What Is Systemic Risk?
Let me explain systemic risk directly to you: it's the possibility that an event at a single company could trigger severe instability or even collapse an entire industry or the whole economy. This was a major factor in the 2008 financial crisis. Companies that pose this kind of risk are often called 'too big to fail.'
These institutions are massive compared to their industries or form a big chunk of the overall economy. If a company is highly interconnected with others, that also makes it a source of systemic risk. Don't confuse this with systematic risk, which affects the entire financial system.
Understanding Systemic Risk
The federal government often uses systemic risk as a reason to step in and intervene in the economy, and it's usually justified. The idea is that through targeted regulations and actions, the government can reduce or minimize the ripple effects from a company-level event.
It's important for you to know that even though some companies are seen as 'too big to fail,' they absolutely will fail if the government doesn't intervene during tough economic times. However, there are cases where the government chooses not to act, especially if the economy has just had a big run-up and needs a cooldown. This is rare, though, because it can destabilize things more than expected, thanks to shifts in consumer sentiment.
Examples of Systemic Risk
Take the Dodd-Frank Act of 2010, officially the Dodd-Frank Wall Street Reform and Consumer Protection Act. It brought in a huge set of new laws aimed at preventing another Great Recession by tightly regulating key financial institutions to cut down on systemic risk. There's ongoing debate about whether we need to tweak these reforms to help small businesses grow.
Lehman Brothers was a prime example because of its size and deep ties to the U.S. economy, making it a clear source of systemic risk. When it collapsed, it caused chaos throughout the financial system and the broader economy. Capital markets froze, and businesses and consumers couldn't get loans unless they were extremely creditworthy and low-risk for lenders.
At the same time, AIG was facing massive financial troubles. Like Lehman, AIG's connections to other institutions marked it as a systemic risk during the crisis. Its assets linked to subprime mortgages and involvement in the residential mortgage-backed securities market via its securities-lending program led to collateral demands, liquidity loss, and a credit rating downgrade as those securities lost value.
While the U.S. government let Lehman go under, it bailed out AIG with more than $180 billion in loans to avoid bankruptcy. Analysts and regulators figured that if AIG failed, it would take down many other financial institutions with it.
Other articles for you
An irrevocable trust transfers assets out of the grantor's control to protect them from taxes and creditors, and it cannot be changed without permission.
The unlimited marital deduction allows spouses to transfer unlimited assets tax-free, deferring taxes until the second spouse's death.
Best endeavors is a contractual obligation requiring a party to use all necessary efforts to fulfill agreement terms, stricter than reasonable endeavors and equivalent to best efforts in the US.
A grandfather clause is a legal exemption allowing continued activities under old rules despite new regulations.
The Unified Payments Interface (UPI) is a secure, real-time mobile payment system in India that simplifies bank-to-bank transfers without needing sensitive details.
Electronic money is digital currency stored in banking systems and backed by fiat for electronic transactions.
The home market effect explains why countries with large domestic demand for certain goods tend to produce and export more of them, especially those with high economies of scale and transport costs.
Treasury bonds are long-term, low-risk U.S
An evergreen loan is a revolving credit option where borrowers pay only interest and defer principal repayment indefinitely.
Multiple linear regression is a statistical method that uses several independent variables to predict a single dependent variable.