted the emergent role of technology-driven personalization across many industries and drew analogies to retail financial advice. Within the high net-worth and affluent segments, he stressed increased adoption of alternative investments. Sameer believes that the trend supporting financial advisor migration to independence from wirehouses and captive channels will gain further momentum, as will the propensity to buy vs. build in-house by mid-size financial firms. All of this, he noted, were catalyzed by major technology shifts, including cloud-based services, usage of low cost and open source software development tools as well as partnering across the digital ecosystem through APIs.
According to Sameer, technology disruption facilitates a “migration to independence,” where captive channel financial advisors break away from wirehouses—such as UBS, Goldman Sachs, JP Morgan, and Morgan Stanley—and become independent RIAs. Independent channels are gaining market share from captive ones and the number of financial advisors leaving large captive financial institutions to become independent continues to accelerate. By delivering superior asset allocation and portfolio construction practices, previously only available to the ultra-high-net-worth segment, at a fraction of the cost of lesser platforms, he hopes that ActiveAllocator serves as a valuable recruiting tool.
Technology-driven personalization is another trend permeating multiple sections of industry but has been slow on the uptake within retail financial advice:
“Everything is personalized. We buy our music that’s personalized, our travel is personalized, but this [personalization] is something that has eluded the financial services industry. People [financial advisors] put their clients in what they call model portfolios. Just how hard is it to put someone in a one size fits all, cookie-cutter model portfolio? Just go through the motions of assessing risk tolerance, ask them three, four, five canned questions in a KYC [know your client] and respond with a simple change in the portfolio mix of stocks and bonds. This is definitely not what I call personalization.”
Sameer further suggests that alternative investments- private equity, real estate, hedge funds, and managed futures – are increasingly become a part of affluent investor portfolios. However, advisors do not properly allocate to these properly, as evident in the usage of thumb rules and back of envelope calculations:
“ActiveAllocator is purpose built to account for the special issues that arise when it comes to allocating to complex products and alternative investments, for which Modern Portfolio Theory does not work. These include stale pricing which creates serial correlation in returns which understates true volatility. Then there is reporting bias from instant history, survivorship and selection bias which overstates index returns. What folks don’t realize is that volatility measured by the normal distribution is not a proxy for risk as historical returns exhibit negative skewness and kurtosis as well as downside risk. Moreover, illiquidity demands a premium, but is hard to calculate as it varies. Furthermore, managers exhibit style drift which is hard to catch given asymmetric information and we all know the difficulties in differentiating between expensive active skills versus cheap passive market exposure.”
Talking about technologies in financial advice, Sameer recognizes many mid-size firms prefer to buy services rather than build them. This happens because technology develops quickly and enables them to lower costs via cloud-based services, open source computing, and partnering across the entire ecosystem using APIs:
Costly and inefficient financial advice
Sameer intends to build the ActiveAllocator platform to satisfy advisors and investors’ expectations about the best advice. Today, he believes, good financial advice is hard to get and is very costly:
“We are driven by an authentic mission: to increase expected returns for 33 million investors by eliminating the 20%-30% loss built into the way the retail financial advice and investment management industry is currently structured. Our technology can remove the deadweight costs of $130 billion of strategic asset allocation inefficiency and drastically reduce the $260-$300 billion being paid in advisory fees, one individual portfolio at a time. ActiveAllocator helps individual investors, financial advisors, and asset managers analyze existing allocations, discover inefficiencies, and create optimized bespoke portfolios – in 10 minutes, 10 clicks and at 10 percent of the typical cost.”
The other problem that Sameer recognizes is that financial advice is impersonal and inefficient. Advisors do not bother to provide a custom portfolio, but offer the same model to multiple clients to reduce their own workload. Unfortunately, end investors do not understand this, and trust their financial advisors:
“ActiveAllocator, by contrast, allows for on-the-fly changes to investor-specific preferences. Things like specifying a desired portfolio risk target range, maximum illiquidity, limits on alternative investments, specifying a maximum turnover, stating expected target returns within a preferred investment horizon as well as imposing asset class exposure constraints at the single client level. In addition, we incorporate each client’s entire disclosed financial position, including accounts held away, to provide the data necessary for holistic portfolio analysis.”
Sameer insists that the financial advisor should not act as an active portfolio manager. As coauthor of a three year research initiative culminating in the Active Equity Management book, now used in many universities, he says:
“Alternative investment, active management, is a good servant but a bad master because people do not know how much to put into active versus passive.”
According to Sameer, they have solved the issue and the ActiveAllocator platform suggests the exact percentage of how much should be put into active and passive investments, to help investors gain better performance. In their algorithms, they do not use just mean variance optimization or historical volatility; Sameer thinks that such popular approaches have fundamental flaws and limitations:
“You should be concerned about future volatility, not historic and should extract it from options pricing data. Don’t look at long-term data and arrive at your numbers for market beta, your correlation matrix, because data is time-variant. It’s constantly changing.”
He said that most investors do not know how to distinguish between beta, which is a passive market measure, and alpha, which is a skills-based return measure. To solve these and other issues he created ActiveAllocator:
“Our general approach to active management is to construct multi-asset portfolios across managed futures, hedge funds, real estate, private equity and debt blended with traditional liquid investments such as stocks, bonds, ETFs and mutual funds. Unlike anyone else I know we calculate active risk adjusted returns and measure an active manager’s skill. We are the only firm that can identify and isolate characteristics of a manager’s skill (alpha). This helps us calculate average alpha of managers, correlation among alphas, the effect of changes in the number of managers and use Bayesian statistics to arrive at degrees of confidence in future performance within portfolios.”
Unlike other platforms, ActiveAllocator forecasts the probability distribution of uncertainty in return, volatility, correlations of a fund. This then helps facilitate fund manager selection to direct capital to only those who produce high skills-based returns and then optimally combine such managers into a portfolio to diversify active risk. The system computes the marginal impact of adding or removing a fund manager to an existing portfolio and compare manager performance in a like-for-like manner and help in ongoing evaluation.
Interviewed by Vasyl Soloshchuk, CEO and co-owner at INSART, FinTech & Java engineering company. Vasyl is also the author of WealthTech Club, which conducts research into Fortune and Startup Robo-advisor and Wealth Management companies in terms of the technology ecosystem.