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Clickbait and Charts to Nowhere

There are some unrealized promises in political risk.

Words: Peter Marino and Milena Rodban
Pictures: Samuel Zeller

The political risk industry, buoyed by recent years of geopolitical unrest, and arguably more prominent than at any time in its history, is failing its customers. Both the people who style themselves pillars of the political risk industry, and those who are attempting to innovate (and sometimes automate) political risk analysis, are exacerbating an industry-wide crisis. Political risk is meant to give clients customized, detailed, and timely insight to help investors and firms operate more successfully in complex business and security environments, helping them understand how changes in those environments can improve or threaten their specific investments and operations. Instead, many older firms have become little more than publishers of international event coverage, and startups, with a tunnel-vision focus on big data and an obsession with charts are little more than publishers of infographics. Both are devoid of customization, and made for mass consumption – pithy, retweetable, and “witty.” Gone is the pretense of bespoke analysis, for specific clients with precise needs, unique vulnerabilities, and varying degrees of exposure to (geo)political risk. They are now random statistics generators and voice actors for puppet shows. This undermines the field’s credibility, and leads clients to question the industry’s integrity and value. If an allegedly prestigious political risk firm is writing reports based on information that can be easily accessed by checking a few news sites, what justifies their high-priced retainers?

Much of what currently passes for political risk analysis is little more than slightly advanced global news analysis, if even that. The focus has gone from providing customized insight, tailored to client risk profiles and vulnerabilities, to creating general analyses that can be quickly repackaged and resold to a wide number of different clients. If clients can hear this analysis on a CNN panel or a Bloomberg video on Twitter, why should they pay for it? Twitter, meanwhile, helps make it easier for clients to access just the expertise they need, just when they need it.  

To pick the most prominent example, Ian Bremmer, widely considered one of the founders of the modern political risk industry, has shifted his focus from writing books, like “The Fat Tail” and “Every Nation for Itself,” whose arguments could be discussed in thoughtful debates, to tweeting random statistics and memes, devoid of context, and mostly without attribution. More puzzlingly, he recently began sharing his thoughts via a puppet made in his likeness as he shops around a show of his own to rival Fareed Zakaria. Eurasia Group’s recent deal with CBS, to provide “strategic insight” to the news network via Bremmer’s GZero Media is the first step in that process, but again treats this insight as something designed for mass consumption – general, broad, and simple. This hardly helps the political risk industry earn respect as an intellectually and methodologically rigorous field, and suggests that it’s just basic news analysis, generalized for the masses who tune in to television news.

The broader arrival of big data has been a boon to an industry struggling to prove its worth to clients, and reluctant to do the real work needed to fix itself. As an industry largely driven by qualitative rather than quantitative methods, political risk eagerly adopted big data analytics, often without serious reflection or review. Many of these amount to having analysts hand-scoring past events, and creating records of how many people accessed certain Wikipedia articles following specific global events, which analysts then claim can somehow be used to predict future, related events. In pursuit of this, Verisk, a data firm, acquired Maplecroft, a political risk consultancy, in hopes of blending big data capabilities with analytical prowess. And there are new firms popping up regularly, including GeoQuant, a new firm that publishes charts without y-axes, because, we were told, those are for paying clients only. The nebulousness of “Big Data” works in the political risk industry’s favor at the moment. Reliance on the somewhat inscrutable technique, whose experts and critics are still few, can lend credence to reports and conclusions in clients’ minds even if this certainty is factually unwarranted.

Much of this derives from the inherent methodological difficulty in developing useful, meaningful, quantified metrics to represent political risk.  As a standalone concept, “risk” is not naturally quantifiable. Something may “feel” more or less risky, but any numerical representation of it must be anthropogenically imposed. This poses two problems: first, it must be developed, and second, its meaning and method must be explicable to clients. Neither of these is easy. And the complexity of the second task can interferes with sales. Clients would prefer not to spend a semester on quant methods in political science to understand their expensive charts, and investors prefer products that can move.

As a consequence, political risk firms tend to rely on existing quantified proxies for the objects of analysis they wish to measure – stock indices, currency spreads, bond spreads, etc. This has created a series of problems that devalue the insight of the analysis being given and treat the client poorly. To begin with, the finance industry has been using this technique for decades to forecast trends about political risks in financial instruments. To dress up these indices with new aggregation and algorithms offers minimal additional value.

Further, most quantification-driven political risk firms (or individuals) treat these algorithms and weighting systems as proprietary information. At best, this is low-level customer manipulation, selling something that clients cannot understand, examine, or act on fully, and at worst, it exposes clients to additional risk if they entrust decisions to such output without being able to understand how the oracular figures are divined.

This approach, however, is predicated on clients’ inclination to over-value quantified conclusions and insights, even if the epistemological value of those numbers is questionable. Data science as a field is still finding its way, and not enough questions are asked about the sources, quality, and comprehensiveness of the data it uses, let alone the extent to which it is manipulated. The value that these firms provide is reduced to fancy charts, rather than customized information meant to answer specific client questions. This will fool some people, but does a disservice to the field because it undermines efforts to make political risk a methodologically rigorous field. We are even tempted to argue that it is actually expressly exploitative of client ignorance of the quality of the data, the methods used to manipulate it, and the conclusions drawn from it. But as yet, still only tempted.

Even with bright graphics and data-laden charts, most of the conclusions generated by these data analysis/political risk firms go to confirm decisions that have already been made, or to support conventional thinking on an issue. Political risk insight is sought largely only after a decision has been finalized, to fulfill a compliance requirement, rather than contribute in any meaningful way to the decision-making process itself. This naturally drives companies to rely on political risk firms already seen as “prestigious,” to ensure that they have sought what is considered the best insight, or towards cheapest insight, since they don’t plan to use it anyway.

Political risk affects individual firms in highly particular, nuanced, and complex ways. Even the term “risk” itself can be misleading, as political changes that could mean calamity for one firm might mean the opportunity of a generation of another. The “advanced news” route of service provision pursued by many older firms is too generalized to capture this, and generally doesn’t justify the high price tag often associated with it. Meanwhile, existing black-box risk quantifications are not only vague, they are impossible for most any client to verify and use. The explosion of high-quality, free academic blogs and research in the last decade has rendered the first method obsolete, and until methodology catches up with hype, the second does not have utility. Political risk analysis, like politics itself, remains a tricky, highly particularistic business, which needs to be suited to specific circumstances.

Practitioners and clients will need to become more responsible. The former need to recommit themselves to intellectual rigor, while the latter need to demand substance over splash.

Peter Marino is the founder and policy director of The Metropolitan Society for International Affairs, an NYC-based think tank, and senior researcher at the Global Narratives Institute. Follow him on Twitter: @nycitywonk.

Milena Rodban is a geopolitical risk consultant and simulation designer. She designs and facilitates interactive simulations to allow clients to diagnose problems, analyze major decisions, and integrate more effective communication, collaboration, and crisis response protocols. She is finishing a book on the political risk industry. Follow her on Twitter: @MilenaRodban

Peter Marino and Milena Rodban

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