When good debt turns bad

OPINION:

The Beginning of Our Troubles

As a response to the emergency financial and health environment caused by COVID-19, central banks around the world dropped interest rates to an all-time low and provided generous fiscal programs to businesses on a scale we have not previously witnessed. Quantitative easing (‘QE’) was applied to buy existing bonds and provide market liquidity, whilst governments issued new Treasury Bonds to raise the much-needed capital for these emergency COVID-19 programs.

The sheer scale of this coordinated global economic response completely dwarfs the measures used by governments during the GFC (approximately 6.5x in size and scale across developed countries). In the aftermath, we Australians now find ourselves fighting the steepest inflation in over three decades. It is my belief that this period will be studied by economic historians with the tagline and conclusion – “Excess money supply equals high inflation” – affirming the late Milton Friedman’s own body of work into this subject matter.

As the old saying goes – “There is no such thing as a free lunch”; we are certainly paying for it now. We are paying for dinner as well – WITH dessert.

Banks Buying up Treasury Bonds

The COVID-19 stimulus packages led to banks around the world seeing increased deposits. With the banks needing to invest this surplus money somewhere, and the lending environment not being favourable to them, the banks resorted to purchasing newly issued government bonds at near-zero coupon rates. Buying treasury bonds was encouraged by regulators and was seen as prudent practice given that the treasury bond is one of the least risky assets to hold on your balance sheet amid a financial crisis. This low risk is due to the government essentially being a guarantor of the capital – in other words, the government will give you back your money with certainty. Buying treasury bonds also has the benefit of meeting the capital adequacy requirement imposed by regulators.

It has surprised everyone that the economy recovered so rapidly, fuelled by pent-up demand and surplus savings. Unfortunately, this fast-paced recovery unleashed inflation, leading to the fastest and most consecutive interest rate increases in Australia’s modern economic history.

Now, let us shift our focus back to the so-called “risk-free” treasury bonds. Most government bonds have a fixed income stream linked to the official interest rates at the time of issue. As the official cash rate increases, these assets diminish in value. The S&P/ASX Australian Government Bond Index has shown a greater than 10% fall since August 2021, with some of individual bonds falling in value up to 20%

If the income stream for a government bond is say, 1%, this would be less attractive than the current cash rate of 3.60%. Therefore, the face value (price) falls as the cash rate rises, allowing the bond to be traded with the appropriate numbers. Despite this, government bonds are still safe and secure. The government’s sovereignty backs the income stream. It is easily traded in the money market and considered as good as liquid cash for banks, with regulators requiring significant exposure to these instruments as part of the credit creation function performed by banking institutions. For example, every dollar held in bonds, allows four dollars to be lent to borrowers.

The Misleading Safety of Government Bonds

Here comes the iceberg. The only asset on the bank’s balance sheet that does NOT reflect actual value is government bonds. This is due to accounting standards and reporting requirements; that is, we do not know the exact scale or concentration of government bonds held on the balance sheet of any particular bank. There are now two issues at hand here: profitability and liquidity. Poor profitability relates to the fact that the bank has poorly performing returns on assets relative to returns available on other similar assets in the market. As a result, it will need to squeeze this extra profit from somewhere else, most likely from the borrower, thus increasing the cost of capital.

While this occurs, banks are increasingly concerned about the borrower’s side of the ledger. Banks must be wary of loan arrears picking up at an alarming pace due to the higher interest rates, cost of living pressures and asset prices falling due to rising interest rates. Therefore, there is ‘credit rationalising’ by lenders. In other words, they are getting tougher and reluctant to lend new money; a classic recipe for an inevitable credit crunch.

The second half is banks that are overweight in government bonds trading below their fair value are particularly vulnerable if there is a run on their money; that is, a very large number of depositors wanting to withdraw their money in a short time frame and the bank not having the cash available to satisfy this demand immediately. This is a major liquidity issue for the particular bank in question, as well as the entire banking system if the flow-on effect is of sufficient magnitude. The commonalities between the GFC and the current crises are confidence and liquidity. However, the difference is that the GFC was predominantly caused by banks holding bad loans.

The cause of this current crisis is that banks are holding too many good loans (government bonds) that have now turned bad due to their fixed rates during a time of rapidly rising rates.

Mary Poppins and the Collapse of SVB

Just as Mr Banks in the Mary Poppins film tries to teach his son the importance of saving and investing money wisely, banks also encourage customers to deposit their money and keep it safe in their accounts. However, if there is a sudden panic or loss of confidence in the banking system, customers may rush to withdraw their money all at once, similar to how Michael Banks ran to spend his tuppence feeding the birds.

The lesson here is that just as individuals need to save and invest wisely, it is also essential for banks and regulators to maintain a stable and trustworthy financial system that can withstand sudden shocks and crises. Due to the sudden increase in interest rates, many banks have become vulnerable and illiquid. The very purpose of government bonds held on their balance sheet is to provide liquidity. However, as has been made evident in the past few weeks, this basic contingency plan has failed.

In the case of Silicon Valley Bank (SVB) in the US, the bank announced that it had lost $1.8b in the fire sale of assets to meet withdrawal demands. The bank then looked to raise $2.25b to shore up its balance sheet and restore investor confidence in the bank’s liquidity and operations. Within 48 hours, an astounding sum of $48b had been withdrawn from the bank out of fear and panic. This placed the financial institution on a pathway to collapse as further sales of government bonds could not be sustained.1

This led to other regional banks looking vulnerable. A central bank would only dare pause increasing interest rates if the act upholds confidence. However, this economic environment certainly supplies ample justification. The fragility of the banking system relies on deposit holders maintaining sufficient confidence in the banking system and wider economy. Raising interest rates leads to devaluing bond portfolios, only making banks more vulnerable and placing additional pressure on them to withstand a run on their capital, placing the entire banking system in jeopardy. Importantly the US Treasury has guaranteed all deposits in these banks to restore confidence in not only the national banking system, but the expansive regional banking system in the US.

Contagion and Credit Suisse

Although the ultimate demise of Credit Suisse was well on its way before the more recent events, the collapse of SVB put the final nail in in the Swiss bank’s coffin by escalating a run on depositor funds. Despite its share price having slumped for quite some time due to multiple scandals, including losses on highly leveraged loans to drug dealers to launder money in Bulgaria, entanglement in a Mozambique corruption case, the collapse of Greensill Capital and the failure of New York-based investment firm Archegos Capital Management.

All of these problems led to billions being lost by the bank. Despite disastrous past performance, if there had been no run on capital, the bank would have survived as it was still adequately capitalised. The Swiss government intervened in the Credit Suisse matter by placing UBS into a forced marriage with them through the provision of a handsome dowry (providing a $162b line of credit) paid by taxpayers, whilst wiping out $25b in bondholders (debt investors) and paying $4.9b (a steal) to shareholders in priority to the bondholders.

This breaks so many rules. Firstly, how can shareholders be paid in priority to bondholders whilst using the Swiss government’s money for the commercial benefit of UBS? Secondly, how is it paid for via QE?

The issuance of government bonds is only more inflationary. The unintended consequences of this action can be quite significant. Firstly, the Swiss government’s intervention undermines trust in the system; investors are less likely to invest in banks and this compounds fear for the next bank that misses expectations, with a potential run on capital to follow.

We have already been seeing some concern with Deutsche Bank following the controversy around bondholders being given priority in the aforementioned Credit Suisse saga. This is despite Deutsche Bank’s business fundamentals being in much better shape than that of Credit Suisse.

Australian Banks and the Future

Unsurprisingly, Jim Chalmers, Philip Lowe and John Lonsdale (chairman of APRA), have all come out in unison, stating that Australian banks are the strongest globally. Indeed, Australian banks are operating in an oligopolistic environment which is well regulated and funded, backed by an economy based on vast resources and immigration. The oligopoly feature of our banking environment works in our favour as it means lower competition, hence less of a necessity to lower rates and sacrifice margin in conjunction being highly regulated with capital. On the other hand, the US has over 4,200 banks and Europe has 5,171 banks.17 The small ecosystem in which Australian banks operate are the reason they are both highly profitable and there is need to take higher risk, with the regulators being able to keep close eye over the banking system.

Our banks will continue to attract depositor funds and have sufficient capital to meet withdrawals. In other words – WE ARE SAFE.

However, the world’s central banks are now fighting two separate battles on two separate fronts: inflation on the one side and fragility in the banking system on the other, which is weakened by higher interest rates and diminished confidence. It is our view that we have reached the top of the interest rate cycle. The importance of the May budget has not been this critical for decades. The government needs to be fiscally responsible in their coming budget to ensure they do not add to inflation, and the RBA may need to accept slightly higher inflation even if it is persistently above 3% for the next 2-3 years so as to not trouble the government bonds held by our banks.

In short, I expect the cash rate to remain unchanged at 3.60% for at least 4-6 months.

Final Thoughts

In the past month, we have seen a change in tone. The government is cooperating in its obligation to create a policy that helps not inflame inflation. In contrast, Philip Lowe has raised concerns regarding housing and rental inflation directly caused by a lack of property supply and increased migration. This is the government’s responsibility, which paves the way to accept higher inflation as long as wage inflation is anchored.

Ultimately, disciplined fiscal and monetary policy is required on the Australian front to ensure our banks are healthy, inflation is kept at bay, and that banking troubles in the rest of the world do not reach our shores. There is no doubt that that recent new bank collapses have completely changed the scope in which the central banks are operating within, ultimately this will lead to a credit crunch, increasing the cost of capital as banks will need and want to increase margins for risk, this will slow down the economy. Rather than worrying about higher interest rates we might have official cash rates drop quicker than anticipated.

Msquared Capital is a private credit provider with investment opportunities backed by quality property along the Eastern Seaboard; we ensure that all investment opportunities are based on risk-to-reward as our core offering and performance. Mortgage funds perform well during volatile times, and the preservation of capital is regular, with reliable monthly income that gives our investors peace of mind.

There is ample and alarming evidence that artificial intelligence can help humans do bad things, such as committing cyberattacks, building weapons and even killing themselves or others. The Hugging Face hacking episode—and a growing list of others by poorly constrained swarms of agents—indicate just how powerful and potentially dangerous AI has quickly become.

Yet many inside the U.S. AI industry insist far worse is coming, on account of the imminent arrival of AI with superhuman and self-improving abilities.

Plenty of experts, including many who study AI harms for a living, are skeptical. The so-called doomers’ assertion that AI might decide to wipe out all of humanity—or even “just” topple human civilization—is contingent on it achieving a pace of development not yet seen.

And if the assumptions behind this global-doomsday scenario are wrong, it could lead us to curb or regulate AI in ways that don’t address its real harms.

At the center of this debate is the claim that current AI systems might take over the job of training their next versions, a process called “recursive self-improvement.” Think of it like evolution on steroids—billions of years happening at light speed within vast AI supercomputers. Anthropic Chief Executive Dario Amodei recently proposed a global agreement to slow down the pace of releasing new AI models, with the goal of delaying the arrival of recursive self-improvement.

“I don’t think we’re anywhere near ‘artificial general intelligence,’” says Melanie Mitchell, a professor at the nonprofit research group Santa Fe Institute who studies AI. She said AI is making impressive strides but thinks claims by engineers that they’ve achieved recursive self-improvement don’t stand up to scrutiny.

She is hardly alone. A recent paper by two dozen academics at Princeton, Stanford and other institutions found that even the most cutting-edge AIs are incapable of doing the original research required to advance the AI frontier.

Two of the authors involved in that paper also threw cold water on the idea that the Hugging Face swarm hack by OpenAI agents occurred because of a breakthrough in intelligence. The attack succeeded primarily because of a lack of basic technical guardrails, not an unmanageable explosion in AI capability, they wrote.

Yann LeCun, former chief AI scientist at Meta, posted that this analysis was “a welcome dose of sanity in an otherwise insane debate.”

OpenAI and Anthropic didn’t respond to several requests for comment.

The people who disagree with the doomers still consider AI to be dangerous, and point out that such systems don’t have to be particularly capable to be powerful. Some argue that AI should undergo regular evaluation by outsiders and that the companies that make it should be held responsible when their systems do harm. AI should also be treated the same as airplanes and elevators, and should be designed to do the least harm possible, they say.

“If you believe that technology is powerful enough to create novel, dangerous viruses, or to essentially take over the whole planet for some reason, then it must also be strong enough to create cures for cancer, to cure aging, to fix socio-economic or political problems,” says Christopher Canal, CEO of EquiStamp, a company that helps companies and governments evaluate AIs.

AI has shown an ability to rapidly advance because it is matching the abilities of humans who are constantly feeding it their knowledge. Sometimes it can recombine that knowledge and exceed what people have been capable of, through a kind of post-training known as reinforcement learning, as we’ve seen in mathematics.

Today’s LLMs are “models of knowledge” rather than actually intelligent, wrote Yi Ma, professor of AI at Hong Kong University.

Researchers at universities and commercial AI research labs in China wrote in a recent paper that autonomous, self-improving AI is likely to be a long way off, due to the sheer number of breakthroughs required. They also argue that humans will probably remain in the loop, supervising that process—and gating how fast it can occur.

Vals AI, a company that evaluates today’s AI models, maintains an RSI Index that benchmarks whether models can “do the research that builds the next model.” So far, no publicly released model is even close.

Yet Rayan Krishnan, CEO of Vals AI, says his team projects models will exceed humans’ ability to improve the next generation of AIs by August 2027, or sooner, and at that point could start building their successors all on their own.

“Once we get to recursive self-improvement, the fear is that all bets are off,” he says. “You could end up with a ‘fast takeoff’ situation, where the models quickly acquire skills and eclipse humans across every possible domain.”

In a reply to the resignation tweet heard round the world from Jacob Coxon, another Anthropic engineer declared his belief that those odds were at least 10% over the next decade. Many others in the industry chimed in to say they thought the percentage was even higher.

Some who argue the end is nigh say they calculate their personal p(doom) based on a chain of conditional probabilities—a bit like the Drake equation for calculating the likelihood of intelligent alien life. Since all those probabilities are based on speculation, estimates range from 0% to nearly 100%. Many land around 10%.

“The weird thing is that if you go back and look at the predictions on this over the last 10 years or more, it’s always been 10%—it’s just a nice round number,” says Mitchell. “I think it’s all vibes, and there’s no actual evidence or calculation.”

One argument against worrying about superintelligent AI is that the world is full of unlikely humanity-ending disasters, and trying to avert them all can make it impossible to prioritize, says Canal.

This has led AI experts and the policymakers who listen to them to propose remedies that don’t get at its real and present dangers.

AI companies’ proposals to “pace the frontier” aren’t addressing the problem in the right way, argues Stuart Russell, a computer-science professor at the University of California, Berkeley, and the president of the International Association for Safe and Ethical Artificial Intelligence.

“It’s like saying we’re driving toward the cliff at 60 miles per hour and we’re going to drive toward it at 40 miles per hour instead, and everything will be OK,” he says.

Russell and his peers have proposed that AI companies should have to meet the same standards that govern other areas of everyday life, from air travel and buildings to food and drugs. They highlight the “behavioral red lines” AI should not be allowed to cross. Breaking into other computer systems, stealing information or advising terrorists on how to build biological weapons are all illegal for a human to do, and should be illegal for companies’ AIs as well, he argues.

The challenge for AI companies in such a proposal, he adds, is that it would be a de facto ban on today’s advanced AI systems, since the companies behind them don’t know how to make them respect such boundaries all of the time.

Others have proposed something like the Food and Drug Administration, but for AI, but setting up a new agency has so far been a nonstarter in Congress. And some prominent voices in tech have said such a structure would give up America’s AI edge to China.

Given the bipartisan groundswell of support for curbing AI companies and their creations, however, that may soon change.

“The tech industry has had this mantra for decades that regulation is bad,” says Russell. “They don’t accept the liability for any harm, and they hide behind free speech. That, I think, has to change.”

When good debt turns bad

Could fears of an AI apocalypse be distracting us from the dangers already here? Experts debate whether regulation should focus on speculative existential threats or present-day harms, including cyberattacks, weapons and unsafe autonomous agents. Read more via the link in bio.