Friday, 28 April 2017
Last updated 5 hours ago
Mar 30 2017 | 3:38pm ET
Editor’s note: Advances in technology and increasing operational complexity in search of higher returns has raised questions about how much the adoption of complex operating models increases risk, and as explored by John Phinney and George Evans of Norwalk, CT-based Convergence, whether it does so unnecessarily.
Analyzing The Digital Footprint: What Operational Data Can Tell You About Future Risk
By John Phinney & George Evans
When it comes to alternative asset management firms, complex operating models often add risk, and unnecessarily complex models add risk unnecessarily.
The issue of complexity has long existed in the shadows, with few tools to quantify either the overall level of risk or the comparative risk between and among asset managers pursuing similar strategies. The growing digital footprint of the alternative asset management industry has changed all that; there is now a new product in the marketplace to analyze and rate the complexity of thousands of funds. Many factors contribute to this analyses including internal valuation ; self-administration; and regulatory history, to name three among the dozens of possibilities. Capturing this information provides a window into an Advisor’s operational risk, a useful tool to have whether you’re an investor, an asset allocator, a plan sponsor, or a service provider.
An examination of the data for the period January 31, 2014 through December 31, 2016 confirms this. During that period, we reviewed alternative asset managers across multiple investment categories, including hedge funds, private equity, venture capital, and real estate, looking for those that had experienced some kind of regulatory violation as a proxy for potential future issues.
We found that of the fund types followed, hedge fund managers incurred the greatest number of regulatory actions of managers advising alternative funds, with reporting regulatory actions with 205, compared to 54 private equity, 11 venture capital, 10 real estate, and 75 “other”. A review of the Complexity profile of the managers who disclosed a regulatory action during that period indicated a correlation between high Complexity profiles (as we define them through an analysis of 40 operational risk factors) and regulatory actions. It was rare for a manager with a low Complexity profile to disclose a regulatory action. In hedge funds, for example, 62 percent of those reporting a regulatory action had a “high” Complexity profile and 33 percent had a “medium” Complexity profile.
Furthermore, we found that those managers who increase the level of complexity in their business data at a faster rate than the overall market ran a greater risk of incurring regulatory violations than those who operated with less Complexity.
There are tens of thousands of funds and thousands of managers, each with its own idiosyncratic way of doing business. A single manager may have dozens of funds, but even the most active allocator is unlikely to see inside more than a few dozen or so of those. Possibly as a result of the inherent difficulty of measuring operational due diligence, it’s often given low priority.
A survey we conducted found that among allocators, 83 percent reported having only 0-3 full-time employees dedicated to operational due diligence. At the same time, 57 percent said they had allocations to 50 or more managers, and 37 percent said they had allocations to 100 managers or more. Other findings include:
While some information can be gleaned from the experience of a single, large allocator – and some comparisons made – the observations are going to be largely anecdotal and of limited utility. For example, how do you know when a service provider has become unduly dependent on a single fund (and potentially vulnerable to undue influence)? How unusual is it for a fund in a specific investment category to use internal valuation for its portfolio? How does one fund’s auditing policy compare to other funds with similar assets and strategies? How do you benchmark your fund against the industry?
Not having these kinds of operational insights can present a potential risk from both an investment and a reputational point of view. Conversely, mapping change and growing complexity can help flag future issues before they erupt. In our experience, as many as 7% of asset managers may be under major operating model stress at any given point. When you consider there are about 58,000 alternative funds, this represents a sizable risk.
Putting Complexity in Context
Just knowing that a fund is complex is useful but not sufficient. In analyzing operational risk, context is important – understanding whether or not the level of complexity aligns with the size and scope of the strategy pursued by the fund. It stands to reason that larger, multi-jurisdictional funds with sophisticated strategies will be more complex operationally. If they were not, that lack of complexity might provoke further questions. Of greater concern is the fact that recent performance trends in the alternative asset class have led some managers to take on additional complexity in hopes of improving returns. Again, this does not automatically suggest a problem, but it does bear watching as our data suggests.
It’s not just allocators who can benefit from monitoring operational change. Asset managers can use operational insights to benchmark their firms against competitors and the industry as a whole. As investors continue to pay close attention to fund infrastructure, understanding what a peer group is doing can provide a competitive edge when looking to attract new
In the search for alpha, alternative asset managers have always guarded their investment strategies closely. Improved operational due diligence will not impact that. But by establishing benchmarks and tracking change, it can provide valuable insight into the risks and rewards of this asset class.
John Phinney and George Evans are co-founders of Convergence, which identifies, tracks and reports changes across the alternative asset management industry on a daily basis.