How Social Media Killed Silicon Valley Bank

The following is a guest post from web3 strategist Toby Fan, and Aly Madhavji, Managing Partner of the Blockchain Founders Fund.

Social media has forever changed the way we view and handle financial crises. Banks need a way to tactfully manage what is now called “social media risk.” Viral phone games played on an exponential scale leave very little time for nuanced investigation or thoughtful reaction. By incorporating social media into overall risk frameworks, banks can help shape the narrative and public perception through proactive and transparent customer engagement. Aggregation and monitoring tools are becoming increasingly important to monitor for early signs of problems and navigate this landscape of rapid information ingestion and rampant spread.

The recent collapses of some of the largest banks associated with cryptocurrencies ($SIVB, $SI, $SBNY) have caused jitters in the tech, crypto, and banking sectors. Many startups were left wondering if they could meet payroll obligations, while regional banks caught signs of a bank run for the first time since the subprime crisis.

Crowd interpretations of data on the financial health of $SIVB gave depositors a crash course (no pun intended) in Game Theory 101, putting many tech and startups in the shoes of a prisoner in a book payout matrix text: Withdraw deposits now or risk purse retention.

how it all went wrong

On March 8, Moody’s downgraded the bank’s issuer and deposit ratings by $SIVB. On the same day, $SIVB announced a proposed sale of $2.25 billion in shares, along with a balance sheet repositioning showing a realized loss of $1.8 billion on the sale of fixed income assets that had lost significant market value with the recent increase of the Federal Reserve rates.

Like many bank runs before this one, depositors, many of them cryptocurrency and venture capital-funded firms, wasted no time playing chicken. Within a day or two, $SIVB’s balance sheets were drying up and the shares were falling; by March 10, regulators had shut down $SIVB and taken control of its deposits. A host of regional banks followed suit, taking massive write-downs in market value ($FRC, $WAL, $CMA, $ZION) before rallying on news of an FDIC endorsement of deposit insurance. And while there have been similar cases of bank runs in financial history, what made this one so exceptional was the speed at which it happened and the medium through which the contagion spread.

The financial contagion went viral on social media. Social media platforms like Twitter dominate the crypto and startup space. The speed of information diffusion (as well as the different interpretations) is an order of magnitude higher than that of traditional news or linear media. Even regulators have recognized the impact of social media in the most recent crisis. House Financial Services Committee Chairman Patrick Henry admitted that “this was the first Twitter-driven bank run.”

Some may remember Washington Mutual, which experienced similar deposit outflows during the 2007-2008 financial crisis. Like $SIVB, WaMu had more than $188 billion in deposits, but began to write off significant losses due to delinquent mortgages. When Lehman Brothers collapsed on September 15, 2008, WaMu depositors began withdrawing money en masse, withdrawing $16.7 billion from checking and savings accounts (~11% of total deposits) over ten days. The speed of the outflows was unprecedented at the time, which ultimately led to WaMu’s bankruptcy. Compare this to $SIVB, where depositors attempted to withdraw $42 billion in a single day, equal to 25% of total deposits.

This time, it wasn’t just the unprecedented speed of information, but the closeness of social distance (among Twitter followers, friends, and subreddits) that helped the news spread like wildfire. Whereas before in traditional media, news was disseminated from centralized parties to the masses (a one-to-many transaction), social media is a many-to-many transaction, and the social distance between sources is much closer. , giving these assets a level of social proof that hasn’t always been present in traditional media. And once the information reaches a critical mass, it becomes the truth as the inertia of diffusion causes the story to become ubiquitous. As they say, a person’s perception is his reality.

The power of viral narratives

By monitoring aggregated social media data, you can see examples of this rapid spread, even early signs of it. Take, for example, Silicon Valley Bank:

In red, we have social media volume (individual tweets/posts/news articles on Twitter, Reddit, and 1000+ news sources) and $SIVB stock price in green. You may see a post-fact spike in social media volume. Zooming in closer, though, you can start to see growth in conversations before the parabolic spike in social media volume (indicating the powerful velocity of social media reach):

Digging further into the days leading up to $SIVB’s significant drawdown, you can see the whispers from industry insiders and analysts ahead of a big relative rise just as stocks start to fall. By digging a little deeper around the time social media activity started to spike, an analyst may have been able to uncover hidden gems like this one from Matt Harney:

Lower fundraising

+

Businesses with negative cash flow (on average)

=

Liquidity drain:

🆘 Negative $57 billion in total client funds in 2022 from startup banking at Silicon Valley Bank

– source = latest MS “Venture Vision” pic.twitter.com/ZMD7miBuyE

—Matt Harney (@SaaSletter) March 7, 2023

or this one from Rusil Sarka that may have raised early red flags for anyone involved with the bank:

When there is an unusual outflow of deposits, the bank needs to sell its assets to meet the withdrawals, which is when the bonds need to adjust to the market.
The same thing happened with Silicon Valley Bank in 2021, when rates were low. He took $91 billion of that money and invested it in mortgages.

— Rusil (@rusilsarkar) March 6, 2023

Similar patterns can be found with the stocks of regional banks affected by the $SIVB fallout, namely banks like First Republic, Western Alliance, Comerica, Zions, and PacWest, which saw up to 65% drawdown in one day. All of these large drops were preceded by parabolic increases or surges in social volume, demonstrating the speed and conviction of social media contagion:

First Republic Bank (through LunarCrush)Charles Schwab (through LunarCrush)Western Alliance Bancorporation (through LunarCrush)Zions Bancorporation (through LunarCrush)

Social media is a real financial risk

Monitoring for outsized or abnormal increases in social chatter can help catch early signs of calm (but soon to be not) developments. These large deviations in social activity often carry with them self-fulfilling alpha fragments. By capturing the attention of the masses and stimulating action in a short period of time, it often creates a game-theoretic dynamic in which the first person to act generally has the most to gain (or the least to lose) and makes action or participation more attractive to the following. party.

“Social networks have accelerated the spread of financial information and, with it, the potential for market contagion. Banks need to recognize and manage ‘social media risk’ as part of their overall risk frameworks. Tools like Moonrise by LunarCrush can help monitor and track early warning signs, allowing financial institutions to shape narratives and engage with customers more effectively,” said Joe Vezzani, CEO of LunarCrush.

One thing is clear: the dust settles on a difficult week in the banking sector. Banks need to meet customers where they are and manage narratives and crises quickly in their preferred medium. A good communication strategy may have helped stop the fallout, but the key would have been to first capture these narratives early in their development. By using smart aggregation tools and maintaining a strong and transparent social media presence, it is hoped that industry participants can be quicker and better prepared to react to and manage these crises in the future.

The data here is courtesy of the LunarCrush APIa social media monitoring engine that provides access to accurate, high-latency data on 4,000+ crypto assets, 300+ NFT collections, and 700 stocks.

Author(s):

Toby Fan, Web3 Strategist Twitter | LinkedIn:
Toby Fan is the Lead Web3 Strategist at LunarCrush, which provides real-time aggregated social media data on crypto, NFT, and traditional stocks. He graduated from UC Santa Cruz, where he double majored in Econometrics and Information Systems and helped lead departmental research on commodity market dynamics in China and the US. Toby is also an active contributor to CoinMonks (https://medium.com/@tobyornottoby) and a member of the BlockBros DAO.Aly Madhavji, Managing Partner of Blockchain Founders Fund and LP at Loyal VC & Draper Goren Holm Twitter | LinkedIn
Aly Madhavji is the Managing Partner of Blockchain Founders Fund, which invests in and builds world-class start-ups. He is a limited partner of Loyal VC and Draper Goren Holm. Aly consults emerging technology organizations such as INSEAD and the UN on solutions to help alleviate poverty. He is a Senior Blockchain Fellow at INSEAD and was recognized as a “Blockchain 100” global leader by Lattice80.