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Proxy Advisory’s Specificity Problem

How Troop’s AI tooling supercharges proxy strategy.

For as long as anyone has been thinking about corporate governance, it’s been clear that investors should have some say in the process. It’s not some needless mantra; it’s the essential fundament of the proxy voting system as it exists today.


The process is supposed to go something like this: each year, when proxy season comes around and a company gears up for its annual general meeting, shareholders—everyone from the casual day traders to the high-net-worth zillionaires—thinks long and hard about what changes they’d like to see at the company in the new year. Those decisions are first and foremost about maximizing return, but they also inevitably depend on the person doing the deciding. They depend on what the shareholder thinks about how the company has been run in the past, but also on the rest of that shareholder’s portfolio, and the extent to which a shareholder wants their portfolio to reflect their values.


Only bespoke strategy can accommodate this sort of nuance. Shareholders understand that they can and should have a say in how the companies they’re invested in are run—but since most shareholders don’t have the time or resources to invest in the voting process, they turn to proxy advisory firms that help make those decisions for them. Shareholders, recognizing the importance of aligning votes with strategy, and acknowledging that it’s probably best to go with what these firms recommend, have overwhelmingly chosen this route: just two firms represent 97% of the market for these proxy advisory services, which means that almost everyone looking for voting advice is getting it from the same two places.

The preparatory work that goes on at these firms is ultimately a bit of a black box. For the researchers who work in this industry, the challenge lies in coming up with voting recommendations that align with their employer’s values and principles. But the values of these middlemen aren’t the same as the values of the investors they represent—nor do proxy advisory firms ever really have the whole picture when it comes to an investor’s strategy. Even getting in touch with these firms is something of a process; filling out an online form might not be enough to convince them to actually meet you in person.


It gets more slippery when you consider the extreme diversity of clients the traditional proxy advisory industry represents: when an advisor makes a judgment about which proposals to back, or which dissident board candidates to support, that judgment all too often becomes an industry-wide mandate.


The result is a kind of perfunctory one-size-fits-all advisory that’s become a central feature of corporate governance in the US and beyond. For plenty of strategists, private investors, and institutional asset managers, the work of voting one’s shares has less to do with creative strategy than with routine adherence to the proxy advisory industry’s determinations. All shareholders, from pensioners to oligarchs, are impacted by these outcomes; but if no two shareholders’ rationales are the same, then why is the entire industry being funneled into a proxy advisory process that elides specificity?


We believe that, in an ideal world, only investors and their stewards are ever positioned to make the right voting choices at the right time. That’s why we’re building tools that preserve specificity in the proxy advisory process. It starts with an artificial intelligence framework that’s trained on a case-by-case basis, accommodating and anticipating investors’ own values as it generates bespoke voting recommendations for any kind of publicly governed company. 


Consider the fast-growing EV sector, whose investors are as diverse as any other. Last year, at the annual general meeting for the electric car manufacturer Rivian, shareholders had the chance to vote on whether or not the company should adopt a comprehensive policy around the protection of human rights. As a nonunion shop, Rivian has faced allegations of labor issues for years, and has been investigated by the National Labor Relations Board over potential anti-union activities. The question of how to vote on this proposal comes down to the legal, reputational, and financial risks posed by not adopting such a policy—but there are plenty of other considerations, too. Would instituting this sort of policy be a waste of resources? Would it make operations less efficient, and therefore sap value from the company? And what about shareholders invested in adjacent businesses, like EV infrastructure and charging units? Might that bloc want to vote in favor of the proposal, in the hopes of creating a risk-abating ripple effect across the industry? Or should it vote against it, looking to generate ripples of efficacy and productivity?

For the traditional proxy advisory system, there’s only one answer to these questions, and it comes down to what their people are recommending. Troop’s AI tooling, rather than prescribing a strategy, offers solutions derived from what investors already know they want. It’s how we’re supercharging the process: serving more kinds of clients, with an even keener eye.

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