Silicon Valley Bank's collapse: interest rate risk and liquidity risk mismanagement

Degree: Double Bachelor’s degree in Business and Economics Final Project in Business Administration Course 2024/2025 Silicon Valley Bank's Collapse: Interest Rate Risk and Liquidity Risk Mismanagement Author: Oihane Leyún Prieto Director: Jose Manuel Chamorro Gómez In Bilbao, on February 13, 2025 Abstract The collapse of Silicon Valley Bank (SVB) in March 2023 marked one of the most significant banking failures in recent history, triggering the Panic of 2023 and raising concerns about risk management practices in the financial sector. This study analyzes the key factors behind SVB’s downfall, focusing on its exposure to interest rate risk and liquidity risk. The bank’s heavy investment in long-term securities made it highly vulnerable to rising interest rates, leading to substantial unrealized losses. Simultaneously, its dependence on large, uninsured deposits from the tech sector exacerbated liquidity pressures when withdrawals surged. Through a detailed examination of SVB’s financial statements, with special focus on its balance sheet structure, this paper identifies the main sources of the aforementioned risks to later quantify them. The findings reveal that by late 2022, SVB was already on the brink of insolvency, with significant unrealized losses on long-term securities and a fragile funding structure heavily reliant on large, uninsured deposits. The poor management of interest rate risk and liquidity risk, coupled with inadequate regulatory supervision, accelerated the bank’s downfall. Keywords: Silicon Valley Bank, bank failure, banking crisis, interest rate risk, liquidity risk, risk management. 2 Table of Contents 1. Introduction........................................................................................................................ 4 1.1 Justification of the Topic............................................................................................... 4 1.2 Objectives.....................................................................................................................5 1.3 Methodology.................................................................................................................5 2. Theoretical Framework......................................................................................................6 2.1. Interest Rate Risk (IRR).............................................................................................. 6 2.1.1. Definition............................................................................................................ 6 2.1.2. Main Sources..................................................................................................... 6 2.1.3. Measurement..................................................................................................... 7 2.2. Liquidity Risk (LR)....................................................................................................... 9 2.2.1. Definition............................................................................................................ 9 3.2.2. Measurement................................................................................................... 10 2.3. IRR and LR Regulation..............................................................................................11 2.4. IRR and LR Management..........................................................................................13 3. Silicon Valley Bank’s Collapse........................................................................................15 3.1. Silicon Valley Bank History........................................................................................15 3.2. Detecting IRR and LR Sources by Analyzing SVBFG’s Financial Statements......... 21 3.2.1. SVBFG’s Balance Sheet.................................................................................. 21 3.2.1.1. Liability Structure of SVBFG....................................................................22 3.2.1.2. SVBG’s Asset Structure.......................................................................... 24 3.2.2. SVBFG’s Income Statement and Statement of Comprehensive Income......... 27 3.2.3. SVBFG’s Cash Flow Statement....................................................................... 28 3.2.4. Summary of All IRR and LR Sources...............................................................28 3.3. IRR and LR Measurement.........................................................................................29 3.3.1. Gap Analysis.................................................................................................... 29 3.3.2. Duration Analysis............................................................................................. 32 3.4. IRR and LR Management Errors...............................................................................34 4. Conclusions......................................................................................................................35 5. Reflection on the Work Done.......................................................................................... 36 6. References........................................................................................................................38 7. Appendix...........................................................................................................................41 Appendix 1: Bank category applicable regulations and risk management requirements.41 Appendix 2: SVBFG’s Balance Sheet.............................................................................. 42 Appendix 3: SVBFG’s Income Statement and Statement of Comprehensive Income.....43 Appendix 4: SVBFG’s Cash Flow Statement................................................................... 44 3 1. Introduction 1.1 Justification of the Topic Silicon Valley Bank (SVB) failed because of a textbook case of mismanagement by the bank. Its senior leadership failed to manage basic interest rate and liquidity risk. Its board of directors failed to oversee senior leadership and hold them accountable. And Federal Reserve supervisors failed to take forceful enough action (Barr, 2023). On March 10, 2023, SVB, the sixteenth largest bank in the United States collapsed, becoming the second-largest bank failure in U.S. history, following the fall of Washington Mutual Bank in 2008. The Vice Chair for Supervision of the Federal Reserve, Michael Barr, described SVB’s collapse as a “textbook case” suggesting that basic management and supervisory errors carried out by multiple parties led to the failure of a well-established institution. However, the repercussions extended far beyond SVB itself. Its collapse triggered the Panic of 2023, a broader banking crisis that led to the failures of other U.S. institutions, including Signature Bank and First Republic Bank, and contributed to the downfall of Credit Suisse, the largest bank failure in global history. This crisis is another reminder of the persistent vulnerabilities in the banking system. Despite the extensive research, regulation and supervision aimed at guaranteeing the correct functioning of the system and financial stability, banks continue to collapse. These events are highly dangerous, as their adverse effects can impact markets, economies, and, in some cases, the global financial system. The Wall Street Crash of 1929, the Great Depression, and the global financial crisis of 2008, are striking examples of how vulnerabilities within financial institutions can escalate into widespread crises (Hull, 2018). The recurrence of bank collapses reinforces the importance of understanding their root causes, which has gained increasing relevance in recent years. In fact, the 2022 Nobel Prize in Economics was awarded to Ben Bernanke, Philip Dybvig, and Douglas Diamond for their contributions to the study of bank failures and the pivotal role of public trust in ensuring the stability of financial institutions (Bernake, 1983; Diamond & Dybvig, 1983). Despite its peculiarities, the case of SVB becomes a valuable case to teach us about the general case in banking economics, demonstrating how the mismanagement of fundamental financial risks can lead to severe repercussions. Its downfall not only exposed weaknesses within the bank but also stimulated discussions on the effectiveness of risk management, regulation, and crisis response in modern banking. 4 1.2 Objectives The main objective of this study is to analyze the causes behind SVB's collapse, focusing on two key areas: interest rate risk and liquidity risk. This analysis aims to contextualize SVB's failure within banking risk management practices, emphasizing how mismanagement of these risks contributed to its downfall. The specific objectives of this study are: ● To develop a deep understanding of interest rate and liquidity risks. ● To examine the history of Silicon Valley Bank and its trajectory. ● To identify and quantify the interest rate and liquidity risks the bank faced before its collapse, and later assess the management failures that led to its downfall. Beyond its academic purpose, this study also arises from a personal interest in gaining a deeper understanding of the banking sector, an area that, despite its significance, is not explored in depth throughout the degree. I have considered this work as an opportunity to enhance my knowledge of banking operations, analyze the underlying causes of a bank failure, and understand the critical role of effective risk management, particularly in a sector that relies heavily on public trust. Furthermore, this work has allowed me to refine my financial statement analysis skill, a capability I am currently developing in my internship and intend to strengthen further in the future. 1.3 Methodology The methodology of this study combines both a theoretical and practical approach. First, liquidity and interest rate risks are defined, along with their identification, measurement, existing regulations, and management strategies. Next, SVB’s history and collapse are examined, to understand how a bank with an innovative business model and rapid growth ultimately failed. Subsequently, a detailed analysis of its financial statements, with special focus on its balance sheet, as of December 2022 (just months before its collapse) is conducted to assess its financial position and identify major interest and liquidity risk sources. Based on this analysis, these risks are quantified to demonstrate how the bank's vulnerabilities were already evident before the crisis. This examination will allow for a discussion on the shortcomings in risk management by the responsible parties. Finally, the conclusions summarize the key findings and lessons learned from the SVB case. 5 2. Theoretical Framework 2.1. Interest Rate Risk (IRR) 2.1.1. Definition According to the Basel Committee on Banking Supervision (BCBS)1 (2004) of the Bank for International Settlements (BIS)2, interest rate risk refers to “the exposure of a bank’s current and future earnings and capital arising from adverse movements in interest rates”. Financial institutions are especially sensitive to interest rate swings due to the nature of their balance sheets, which include interest-earning assets and interest-bearing liabilities that differ in maturities and in interest rates. Consequently, fluctuations in interest rates can alter the value of most assets and liabilities. Considering that net interest income (NII)3, the primary source of revenue for banks, is directly affected by changes in interest rates, effective management of IRR is essential to ensure banks’ profitability and preserve their economic value. 2.1.2. Main Sources The BCBS (2004) identifies four primary sources from which IRR arises: 1) Repricing Risk: it derives from discrepancies in the timing of interest rate changes and cash flows. Banks are exposed to this risk when they renew the liabilities used to fund their assets, that come due and are renewed at different times. Usually, banks finance long-term, high-yield assets with short-term lower-interest liabilities, which makes them liability-sensitive. As a result, their liabilities reprice faster than assets, exposing them to potential losses if interest rates rise. 2) Yield Curve Risk: it refers to the risk faced by a financial institution due to variations in the slope or the shape of the yield curve4. It results from shifts in the correlation between interest rates at different maturities within a given market or index. 4 The yield curve is the function describing the relationship between interest rate variation and maturity. 3 NII arises from the difference between the interest earned from interest-generating assets, such as loans and securities, and the interest paid on interest-bearing liabilities, such as funds and deposits (Hull, 2018). 2 The BIS is an international financial institution that offers financial services to central banks and supports them in their search for monetary and financial stability through international cooperation. 1 The BCBS is the primary global standard setter for the prudential regulation of banks and provides a forum for regular cooperation on banking supervisory matters. 6 3) Basis Risk: it arises when the relationship between interest rates in different financial markets or instruments changes. This happens because there are many different interest rates in a given currency, which tend to move together but are not perfectly correlated. 4) Options Risk: it emerges when a bank or its client holds options, which are financial instruments that give the right to modify the timing or amount of cash flows associated with an asset, liability, or off-balance-sheet (OBS) instrument. Consequently, the holder of an option has the right to buy or sell a financial asset at a specified price before a certain date, which can be prompted by changes in interest rates. This poses a risk to nearly all banks, which tend to hold financial instruments with embedded options on both their assets and liabilities, such as variable-rate loans with prepayment options or demand deposits. 2.1.3. Measurement In view of the great impact IRR has on banks, precise and prompt measurement of this risk becomes essential for adequate management. The Federal Deposit Insurance Corporation (FDIC) (2024) holds that financial institutions should frequently measure IRR and employ various measurement methods, suitable for the bank’s characteristics, such as its size, complexity and risk profile. This allows evaluating how sensitive a bank’s earnings, assets and liabilities are to interest rates swings. The most widely used methods include: ● Earnings simulation models: also known as earnings-at-risk (EaR) models, forecast future profitability under different scenarios. They measure short-term IRR by evaluating the potential impact of rate changes on the bank’s earnings, typically NII, over a specified period, often one or two years (Board of Governors of the Federal Reserve System, 2023a). ● Gap reports: they focus on the identification of short-term maturity and repricing imbalances between assets and liabilities within a given period. They generally present ratios of rate-sensitive-assets (RSA) to rate-sensitive-liabilities (RSL)5 to determine the bank’s sensitivity. The U.S. Office of the Comptroller of the Currency (OCC)6 (2020) states that a positive gap, or an RSA to RSL ratio above one indicates asset-sensitivity, so that assets reprise faster, a negative gap or an RSA to RSL ratio 6 The OCC, an autonomous bureau within the U.S. Department of the Treasury, is responsible for regulating and supervising “all national banks and federal savings associations as well as federal branches and agencies of foreign banks” (OCC, 2020). 5 RSA (RSL) refers to all the assets (liabilities) that mature or are repriced within the gapping period. 7 below one indicates liability-sensitivity, so that liabilities reprice faster, and a neutral gap or RSA to RSL equal to one indicates a neutral gap or no maturity imbalance. ● Duration Analysis: Macaulay’s duration measures how much weighted average time an investor has to wait to recover the present value of the cash flows of a bond (Hull, 2018). It helps to measure how much the value of an asset or liability would change to a small interest rate shift, which is often measured in basis points7. Macaulay’s duration formula is as follows: , 𝐷=Σ𝑡𝑖𝑣𝑖 𝐵 ( ) where refers to the time, usually expressed in years, in which the cash flow is 𝑡 made, is the present value of the cash flow, and is the market price of the bond. 𝑣 𝐵 The change in the bond’s market price is obtained as: , Δ𝐵 =−𝐷𝐵Δ𝑦 where stands for the shift in the bond’s yield. ∆𝑦 ● Convexity Analysis: similar to duration analysis, convexity measures the sensitivity of a portfolio to interest rate shifts. However, it provides more accurate estimates of bond prices, particularly for larger interest rate changes by considering the non-linear relationship between bond prices and yields (Hull, 2018). The convexity for a bond is: , 𝐶= 1𝐵 𝑑2𝐵 𝑑𝑦2=Σ𝑐𝑖𝑡𝑖2𝑒−𝑦𝑡𝑖 𝐵 where is the bond’s yield measured with continuous compounding and stands for 𝑦𝑐 cash flow. This is the weighted average of the square of the time to the receipt of cash flows. Hull (2018) provides a formula to approximate the change in the bond price combining both Macaulay’s duration and convexity as follows: ∆𝐵 𝐵 = −𝐷∆𝑦+ 12𝐶(∆𝑦)2 7 A basis point is 0.01% per annum. 8 2.2. Liquidity Risk (LR) 2.2.1. Definition Liquidity risk refers to the potential difficulties an entity may encounter in funding asset growth and fulfilling payment obligations, due to cash shortage or inability to convert assets into cash without facing significant losses. The BCBS (2008) holds that banks are subject to LR by nature since their core function is to transform short-term deposits into long-term loans. This mismatch between the maturities of assets and liabilities, along with the uncertainty of certain cash flows, such as deposit withdrawals, loan renewals or new loan requests, heightens LR. Thus, adequate LR management becomes essential to ensure a bank remains liquid and can meet all payment obligations at any time. Moreover, insufficient liquidity can lead to a bank run, a situation where a large number of depositors simultaneously withdraw their funds from a bank because they believe it might fail or become insolvent, and therefore fear not being able to recover their deposits (Iyer & Puri, 2012). This sudden demand can cause solvent8 financial institutions to fail as the bank is unable to make cash payments when they are due. Besides, the problem of one bank can rapidly spread across the entire banking sector, triggering a bank panic. In turn, lack of liquidity can have repercussions on the whole financial system (BCBS, 2008). According to Hull (2018) financial institutions’ liquidity funding problems arise from: ● Liquidity stress in the economy: credit risk concerns can discourage investors from providing funding, as it happened in the financial crisis of 2007. ● Over-reliance on short-term funding to long-term obligations: financial institutions tend to fund their long-term obligations through short-term instruments. These maturity imbalances can bring liquidity issues if not managed correctly. ● Poor financial performance: banks rely on customers’ trust. If customers perceive a high risk of default, their confidence loss may lead to a funding shortage. In fact, banks’ insufficient liquidity levels were one of the reasons that stimulated the economic and financial crisis of 2007. The confidence loss of the market towards the solvency and liquidity of banks impacted not only the banking sector but also the financial system and the global economy (BCBS, 2011). This was a turning point, and since then awareness of the importance of LR and its management has increased and more appropriate regulation has emerged. There are many examples of bank failures due to LR, 8 Solvency refers to the ability of a company to meet its obligations. A company is solvent when its assets exceed liabilities, so that the value of its equity is positive (Hull, 2018). 9 startups to established enterprises10. Figure 1 presents the group’s client funds by client type, proving its high client concentration both on deposits and on funds placed OBS arising from VC activity. Figure 1: SVBFG’s total client funds by client type Notes: Early stage technology, technology, early stage life science/healthcare and life science/ healthcare refer to VC-backed companies. Source: SVB Financial Group (2023). Unlike traditional banks, SVB specialized in supporting high-risk startup companies, which are characterized by unpredictable profitability in their early years, and provided them financial support across their entire lifecycle (Al-Sowaidi & Faour, 2023). This resulted in a high concentration of funds allocated to VC-backed and early-stage companies. Additionally, its pioneering and personalized approach to banking enabled the company to establish strong strategic relationships with the VC and PE firms worldwide, many of which were not only clients but also potential investors in other SVB-backed companies. This network played a crucial role in facilitating growth and investment within the innovation ecosystem, in which SVB acted as a key financial partner to entrepreneurs, innovators and investors. The group provided services to a diverse array of customers across the U.S. and to international customers in key international innovation markets. Nevertheless, SVBFG derived the majority of its revenue from U.S. clients, and about 80% of its workforce was based in the U.S., proof of their strong focus on the domestic market. Between 2019 and 2021, the bank experienced remarkable profits and a substantial rise in deposit percentage. This was due to the rapid growth of the tech industry during COVID-19 pandemic and the economic measures taken to stimulate the economy at the 10 SVB offered three different banking practices aimed at each stage of the life cycle: SVB StartUp Banking for early-stage private companies with annual revenues below $5 million, SVB Early Stage for mid-stage companies, usually venture-funded and with revenues between $5 million and $75 million, and SVB Corporate Banking for mature companies with annual revenues over $75 million. 16 time (Tellez, 2023). The near-zero interest rates during this period, combined with the excess liquidity due to the Fed’s decision to inject $2.3 trillion in loans to help mitigate the effects of the pandemic, pushed investors towards riskier alternatives yielding higher returns such as startups (Al-Sowaidi & Faour, 2023). All this led to increased VC and startup investment in emerging technology companies (Figure 2), which brought a large influx of capital to the banking sector in the form of deposits (Figure 3). SVB made great profits from taking deposits from customers, mostly uninsured11, as seen in Figure 3, and lending them at a higher interest rate. Figure 2: U.S. VC deal activity by quarter 2017-2022 Notes: Deal activity: equity investments in startups. Source: Barr (2023). Figure 3: SVB’s deposits evolution by quarter 2017-2022 Source: Barr (2023). 11 Uninsured deposits are bank deposits exceeding the insurance limits set by a country’s deposit insurance agency. In the United States, the FDIC provides deposit insurance up to $250,000 per depositor at each FDIC-insured bank to protect individuals in the event of a bank failure. 17 Nevertheless, the bank started to face a lending shortage as it received more deposits than it could lend out. To address this, SVB allocated its excess funds primarily into longer-term, held-to-maturity (HTM)12 securities, both mortgage-backed securities and U.S. Treasury bonds, low risk investments that provide a predictable return (Tellez, 2023). In this way, through almost four decades, SVB built a reputation as a cornerstone of the innovation economy and established strong connections with VC and PE firms, portfolio companies of investors, prominent law firms and influential figures in this sector (Nguyen, 2024). In fact, almost half of all U.S. life sciences and technology firms backed by venture capital received financing from SVB, additional proof of the Bank’s link to VC deal activity (SVB Financial Group, 2023). By 2022, SVB was the 16th largest bank in the U.S. based on total assets and had a lot of recognition. Between 2019 and 2023, SVBFG was listed in Forbes’ prestigious annual ranking of “America's Best Banks” for five consecutive years, as well as in “Forbes Financial All-Stars” in 2023. Additionally, the group was named one of the 100 best companies to work for by FORTUNE Magazine. Nevertheless, the Fed's decision in March 2022 to raise interest rates to fight inflation brought severe consequences for the bank and contributed to its collapse. Throughout 2022, the Federal Funds Rate, the interest rate range at which banks lend to one another and a key benchmark for other interest rates, increased to around 4.5% (Kozlowski & Jordan-Wood, 2023). Figure 4 shows the evolution of the Federal Funds Effective Rate between the beginning of 2020 until March 15, 2023. This completely changed the shape of the yield curve, which by the end of the year was nearly flat at around 4% for all maturities, indicating that the term-spread (or the higher yield for longer terms) was eliminated (Metrick, 2024). Higher rates decreased the market value of the company’s investment securities and led to unrealized losses13. Moreover, these higher rates diminished the appeal of riskier investments, reducing clients' interest in funding new companies and accelerating the outflow of deposits (Tellez, 2023). 13 Unrealized losses are potential losses that arise when the market value of a security falls below its purchase price, representing the loss that would be incurred if the security were sold (Barr, 2023). 12 HTM securities consist of securities intended to be held until maturity, so that the bank records them at amortized historical cost. However, if banks decide to sell even a part of them, they have to reclassify all of them as available-for sale (AFS) at market value (Vickery et al., 2015). 18 Figure 4: Federal Funds Effective Rate Evolution by quarter between January 1, 2020 and March 15, 2023 Notes: Units in percentages. Frequency: daily (7-Day). Source: Own elaboration, data from Board of Governors of the Federal Reserve System via FRED. The increase in deposit withdrawals caused liquidity issues for the bank towards its clients. To address this, SVB sold government bonds at a price lower than the purchase price, which turned unrealized losses into realized ones. Although the situation went unnoticed for a while, it turned serious when Moody's Investment Service threatened downgrading SVB’s credit rating by more than one notch due to the Bank’s difficulties to meet depositors' withdrawal requests (Wang, 2023). In view of this, on March 8, 2023, SVBFG announced a restructuring of its balance sheet. “SVBFG had sold $21 billion in available-for-sale (AFS) securities, was booking a $1.8 billion after-tax loss, was planning to increase term borrowings by $15 billion to $30 billion, and was seeking to rise $2.25 billion in capital” (Barr, 2023). The aim was to sell the low-yielding bonds to reinvest the money in assets yielding higher returns, which, along with the sold shares, would offset the incurred losses (Wang, 2023). The following day, panic emerged among uninsured depositors, who interpreted the announcement as a signal of financial distress, which led to a bank run. Withdrawals of uninsured deposits approached $42 billion on March 9th, almost 25% of total deposits, with estimates indicating an additional $100 billion outflow on March 10, nearly depleting the bank’s remaining deposits. According to Barr (2023), the run was sparked by social media and the firm’s concentrated clientele of VC investors and technological firms that withdrew their deposits simultaneously, resulting in a remarkable deposit outflow that accounted for 85% of the bank’s total deposits. In fact, a study conducted by Bales & Burghof (2024) proved how intense social media activity, especially on Twitter and Google, accelerated 19 SVB’s collapse by influencing its stock price and enabling real-time bank run coordination between March 8 and March 10, 2023 as shown in Figure 5. Figure 5: Public reaction to SVB’s restructuring announcement (March 8-10, 2023) Source: Bales & Burghof (2024). SVB collapsed on March 10, 2023, due to insufficient cash to meet the extraordinary and sudden outflows that caused a bank run. That morning, the California Department of Financial Protection and Innovation closed SVB, becoming the fastest bank closure in U.S. banking history, and appointed the FDIC as receiver, which subsequently led to the bankruptcy of SVBFG (Barr, 2023). The regulation and supervision in place to prevent bank failures proved insufficient in averting this outcome. Nevertheless, as previously mentioned, bank failures are rarely isolated events. SVB’s collapse triggered systemic risk and set off the Panic of 2023, leading to the failures of other two regional banks, namely Signature Bank and First Republic Bank, due to similar exposure to uninsured deposits and IRR. The contagion effect caused widespread deposit withdrawals, resulting in their shutdowns on March 12 and May 1, respectively. In an attempt to contain the crisis, regulators invoked the “systemic-risk exception” from the 1991 law, which allowed the FDIC to fully cover uninsured deposits at SVB and Signature. However this measure proved insufficient, and together, these three bank failures represent the largest failures in U.S. history. Ultimately the crisis spread to Europe, culminating in the collapse of Credit Suisse in April 2023, the largest bank failure in global history (Metrick, 2024). 20 3.2. Detecting IRR and LR Sources by Analyzing SVBFG’s Financial Statements 3.2.1. SVBFG’s Balance Sheet By the end of 2022, SVBFG’s balance sheet already presented a risky structure, and the risks associated with it could be spotted. The company held $211.8 billion worth of assets (see Appendix 2 for SVBFG’s balance sheet), consisting of $120.1 billion in investment securities, $73.6 billion in loans, $13.8 billion in cash, and $4.3 billion in other assets. Equity accounted for $16.3 billion, while liabilities amounted to $195.5 billion. Of these liabilities, $173.1 billion were deposits, $13.6 billion were short-term borrowing, $5.4 billion were long-term borrowing and $3.4 billion fell under other liabilities. Figure 6 provides an overview of SVBFG’s balance sheet structure as of December 31, 2022. Figure 6: SVBFG’s Balance Sheet Structure December 31, 2022 Notes: The color gradient represents the liquidity of assets and liabilities, with darker blues indicating illiquid items and lighter shades representing more liquid ones. While loans are generally more illiquid than investment securities, this was not the case for SVB, as explained along this section. Source: Own elaboration, SVB Financial Group (2023). While total assets remained relatively stable, amounting to $211.3 billion in 2021, the changes from one year to the next were primarily driven by shifts within individual asset and 21 liability categories, rather than a significant change in the overall total. These shifts reflect how clients and the bank responded to the changing economic environment throughout 2022, and suggested potential risks for the following year. Hence, analyzing SVBFG’s balance sheet structure will provide an understanding of the company’s financial position at the year-end and the risks it faced prior to its collapse. By examining the evolution of the composition of assets and liabilities, and considering their maturity periods, if known, the main sources of IRR and LR will be identified, which the company could, and should, have identified. For this analysis, data has been obtained from the SVBFG’s 2022 annual report (2022 Annual Report onwards). 3.2.1.1. Liability Structure of SVBFG As previously mentioned, SVBFG’s liabilities were composed of deposits, short-term borrowings, long-term debt and other liabilities. In total, they amounted to $195.5 billion ($194.7 billion in 2021). Table 1 provides a detailed breakdown of the composition of SVBFG’s liabilities and their respective maturities as of December 31, 2022, as well as a comparison to the company’s liabilities as of December 31, 2021. Table 1: SVBFG’s Liabilities (December 31, 2022) (Dollars in millions) Uncertain One year or less More than one year to five years More than five years Total 2022 Total 2021 Deposits $ 166,416 $ 6,682 $ 11 $ 173,109 $ 189,203 ST borrowings $ 13,565 $ 13,565 $ 71 LT debt $ 2,995 $ 2,375 $ 5,370 $ 2,570 Other liabilities $ 3,454 $ 3,454 $ 2,855 Total liabilities $ 166,416 $ 23,701 $ 3,006 $ 2,375 $ 195,498 $ 194,699 Source: Own elaboration, SVB Financial Group (2023). The liability structure of SVBFG presented a high funding concentration, with deposits being the bank’s main source of funding. Despite the notorious deposit outflow experienced during 2022, deposits still accounted for almost 89% of total liabilities by the end of that year, dropping from over 97% in 2021. To compensate for the $16.1 billion decrease in deposits, the company significantly increased its short-term borrowings, by nearly $13.5 billion. While these borrowings, primarily composed of short-term loans, represented just 7% of total liabilities, they became the bank’s second-largest source of financing, surpassing long-term liabilities. This 22 significant increase highlights the bank's efforts to address its liquidity needs and meet its obligations. According to the 2022 Annual Report, the weighted average interest rate on these borrowings was 2.9%. Additionally, a $2.8 billion increase in long-term debt, which comprised senior notes, subordinated debt, and convertible debt with maturities exceeding one year, alongside a $0.6 billion increase in other liabilities, which included various short-term operational payables, fully offset the decline in deposits. All these adjustments collectively led to a slight increase in the company’s total liabilities, which negatively impacted its NII due to higher interest expenses. Focusing on deposits, the bank’s primary source of funding, in 2022, they were composed of $166.4 billion in demand deposits, which were payable on demand, and $6.7 billion in time deposits (commonly known as term deposits), predominantly with a fixed maturities of three months or less. This structure exposed the bank to significant uncertainty regarding the timing of deposit withdrawals, as most of its funding could be required by clients’ on very short notice. This uncertainty created a need for SVB to maintain sufficient liquidity to meet clients’ potential withdrawal demands, making it particularly vulnerable to bank runs and increasing its LR. Moreover, holding such a high proportion of demand deposits increased the bank’s exposure to option risk, a component of IRR. Since depositors could withdraw their funds at any time, fluctuations in interest rates could incentivize early withdrawals, as seen in 2022. Fascione et al. (2024) highlight that digitalization has reduced deposit stability and increased deposit sensitivity to interest rate changes. This trend underscores the need for banks to adapt their liquidity risk management strategies to an environment where withdrawals can occur more rapidly than ever before. By year end, total deposits comprised $80.8 billion in non-interest bearing (down from $125.9 billion in 2021) and $92.4 billion in interest bearing (up from $63.4 billion in 2021). These shifts reflect customers’ reaction to rising interest rates. On the one hand, holders of non-interest-bearing deposits were incentivized to seek yield-generating alternatives, either within the bank by switching to interest-bearing deposits, or externally in the market. On the other hand, assuming the bank raised interest rates on deposits to stay competitive, clients with interest-bearing deposits had motives to retain their funds. This simultaneous increase in interest-bearing deposits and decline in non-interest deposits translated into higher interest expenses to the bank, which negatively impacted its NII. 23 Besides, having a customer base highly concentrated and homogeneous further increased the bank’s exposure to LR and a potential bank run. As SVB’s clients operated in related sectors, the economic and financial conditions affecting one sector simultaneously impacted a large portion of the bank’s deposit base. Therefore, while the growth of the tech sector between 2019 and 2021 contributed to substantial deposit inflows, this reliance also posed significant risk of simultaneous withdrawals in times of financial need, lower tech funding or reduced VCl activity, as it happened in 2022. It is noteworthy that $151.5 billion of all deposits were large enough to be uninsured, making SVBFG the bank with the highest percentage of uninsured deposits among all banks with assets of $50 billion or more (Metrick, 2024). This aggravated the bank’s funding concentration, as most of its funding came from fewer clients with larger deposits. 3.2.1.2. SVBG’s Asset Structure Moving into SVBFG’s assets, the company held cash, loans, investment securities and other assets, amounting to $211.8 billion ($211.3 billion in 2021). Table 2 provides a detailed breakdown of the composition of SVBFG’s assets and their respective maturities as of December 31, 2022, along with a comparison to the company’s assets the year before. Table 2: SVBFG’s Assets (December 31, 2022) (Dollars in millions) Not specified or no maturity One year or less More than one year to five years More than five years to ten years More than ten years Total 2022 Total 2021 Cash $ 13,803 $ 13,803 $ 14,586 Net loans $ -636 $ 42,913 $ 18,251 $ 13,086 $ 73,614 $ 65,854 Investment securities $ 2,664 $ 1,153 $ 15,520 $ 7,441 $ 93,276 $ 120,054 $ 127,959 Other assets $ 375 $ 3,082 $ 865 $ 4,322 $ 2,909 Total assets $ 2,403 $ 60,951 $ 33,771 $ 20,527 $ 94,141 $ 211,793 $ 211,308 Notes: Maturities of cash and other assets have been estimated considering the nature of the assets. Assets with no maturity or not specified maturity include allowance for credit losses in negative sign (classified under net loans), non-marketable securities (classified under investment securities) and goodwill (classified under other assets). Source: Own elaboration, SVB Financial Group (2023). The company’s asset structure was predominantly composed of investment securities, mostly with maturities over ten years, which accounted for 57% of total assets by the end of 2022. Loans, on the other hand, accounted for 35% of total assets. According to 24 Barr (2023), this allocation was notably atypical, as most large banking organizations (LBOs) allocate, on average, 24% of their total assets to investment securities and 58% to loans. Of the $120.1 billion investment securities, as shown in Table 3, $91.3 billion were HTM securities, representing 76% of total securities (almost the double of an average LBO), $26.1 billion were AFS14 securities, which comprised 22% of total securities, and $2.7 billion were non-marketable and other equity securities15 accounting for 2%. Table 3: SVBFG’s Investment Securities (December 31, 2022) (Dollars in millions) Not specified or no maturity One year or less More than one year to five years More than five years to ten years More than ten years Total 2022 Total 2021 AFS $ 1,084 $ 14,784 $ 2,963 $ 7,238 $ 26,069 $ 27,221 HTM $ 69 $ 736 $ 4,478 $ 86,038 $ 91,321 $ 98,195 Non-mark. $ 2,664 $ 2,664 $ 2,543 Investment securities $ 2,664 $ 1,153 $ 15,520 $ 7,441 $ 93,276 $ 120,054 $ 127,959 Notes: Non-mark.: non-marketable and other equity securities. AFS securities at fair value, HTM securities at amortized cost. Source: Own elaboration, SVB Financial Group (2023). As previously explained, although SVB’s primary activities were deposit intake and loan issuance, the excess liquidity generated by the high volume of deposits between 2019 and 2021, combined with the relatively weaker lending activity, led the bank to invest its funds in long-term HTM securities. This strategy aimed to generate returns by investing in securities traditionally considered low-risk, as their nominal value is recovered at maturity and they tend to provide regular and stable cash flows, and because most of them were issued by the U.S. government, so they posed low credit risk. Yet, holding such a high share of these instruments exposed the bank to both significant IRR and LR, since securities with large maturities are highly sensitive to rate fluctuations. Meanwhile, most loans were short-term credit lines, primarily granted to PE and VC firms that need financing before receiving capital contributions from their investors. In contrast, the company extended very few commercial or residential mortgages. Besides, 15 Non-marketable securities are not tradeable and equity securities do not mature (Vickery et al., 2015). 14 AFS securities are flexible securities that the bank may either sell or retain for long periods, and since they are accounted for at market price, they are recorded at fair price in the balance sheet. (Vickery et al., 2015). 25 proportional increase in asset income, negatively impacting profitability. This negative effect would have intensified in the intermediate term, with a $98.40 million decrease in NII, as the negative accumulated gap continued to grow. This evidences the bank’s vulnerability to rising rates, as liabilities would have been refinanced at higher costs, while asset income would not have been sufficient to compensate for this. In contrast, in the long term, the positive accumulated gap would have led to a $13.89 million increase in NII, as long-term assets exceeded liabilities, so that interest income would have outweighed the higher funding cost. However, this benefit would have been limited because many of these assets were fixed income, reducing the bank’s ability to fully capture the rate increase. Nevertheless, the bank’s financial problems and lack of liquidity led to its collapse before it could benefit from the long-term reversal. Given SVB's significant maturity mismatch and exposure to interest rate risk, Golding & Lucas (2023) argue that periodic disclosure of the duration gap should be required for all medium and large banks to enhance regulatory and market oversight. They defend that standardized disclosures would allow early detection of emerging risks, helping to prevent crises like SVB’s. Additionally, they propose linking capital requirements to duration gap levels to discourage excessive interest rate exposure, which could have provided an early warning signal in SVB’s case. 3.3.2. Duration Analysis Since SVB held a large proportion of its assets in investment securities, conducting a duration analysis allows quantifying the impact of small basis point increases in interest rates on these securities’ value and, consequently, on the bank’s net worth. The 2022 Annual Report already provides the weighted average duration for both the AFS and HTM securities portfolios, which corresponds to the Macaulay duration. Since AFS securities’ duration is 3.6, and HTM securities’ duration is 6.2, the estimated change in market value due to a 0.1% (10 basis points) increase in interest rates is as follows: Δ𝐴𝐹𝑆 =−3.6*26,069*0.001=−$93.85 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 Δ𝐻𝑇𝑀 =−6.2*91,321*0.001=−$566.19 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 𝑇𝑜𝑡𝑎𝑙 𝑎𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝑢𝑛𝑟𝑒𝑎𝑙𝑖𝑧𝑒𝑑 𝑙𝑜𝑠𝑠𝑒𝑠 =−(93.85+566.19)=− $660.04 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 This indicates that a 0.1% rise in interest rates would have caused almost a $94 million decrease in the market value of the AFS securities portfolio and around a $566 million decrease in the HTM securities portfolio. In other words, the market price of AFS 32 securities would have dropped to around $25,975 million, while HTM securities would have declined to $90,755 million, leading to a total of $660 million in additional unrealized losses. By year-end 2022, SVB already reported $17.7 billion in unrealized losses on its securities portfolio (as mentioned in Section 3.2.1.2), or concretely $17,699 million, bringing the total unrealized losses to $18,350 million after factoring in the additional losses. Given that SVB’s equity stood at $16,295 million, these losses would have exceeded the bank’s capital base. Notably, only the unrealized losses from AFS securities would have been reflected on the balance sheet, adjusting reported equity to $16,201 million. However, if the bank had been forced to sell its entire securities portfolio (as ultimately happened), both AFS and HTM losses would have been realized, making it critical for SVB to have sufficient equity to absorb them. Nevertheless, this duration analysis provides a simplified estimation based on a 0.1% rate increase. To assess SVB’s actual exposure more accurately, it is essential to consider the 24-basis-point increase (0.24 p.p.) in the Fed Funds Rate from 4.33% to 4.57% between January 1, 2023, and March 8, 2023 (the day SVB announced its balance sheet restructuring) (Board of Governors of the Federal Reserve System, n.d.). Under this scenario, assuming the bank maintained its securities holdings, the additional unrealized losses would be: Δ𝐴𝐹𝑆 =−3.6*26,069*0.0024=−$ 225.24 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 Δ𝐻𝑇𝑀 =−6.2*91,321*0.0024=−$1,358.86 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 𝑇𝑜𝑡𝑎𝑙 𝑎𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝑢𝑛𝑟𝑒𝑎𝑙𝑖𝑧𝑒𝑑 𝑙𝑜𝑠𝑠𝑒𝑠 =−(225.24+1,358.86)=−$1,584.10 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 As a result, the total unrealized losses would have increased to approximately $19,283 million ($17,699 million + $1,584 million), further highlighting SVB’s extreme vulnerability to interest rate movements. Given that the bank’s total equity was only $16,295 million, this meant that potential losses had further exceeded its capital base, reinforcing depositors' concerns about SVB’s solvency and triggering the bank run. Had SVB been able to hold its investment securities until maturity, it might have avoided failure. However, this scenario was unlikely, as unrealized losses had already surpassed its equity, making it increasingly difficult to restore confidence and maintain liquidity. 33 3.4. IRR and LR Management Errors The main problem that contributed to the collapse was the poor management of IRR and LR across all four lines of defense, as mentioned in the beginning of this study. On the first line, many people, such as OOnagh McDonald (2023), former British Member of Parliament, highlight SVB Board’s lack of financial and banking services knowledge and experience at accepting the risky and concentrated business model. Besides, at the operational level, the company focused on short-term profitability rather than ensuring long-term stability. Decisions such as over-reliance on HTM securities with long maturities, or closing out risk hedges when interest rates were high to make short-term profits, instead of holding them to mitigate potential losses, exposed the bank to significant risk. Furthermore, the second line of defense, consisting of risk management and internal control, also failed to properly manage IRR. Firstly, from April 2022 to January 2023, the company did not have a Chief Risk Officer, which further hindered the oversight of both IRR and LR. Besides, according to the Fed, the metrics SVB used to assess IRR were basic and mostly oriented towards NII variations (Barr, 2023). Therefore, they only contemplated risk in the short-term, and did not consider the impact on the economic value of equity, or the long-term. Regarding LR, the company failed its internal liquidity tests but took no action, and had no contingency funding plan. Instead of addressing the problems and finding a solution, they resorted to more relaxed stress tests to obtain better results and create a false sense of security. Additionally, the third line of defense proved to be very weak. The Fed admitted that SVB’s internal audit failed to hold management accountable for poor risk management, despite clear signs of an ineffective risk management program (Barr, 2023). This resulted in insufficient independent assurance regarding the effectiveness of risk management, governance, and internal controls. Besides, the audit function did not challenge management’s assumptions, allowing risky decisions to persist unchecked. Finally, external oversight of SVBFG proved inadequate, as regulators failed to detect and act upon SVB’s IRR and LR vulnerabilities and managerial weaknesses in a timely manner (Barr, 2023). SVB was supervised by three agencies, namely the California Department of Financial Protection and Innovation, the Federal Reserve Bank of San Francisco, and the FDIC as the backup federal regulator, and they all failed (Metrick, 2024). As the bank expanded rapidly, supervisors underestimated its vulnerabilities, keeping relaxed capital and liquidity requirements under the EGRRCPA. Despite rising risks, SVB continued to be rated as well-managed, delaying stricter oversight. Even when deficiencies 34 in interest rate and liquidity risk management were identified, regulators took little action and issued no formal findings (Barr, 2023). Additionally, the regulatory framework lacked clear guidance on IRR, allowing banks to ignore unrealized losses, and the EGRRCPA’s relaxed standards hindered oversight by exempting SVB from stricter requirements, like computing the LCR, making supervisors less assertive in enforcing corrections. In conclusion, SVB’s collapse was not only a result of poor internal risk management but also a failure of regulatory oversight. While management made decisions that heightened its exposure to IRR and LR, supervisors failed to intervene effectively, and regulatory policies allowed significant vulnerabilities to persist. This combination of internal mismanagement and external supervisory weaknesses created the conditions that ultimately led to SVB’s downfall. 4. Conclusions In conclusion, the case of SVB demonstrates how a combination of foreseeable factors can lead to a major crisis when mismanaged. Its balance sheet reflected a structure highly exposed to LR and IRR, both of which were easily identifiable and quantifiable. Even with simple metrics like those used in this study (far less sophisticated than those employed by banks), it has been shown that, by the end of 2022, it was already evident that the institution would face serious liquidity issues, largely due to its high exposure to IRR in a rising-rate environment. Furthermore, its business model, characterized by a highly concentrated client base, further amplified its vulnerability. The interconnectedness and rapid response of SVB’s clients, fueled by social media, and combined with predominantly uninsured deposits, facilitated the spread of panic once the bank’s problems became public. This chain reaction accelerated the liquidity crisis, forcing SVB to sell assets at significant losses and leaving it with no flexibility to respond. Although SVB’s investments were concentrated in low-risk assets, its investment strategy did not align with the reality of its liability structure, which was primarily composed of volatile, short-term, or uncertain-maturity deposits. The mismatch between assets and liabilities, combined with a high concentration in both funding sources and investments, as well as in its customer base, created the perfect conditions for the crisis. Consequently, as interest rates rose, the value of its investments declined far more than expected; when clients reacted, withdrawals multiplied; and, lacking flexibility, the bank was unable to withstand the liquidity crisis without incurring massive losses. 35 SVB's collapse also reveals failures across the four lines of defense. The first line allowed an investment strategy misaligned with the bank’s funding structure. The second failed to identify and quantify risks in a timely manner or implement effective mitigation measures. Internal audit did not exercise sufficient oversight over risk management, and external supervision neither detected nor demanded timely corrective actions. This combination of deficiencies allowed manageable issues to escalate into a large-scale crisis. Moreover, the existing regulatory framework proved inadequate for an atypical institution like SVB, highlighting the need for both supervision and regulation to adapt to the constantly evolving banking system. As riskier, non-traditional banks emerge, current oversight has repeatedly fallen short in preventing collapses. Meanwhile, regulatory responses, such as bailouts, have reinforced the too big to fail perception, potentially undermining financial stability in the long run. This case underscores the importance of prudent management of IRR and LR, as well as the need to diversify both funding sources and the customer base. It also reveals the significance of a well-designed investment strategy that not only seeks profitability but also accounts for potential risks and adapts to the reality of the business. In a sector as vulnerable as banking, where maturity mismatches are an inherent characteristic, having effective mechanisms to identify and manage risks is crucial to preventing uncontrollable crises. SVB’s collapse further evidences that the stability of the financial system depends not only on the individual decisions of each bank but also on the robustness of their internal controls and the effectiveness of regulation and supervision. When these fail collectively, even solvent institutions can fail due to a crisis of confidence with systemic consequences. 5. Reflection on the Work Done The analysis of SVB’s collapse provides insight into the crucial role of financial stability in a democratic society and its direct link to sustainable development. A well-functioning banking system supports economic growth, public trust, and institutional transparency. This study aligns with several Sustainable Development Goals (SDGs), particularly SDG 16: Peace, Justice, and Strong Institutions, SDG 8: Decent Work and Economic Growth, SDG 9: Industry, Innovation, and Infrastructure, and even SDG 3: Good Health and Well-being. 36 SVB played a key role in financing startups and innovative industries (SDG 9), fostering entrepreneurship and innovation. Many of its clients belonged to the life sciences sector, contributing to advancements in healthcare and medical research (SDG 3). The bank’s failure disrupted funding for biotech firms and health startups, posing risks to innovation in medical treatments and technologies. Moreover, its collapse exposed critical weaknesses in risk management and regulatory oversight, threatening financial stability and economic growth (SDG 8 and SDG 9), and reinforcing the need for robust institutions and transparent governance (SDG 16). From a democratic perspective, SVB’s case underscores the need for financial transparency, regulatory accountability and responsible banking practices (SDG 16). A well-regulated banking system is essential not only for protecting depositors but also for ensuring economic stability and preventing crises that could hinder innovation, job creation, and social progress (SDG 8 and SDG 9). 37 6. References Al-Sowaidi, A. S. S., & Faour, A. M. W. (2023). Causes and consequences of the Silicon Valley Bank collapse: Examining the interplay between management missteps and the Federal Reserve's floundering decisions. Journal of World Economic Research, 12(1), 38-46. https://doi.org/10.11648/j.jwer.20231201.15 Bales, S., & Burghof, H.-P. (2024). Public attention, sentiment and the default of Silicon Valley Bank. The North American Journal of Economics and Finance, 69(A), 102026. https://doi.org/10.1016/j.najef.2023.102026 Barr, M. (2023). Review of the Federal Reserve’s supervision and regulation of Silicon Valley Bank. Board of Governors of the Federal Reserve System. Basel Committee on Banking Supervision. (2004). Principles for the management and supervision of interest rate risk. Bank for International Settlements. https://www.bis.org/publ/bcbs108.pdf Basel Committee on Banking Supervision. (2008). Principles for sound liquidity risk management and supervision (BCBS 144). Bank for International Settlements. https://www.bis.org/publ/bcbs144.pdf Basel Committee on Banking Supervision. (2011). Basel III: A global regulatory framework for more resilient banks and banking systems (revised June 2011). Bank for International Settlements. https://www.bis.org/bcbs/basel3.htm Basel Committee on Banking Supervision. (2013). Basel III: The Liquidity Coverage Ratio and liquidity risk monitoring tools. Bank for International Settlements. https://www.bis.org/publ/bcbs238.pdf Bernanke, B. S. (1983). Nonmonetary effects of the Financial Collapse. AmericanReview, 73, 257-276. Board of Governors of the Federal Reserve System. (n.d.). Federal Funds Effective Rate [DFF]. Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/DFF Board of Governors of the Federal Reserve System (2014). Regulation YY: Enhanced prudential standards for bank holding companies and foreign banking organizations. https://www.federalreserve.gov 38 Board of Governors of the Federal Reserve System. (2023a). Commercial bank examination manual. https://www.federalreserve.gov/publications/files/cbem.pdf Board of Governors of the Federal Reserve System. (2023b). Supervision and regulation report (May 2023). https://www.federalreserve.gov/publications/files/202305-supervision-and-regulation-r eport.pdf Diamond, D. W., & Dybvig, P. H. (1983). Bank runs, deposit insurance, and liquidity. Journal of political economy, 91(3), 401-419. Dodd-Frank Wall Street Reform and Consumer Protection Act, 12 U.S.C. § 5301 (2010). Economic Growth, Regulatory Relief, and Consumer Protection Act, Pub. L. No. 115-174, 132 Stat. 1296 (2018). Fascione, L., Oosterhek, K., Scheubel, B., Stracca, L., & Wildmann, N. (2024). Keep calm, but watch the outliers: deposit flows in recent crisis episodes and beyond. ECB Occasional Paper, (2024/361). Federal Deposit Insurance Corporation. (2024). Risk management manual of examination policies. https://www.fdic.gov/resources/supervision-and-examinations/examination-policies-m anual/risk-management-manual-complete.pdf Federal Reserve. (2024). 2024 Federal Reserve stress test results. Board of Governors of the Federal Reserve System. https://www.federalreserve.gov/publications/files/2024-dfast-results-20240626.pdf Golding, E. L., & Lucas, D. J. (2023). Duration gap disclosure: A modest proposal to prevent another SVB. Shadow Open Market Committee. Hull, J. C. (2018). Risk management and financial institutions (5th ed.). John Wiley & Sons. Iyer, R., & Puri, M. (2012). Understanding Bank Runs: The Importance of Depositor-Bank Relationships and Networks. The American Economic Review, 102(4), 1414–1445. Kozlowski, J., & Jordan-Wood, S. (2023). The many interest rates in 2022. Federal Reserve Bank of St. Louis. https://www.stlouisfed.org/on-the-economy/2023/jan/many-interest-rates-2022#:~:text =Throughout%202022%2C%20the%20Federal%20Open,%25%20to%204.25%25%2 D4.5%25 39 McDonald, O. (2023). Further reflections on the collapse of the Silicon Valley Bank. Journal of Applied Corporate Finance, 35(1), 37–41. https://doi.org/10.1111/jacf.12569 Metrick, A. (2024). The Failure of Silicon Valley Bank and the Panic of 2023. Journal of Economic Perspectives, 38 (1): 133–52. Nguyen, X. T. (2024). Silicon Valley Bank: the rise and fall of a community bank for tech. Cambridge University Press. Office of the Comptroller of the Currency (OCC). (2020). Interest rate risk. U.S. Department of the Treasury. https://www.occ.gov/publications-and-resources/publications/comptrollers-handbook/f iles/interest-rate-risk/index-interest-rate-risk.html SVB Financial Group. (2023). Form 10-K: Annual report pursuant to section 13 or 15(d) of the Securities Exchange Act of 1934 for the fiscal year ended December 31, 2022. U.S. Securities and Exchange Commission. https://www.sec.gov/Archives/edgar/data/719739/000071973923000021/sivb-202212 31.htm Tellez, A. (2023, March 14). Coinbase, Circle, Paxos: Here are the major firms with funds tied up in SVB and Signature Bank. Forbes. https://www.forbes.com/sites/anthonytellez/2023/03/13/coinbase-circle-paxos-here-ar e-the-major-firms-with-funds-tied-up-in-svb-and-signature-bank/ Tobin, M., & Miller, H. (2023). Silicon Valley Bank Was Practically Everything to Tech Industry: What to Know. Bloomberg. https://www.bloomberg.com/news/articles/2023-03-10/silicon-valley-bank-the-investor -lender-networker-of-startups Vickery, J., Deng, A., & Sullivan, T. (2015). Available-for-sale? Understanding bank securities portfolios. Liberty Street Economics. Federal Reserve Bank of New York. https://libertystreeteconomics.newyorkfed.org/2015/02/available-for-sale-understandi ng-bank-securities-portfolios/ Wang, E. (2023). Silicon Valley Bank’s demise began with downgrade threat. Reuters. https://www.reuters.com/markets/us/silicon-valley-banks-demise-began-with-downgra de-threat-sources-2023-03-11/ 40 7. Appendix Appendix 1: Bank category applicable regulations and risk management requirements Bank category Total Asset Range Key Applicable Regulations Main Risk Management Requirements U.S. domestic firms (2022 Q4) Category I Globally Systemically Important Banks (G-SIBs) $700B in total ≥ assets or $75B ≥ in cross-border activity - Dodd-Frank Act - Regulation YY - Basel III - EPS under Fed/OCC/FDIC - Annual stress tests - Additional capital buffer for GSIBs - Intensive systemic risk supervision - Strict liquidity requirements (LCR, NSFR) - Resolution planning - Bank of America - Bank of New York Mellon - Citigroup - Goldman Sachs - JPMorgan Chase - Morgan Stanley - State Street - Wells Fargo Category II $700B in total ≥ assets or $75B ≥ in certain exposures - Dodd-Frank Act - Amendments under EGRRCPA - Regulation YY - Biennial stress tests - Full LCR and NSFR compliance - Intensive liquidity and capital supervision - Simplified resolution plans - Northern Trust Category III $250B in total ≥ assets or $75B ≥ in specific risk indicators (funding, off-balance-sheet exposures, etc.) - Dodd-Frank Act - EGRRCPA - Regulation YY - Biennial stress tests (severely adverse scenario required) - Partial LCR and NSFR compliance (50%) - Lighter supervision compared to Categories I and II - Capital One - Charles Schwab - PNC Financial - Truist Financial - U.S. Bancorp Category IV $100B in total ≥ assets; does not meet criteria for Categories I, II, or III - Dodd-Frank Act - EGRRCPA - Regulation YY - Biennial stress tests for severely adverse scenarios - No mandatory LCR or NSFR, but basic liquidity management and contingency planning requirements - More limited capital and liquidity oversight compared to higher categories - SVB Financial - Ally Financial - American Express - Citizens Financial - Discover - Fifth Third - First Citizens - Huntington KeyCorp - M&T Bank - Regions Financial Banks with < $100B < $100B in total assets - EGRRCPA - Specific state or federal regulations depending on the institution type (FDIC or OCC) - Exempt from EPS* - Standard supervision (adequate capital, basic risk management, etc.) - Not required to conduct stress tests (although some institutions may perform internal testing) Notes: EPS: Enhanced Prudential Standards. Regulatory requirements under the Dodd-Frank Act. Source: Own elaboration with data from Dodd-Frank Act, Regulation YY, Basel III, EGRRCPA and Federal Reserve Supervision and Regulation Report May 2023. 41