The Top Global Gray Rhinos of 2017

This week, we have a guest post from our friend , the author of THE GRAY RHINO. It’s a post Michele wrote earlier this year where she takes a look at the possible disruptions facing the world today. Wucker’s work recently received coverage from the People’s Daily Newspaper in China, which warned of Gray Rhinos that might affect the Chinese Economy. 

What will keep investors and policy makers up at night in 2017?

For the second year in a row, I’ve sorted through lists of predictions and top geo-political and geo-economic “gray rhino” risks: the highly obvious, probable threats that may or may not be getting the attention and responses they need to be averted. More often, the answer is “not.”

With the European Union dropping to third place and the United States taking the top spot, China has risen to second place. Technology –including both cyber attacks and the economic and political fallout of automation and artificial intelligence on jobs- has bumped the Middle East off of the top five list. Market shocks have fallen to fifth.

This list is derived from nearly two dozen “top risks” and predictions lists, as well as reports from analysts. Because these lists come from different angles, I’ve focused on those with geo-political and economic implications. I’ve factored in number of mentions and where each risk is on a list; connections with and impact on other risks; size of the risk; and speed. While no list is perfect, studies show that drawing on a wider, diverse set of inputs comes up with the most accurate assesments.

So, without further ado, here are the Top Global Gray Rhinos of 2017:

1) The United States political environment is the top risk this year, up from third place in 2016. It gets top billing in part because of the global reach of its impact and the sheer number of mentions not just of the broad political situation, but of the potential consequences: regulatory and legislative whiplash, growing populism and anti globalization, big power saber rattling, income and wealth disparity, and authoritarianism, political violence and extremism. The Economist Intelligence Unit –which in 2016 rated a Trump presidency the “top global risk”- downgraded the US from “full democracy” to “flawed democracy” as a result of recent developments. The turmoil at the beginning of the Trump administration bears out these concerns.

2) China’s intertwined economy and politics. The economy is the top risk for the Economist Intelligence Unit, and military issues the second-highest risk for Eurasia Group. The 19th Party Congress this fall brings the risks that always accompany transitions, as President Xi Jinping presides over high-level leadership changes. Reports that China’s foreign currency reserves fell by $320 billion in 2016, and in January for the first time in six years fell to a hair under $3 trillion –of which only $1 trillion is estimated to be liquid. Michael Pettis, one of my favorite China analysts, has long argued that markets underestimate the size of China’s problems, but that the country is still likely to avoid a full blown crisis. But even he is increasingly worried. Analysts identified China as a major risk in 2016, but it dropped off the radar when it seemed that it might muddle through successfully. But this year, China has edged out Europe for the second spot because of the sheer number of mentions and interconnections with other risks –particularly given provocations by the new US administration. The challenges facing Europe, however, are daunting as well.

3) Fractures in the European Union, the top risk of 2016, remain a major risk, slipping to third place only because U.S. and China risks are perceived to have risen even more. With roughly €360 billion in distressed loans (versus €225 billion in bank equity), Italy is facing some hard realities. German taxpayers are not likely happy with the prospects of a bailout in Italy, nor with continuing Greek drama. Recent polls show German Chancellor Angela Merkel losing her re-election bid in September. Deutsche Bank, with intricate, systemically significant connections across the global economy, remains a major risk. French elections, where Marine LePen has pledged to withdraw from the Eurozone and possibly even the whole EU if she wins. While polls suggest that she’d lose in the second round, we know all too well how fickle polls can be. Following the 2016 Brexit vote and Italian referendum, the anti-EU forces have been gaining momentum. Growing political extremism and further terrorist attacks could tip the balance further.

4) Management of technology, including cyber attacks and responses to the impact of automation on jobs, has received attention from both political risk-oriented lists and more operationally oriented. This broad category is tied in to the rise of populism in the United States, fed by fears on both the national security and the job security front. Cyber attacks were mentioned on nearly half of the lists consulted, reinforced by worries over business interruptions. Growing cyber dependency makes economies and governments that much more susceptible to cyber attacks. Though trade and immigration have been the target of populist furor, a number of analysts have rightly pointed out that robots and automation are a much bigger threat to jobs –an issue that has not received the policy attention that it needs.

5) Market volatility has fallen in the number of mentions this year, but that may simply because analysts are looking at the risks above as triggers to market gyrations. Or, more troublingly, it may be because of what one small investor expressed to me: “They keep saying it’s going to collapse and it doesn’t, so I thought I’d get back in.” Analysts listed market concerns ranging from politicized central banks to interest rate volatility and rising inflation, US dollar, and interest rates, to corporate debt. Underfunded pensions are another concern. The Bank for International Settlements has been warning about the risk of a China banking crisis and involving rising global debt levels.

Worries over the direction of the global economy as a whole were relatively low, perhaps because there is typically a lag between market and political shocks and slowing economies.

Other risks that were mentioned but didn’t make it to the top 5 include the Middle East as a whole, with particular concerns over Turkey, Afghanistan and Syria; North Korea, Venezuela, South Africa, India/Pakistan tensions, the Philippines, and India.

Climate change and its consequences received two mentions on this year’s lists, along with related mentions of natural catastrophes and business interruption.

In coming weeks, I’ll be going into more depth on the top five global gray rhinos and what’s being done about them.

You can view many of this year’s predictions and top risks reports here.

Originally published at www.thegrayrhino.com.

 

Michele Wucker is the author, most recently, of THE GRAY RHINO: How to Recognize and Act on the Obvious Dangers We Ignore (St Martin’s Press, 2016). She is the founder and CEO of Gray Rhino & Company (www.thegrayrhino.com), which helps decision makers develop strategies that create new opportunities from clear but under-addressed risks.

Deepwater Horizon: The Movie

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Peter Berg’s Deepwater Horizon (trailer) premiered at the Toronto Film Festival, so I had a chance to see it before it hits theatres at the end of this month.

It was a bit difficult for me to enjoy this movie, but that’s just because I know the story quite well. I’ve read the report, taught the case a bunch of times, wrote about the accident, and am writing about it again. When you know all the plot twists that are coming, a film is just not that interesting. So I will let more qualified others comment on its merits as a piece of entertainment.

But I do want to say that the film did a nice job of covering the main themes of the event and (some of) its causes. It’s a Hollywood disaster movie, rather than a documentary, so one shouldn’t expect a perfect coverage of all the details. But the essence of the disaster is quite well captured, from the relationship between BP and Transocean to the disturbing scene (and a compelling illustration of confirmation bias in action) when the negative pressure test is redone because it doesn’t initially provide the “right” result.

So it’s worth watching. And if you’re looking for a more in-depth, scholarly analysis–something more Harvard than Hollywood–check out Deepwater Horizon: A Systems Analysis of the Macondo Disaster (by Earl Boebert & James Blossom; Harvard University Press), which also came out this month.

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More experts, more bankruptcies?

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My friend John Almandoz and I recently published a paper on the relationship between the proportion of banking experts on a bank’s board of directors and the likelihood that that bank will fail. A reader-friendly summary just appeared in the online edition of Harvard Business Review. Click HERE to take a look, and let me know what you think!

Illusory Redundancy Strikes Again

What my trip to the airport teaches us about why catastrophe happens.

I noticed the feeling of rain in the air as soon as I stepped out of my final afternoon meeting on this trip to New York. Since moving to Seattle, I have missed the powerful, dramatic summer thunderstorms that the East Coast produces, and I suspected that one was in store.

I had a few hours until I had to be at JFK, but it was too early to have dinner, so I decided to retreat to a cafe in nearby Flatiron for a respite from the heat and humidity.

A few minutes later, the deluge arrived. The rain hammered the street as well-prepared pedestrians hoisted umbrellas. It soaked the unprepared.

I was hoping to have dinner at a restaurant that was a fifteen-minute walk away. Burdened by a rolling suitcase, and lacking an umbrella or rain jacket, I decided to check on Uber.

When I first looked, the surge multiplier was around 2.0, but in minutes the rain and rush-hour commute caused it to skyrocket to nearly four (with long wait times to boot). I decided to simplify and grab dinner around the corner, scurrying from awning to awning to avoid a soak.

After a quick dinner, I checked in on Uber again. Still a surge multiplier of 4.0, which made the ride from Manhattan to JFK around $400, more than I wanted to spend.

But, I’ve lived in New York before, so I decided to use my go to backup option: the Long Island Rail Road and AirTrain. The rain let up a little, and I made my way to Penn Station—a few-block walk and a quick subway ride away. Commuters packed the station, some milling about waiting for more information about delays on their lines. But the train to Jamaica still seemed OK, so I purchased a ticket, rushed down to the track, and jumped on the 6:31 train with only a moment to spare. If everything went well, I’d arrive in plenty of time for my 8:45 flight.

But everything wasn’t going well. Instead of speeding out of Penn Station, the train just sat.

A few minutes later, the conductor announced, “I have just heard from the Station Master: we’re being held momentarily in the station.” Commuters groaned collectively—a momentary delay on a day like today was unlikely.

Their suspicions were well founded. In a few more minutes, the conductor announced that “due to weather-related signal problems near Jamaica, this train line is being suspended until further notice.”

There I sat, a victim of illusory redundancy, when a backup system is vulnerable to same disruption as the system it’s meant to protect. Illusory redundancy is all about unexpected correlations, in this case rain drove Uber’s increasing demand and caused signal failures on the LIRR.

Illusory redundancies lie at the core of many meltdowns. During Hurricane Sandy, for example, the storm surge destroyed a key substation and blacked out a large chunk of Manhattan. At the same time, the surge flooded NYU’s state-of-the-art hospital, located a few blocks uptown, disabling their backup generator and forcing the evacuation of critically ill patients.

Before the launch of the Space Shuttle Challenger, engineers at NASA assumed that having two O-rings on the potentially problematic solid rocket boosters provided sufficient protection: even though cold temperatures might affect one important seal, they argued, the second would provide a backup. Yet when the primary O-ring failed during the stress of the launch, hot gasses from the booster quickly eroded the backup, causing it to fail as well and leading to Challenger’s destruction.

And illusory redundancy doesn’t just occur in physical systems. During the financial crisis, products like auction rate securities, which once seemed safe and liquid because of the breadth of participants that traded them, froze as shocks simultaneously affected many financial institutions. Anyone relying on the redundancy of multiple participants quickly realized their folly.

I thought of these examples as I made my way off of the train and onto the main level of Penn Station. It was so crowded with commuters that police had shutdown the station and were preventing people from entering. Inside, I found a corner with a trickle of 4G internet and checked out the Uber situation – surge pricing had dropped to 1.2. I requested a pickup and raced up to street level to meet the driver.

Traffic was bad, and we didn’t get to the airport until 8:52. But I had one thing going for me – I knew that the same weather system that shut down the LIRR caused delays at JFK. I thought that I still had a chance.

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The incoming flight. Note the racetrack holding pattern in the top left.

After passing through security, I ran to my gate, and arrived just as the gate agent called my boarding group.

I was lucky – though I was surprised by illusory redundancy, unexpected correlations, in the form of flight delays, worked in my favor.

Knowing that New York can be virtually shut down by heavy rain, I might have headed straight to the airport to wait there at the first sign of rain. It certainly would have made for a less exciting afternoon.

The Big Hack – NY Magazine

NY Magazine has an interesting (fictional) story about a 2017 cyber attack. Almost all of the elements seem plausable: a mix of hardware-based and people-based attack vectors, failures of coordination, confusion, and the financial consequences.

It’s worth a read.

 

Poets & Quants MBAs To Watch: Anthony Harbour

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Congratulations to Rotman School of Management graduate Anthony Harbour for being selected by Poets & Quants as one of their MBAs To Watch this year. Anthony was a student in my Catastrophic Failure in Organizations course as part of a great cohort in 2016 (thanks for the shoutout to the course, Anthony!). A Los Angeles native, Anthony came to Rotman with prior experience at the U.S. Securities and Exchange Commission and left a lasting mark on the Rotman School. You can read about his many great contributions to our community on his Poets & Quants profile. Congratulations, Anthony!

 

Reg AT – Don’t Go There

Craig Pirrong, the Streetwise Professor, recently wrote about his skeptical take on the CFTC’s desire to examine the source code of trading algorithms. The proposed Regulation AT (Automated Trading) has many issues, and Pirrong calls out two of them:

I seriously doubt that the CFTC can attract people with the coding skill necessary to track down errors in trading algorithms, or can devote the time necessary… for a truly effective review.

This is a great point. If the CFTC is so burdened with what’s on their regulatory plate already, how can they possibly add this? And how can the CFTC hope to compete with trading firms for the technical talent required to effectively review such code?

Second, and more substantively, reviewing individual trading algorithms in isolation is of limited value in determining their potentially disruptive effects…

This is because in complex systems, attempts to improve the safety of individual components of the system can actually increase the probability of system failure.

Pirrong is a scholar after our own hearts, and he hits on so many important points here. The theory of complex systems tells us that non-holistic safety mechanisms often make things worse.

For example, after the 2010 Flash Crash, the SEC implemented single-stock circuit breakers. Such measures seem like a good idea, and the circuit breakers often help minimize disruptions. But on August 24, 2015, these single-stock circuit breakers halted trading in 471 different ETFs and stocks. This in turn lead to further dislocation as many key ETF liquidity providers simply stopped trading because they could no longer model the baskets of securities that underlie many ETFs.

Worse, if the intent is to prevent Knight-like fiascos, the CFTC should look elsewhere. Knight’s problem wasn’t even a coding error. Knight’s code worked—it was just deployed incorrectly. If that sounds like splitting hairs, that’s precisely the point. These systems are so complicated that code divorced from configuration files and deployment procedures is essentially meaningless.

I understand where the desire for a Reg AT-type solution comes from. The complexity of the financial markets is increasing, and we’ve seen over and over that regulators are struggling to get a handle on things. But if the CFTC really wants a window into the risk of automated trading, they should take a page from the Federal Aviation Administration’s playbook (as we’ve argued before). The FAA supports the airline industry’s quest for safety by cooperatively interfacing with airline-run Safety Management Systems. These systems specify a structure for reporting, discussing,  correcting errors, and for auditing those corrections—largely without the fear of regulatory reprisal.

The CFTC should drop the costly, draconian, ultimately counterproductive Reg AT proposal. Instead, they should consider “Reg SMS,” in which they work with the industry to set up standard error capture, discussion, and QA processes—modeled after the airlines’ Safety Management Systems—so we can all get a handle on this complexity together.

Just as there are best practices for coding, there are best practices for managing complexity. The CFTC needs to look for them.