SVB Collapse: A cautionary Tale of Concentration Risk and Lending to the Rich

Silicon Valley Bank, First Republic, Signature Bank - in one week in America, the second largest bank in US history went bankrupt along with the collapse of other smaller banks. What unites them? A warning about the risk and impact of lending only to the wealthiest part of society.

Silicon Valley Bank Customer Profile

Early in its operations, the Silicon Valley Bank began to grow and expand rapidly as many of its technology-based clients prospered at the onset of the pandemic. The bank took the risk of lending to risky tech start-ups and cryptocurrency companies that no one else would lend to. The bank's customer base consisted mainly of extremely wealthy clients, and it lent exclusively to this segment of the population, ignoring everyone else, since it was the wealthy clients that ensured growth. Deposits tripled between 2020 and 2022, with billions of dollars flowing into it. The Silicon Valley Bank used the money it made from taking on these risks and invested it in what was considered a less risky investment: US government bonds.

Government bonds

Bonds are generally viewed as a risk-free investment. Bonds are loans that individuals make to the government for a specific period of time (3 months, 1 year, 10 years, etc.). When the loan expires, the government repays the debt along with interest. Although these bonds are considered risk-free, they are not extremely profitable, but long-term bonds are more profitable and pay more interest at maturity. SVB intended to get the highest payout and took the longest term of the bonds to earn as much as possible from its investments in wealthy clients, having invested billions in these long-term bonds, it was possible to return the invested funds only after 10 years.

However, SVB did not foresee a possible increase in interest rates in the future. That is, the market value of bonds is directly related to the interest rate. When interest rates rise, the market price of old bonds falls because new bonds pay higher interest. Therefore, the market value of SVB bonds experienced a significant decrease.

Influence of wealthy clients

As mentioned earlier, SVB's main clients were very wealthy individuals and businesses. When rumors began to spread about the bank, customers began to panic and urgently withdraw their money. Since these were wealthy individuals and companies, this meant that multi-million, even multi-billion dollar sums disappeared from their accounts at the same time. The Silicon Valley Bank urgently needed a lot of cash, and a significant portion of its funds were locked in 10-year bonds. In addition, as prices fell, banks issued products at a price below their cost. This meant that now the bank had to try to sell it at a loss in order to cash out.

Banks take money from the rich and lend it to the rich. All banks provide loans to rich people because it is easy to secure or get approved for a loan. However, people with high incomes are only a small 5% of society and all banks want to lend exclusively to this 5%. This creates a huge imbalance of supply and demand: there is a limited supply of the rich and a lot of demand from banks that want to borrow from the rich. This demand-for-supply problem has resulted in an oversupply, causing the prices of these loans to fall and making the underwriting and approval process easier.

Solving the problem of uneven lending with the help of artificial intelligence

The problem of supply and demand can be solved by banks by introducing artificial intelligence. Artificial intelligence allows banks to lend to everyone anyway, as the technology is fast and able to calculate complex lending scenarios. Banks tend to prefer clients with a stable income over a client with a less linear background. However, artificial intelligence facilitates this process of assessing the creditworthiness of applicants. It ensures that borrower applications are treated in the same way. That is, it means that lending to a low-income person with multiple jobs and complex financial problems will become as easy as lending to an applicant with a million dollars in a bank account. One example is Celligence, a fintech startup bank that is already implementing the technology. They have created artificial intelligence to help banks and borrowers process loans quickly and easily for all borrowers. Banks don't like difficult borrowers and want to get their money back easily. Artificial intelligence ensures that everyone is on an equal footing, not just people with millions in their accounts.