SILICON VALLEY BANK: BARGAIN BUY OR A BANKRUPT?
CASE STUDY SOLUTION
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SYNOPSIS
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On March 8, 2023, Silicon Valley Bank (SVB) disclosed its plans to raise USD 2.25 billion2 to seal a hole in
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its balance sheet from an unsuccessful sale of a fixed-income portfolio that had reportedly resulted in
substantial losses. This unexpected move triggered a massive withdrawal of deposits, especially by technology
and venture capital firms. The liquidity problem was expected to leave losses amounting to USD 20 billion.
Andrew, a fund manager at a US investment firm, intended to examine the level of financial distress in SVB
and identify the possibility of recovery. Andrew’s clients believed that SVB could still be a good buy at the
n
current valuation. However, the risk of failure was also large, and the bank could go bankrupt if no corrective
tio
action was taken in time. Andrew decided to identify abnormalities in SVB’s financials and to estimate the
possibility of SVB’s bankruptcy using the probability of financial distress (PFD) model. Upon analysis,
Andrew found various issues like liquidity risk, interest rate risk, and governance failures in the bank. Further,
lu
the PFD analysis disclosed that the bank had a high chance of bankruptcy.
So
OBJECTIVES
• Understand the various risks prominent in banks.
• Examine the bank’s operations and financials to identify potential risks.
• Understand the application of the PFD model to estimate the solvency level of a bank.
• Estimate the possibility of SVB’s bankruptcy using the PFD model.
The Case Solution Starts From page 5
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ASSIGNMENT QUESTIONS
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1. Discuss the various risks prominent in banks.
2. Examine the risks that SVB faced that are evident in its business operations and financials.
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3. Explain the need for distress prediction models in banks and discuss the significance of the PFD model.
4. Estimate the possibility of SVB’s bankruptcy using the PFD model.
So
The Case Solution Starts From page 5
,ANALYSIS
1. Discuss the various risks prominent in banks.
Risk management is a systematic and continuous process that involves the identification and assessment of
risks followed by prioritization and mitigation to achieve organizational goals. Since banks are in the
business of managing others’ money, sound risk management is an integral part of their activity and the
primary factor in gaining customers’ trust.
For effective risk management banks need to have fundamental systems in place that should be competent
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to identify, measure, monitor, control, and report their risk exposures. The following are the prominent risks
that banks usually face:
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• Asset-liability mismatch risk refers to a situation when a bank’s assets and liabilities have different
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maturity periods or varied cash flow patterns. If a bank utilizes its short-term deposits (liabilities) to
fund long-term loans (assets), it results in asset-liability mismatch. When these short-term deposits are
Sa
due for payment upon maturity, the bank might not be able to repay them since these funds were given
as long-term loans to borrowers, leading to liquidity and interest rate risk for banks. Upon the maturity
of the short-term deposits, the bank might be forced to redeem its long-term assets at a loss, especially
in the case of an increasing interest rate scenario.
• Interest rate risk refers to the impact of interest rate changes on the market value of a bank’s investments. If
n
tio
lu
So
The Case Solution Starts From page 5
, EXHIBIT -1: ESTIMATION OF THE PFD (USD IN MILLIONS)
NIMTAAVG = NET INCOME TO MARKET TOTAL AVERAGE ASSETS*
Latest 2nd Latest 3rd Latest 4th Latest
Dec-22 Sep-22 Jun-22 Mar-22
Net income 305.00 418.00 353.00 533.00
Equity 16,295.00 15,810.00 16,276.00 16,360.00
Total liabilities 195,498.00 197,057.00 198,113.00 203,995.00
NIMTA 0.00144 0.00196 0.00165 0.00242
Weights 0.5333 0.2666 0.1333 0.0666
0.0007680 0.0005235 0.0002195 0.0001611
NIMTAAVG 0.001672089
TOTAL LIABILITIES TO MARKET TOTAL ASSETS (TLMTA)
e
pl
CASH TO MARKET TOTAL ASSETS (CASHMTA)
m
Sa
EXRETAVG = EXCESS RETURN COMPARED TO THE BENCHMARK INDEX (NIFTY 50)
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tio
lu
So
SIGMA = STANDARD DEVIATION OF DAILY RETURNS OVER THE PAST THREE MONTHS
The Case Solution Starts From page 5
CASE STUDY SOLUTION
e
pl
SYNOPSIS
m
On March 8, 2023, Silicon Valley Bank (SVB) disclosed its plans to raise USD 2.25 billion2 to seal a hole in
Sa
its balance sheet from an unsuccessful sale of a fixed-income portfolio that had reportedly resulted in
substantial losses. This unexpected move triggered a massive withdrawal of deposits, especially by technology
and venture capital firms. The liquidity problem was expected to leave losses amounting to USD 20 billion.
Andrew, a fund manager at a US investment firm, intended to examine the level of financial distress in SVB
and identify the possibility of recovery. Andrew’s clients believed that SVB could still be a good buy at the
n
current valuation. However, the risk of failure was also large, and the bank could go bankrupt if no corrective
tio
action was taken in time. Andrew decided to identify abnormalities in SVB’s financials and to estimate the
possibility of SVB’s bankruptcy using the probability of financial distress (PFD) model. Upon analysis,
Andrew found various issues like liquidity risk, interest rate risk, and governance failures in the bank. Further,
lu
the PFD analysis disclosed that the bank had a high chance of bankruptcy.
So
OBJECTIVES
• Understand the various risks prominent in banks.
• Examine the bank’s operations and financials to identify potential risks.
• Understand the application of the PFD model to estimate the solvency level of a bank.
• Estimate the possibility of SVB’s bankruptcy using the PFD model.
The Case Solution Starts From page 5
, e
pl
m
Sa
n
ASSIGNMENT QUESTIONS
tio
1. Discuss the various risks prominent in banks.
2. Examine the risks that SVB faced that are evident in its business operations and financials.
lu
3. Explain the need for distress prediction models in banks and discuss the significance of the PFD model.
4. Estimate the possibility of SVB’s bankruptcy using the PFD model.
So
The Case Solution Starts From page 5
,ANALYSIS
1. Discuss the various risks prominent in banks.
Risk management is a systematic and continuous process that involves the identification and assessment of
risks followed by prioritization and mitigation to achieve organizational goals. Since banks are in the
business of managing others’ money, sound risk management is an integral part of their activity and the
primary factor in gaining customers’ trust.
For effective risk management banks need to have fundamental systems in place that should be competent
e
to identify, measure, monitor, control, and report their risk exposures. The following are the prominent risks
that banks usually face:
pl
• Asset-liability mismatch risk refers to a situation when a bank’s assets and liabilities have different
m
maturity periods or varied cash flow patterns. If a bank utilizes its short-term deposits (liabilities) to
fund long-term loans (assets), it results in asset-liability mismatch. When these short-term deposits are
Sa
due for payment upon maturity, the bank might not be able to repay them since these funds were given
as long-term loans to borrowers, leading to liquidity and interest rate risk for banks. Upon the maturity
of the short-term deposits, the bank might be forced to redeem its long-term assets at a loss, especially
in the case of an increasing interest rate scenario.
• Interest rate risk refers to the impact of interest rate changes on the market value of a bank’s investments. If
n
tio
lu
So
The Case Solution Starts From page 5
, EXHIBIT -1: ESTIMATION OF THE PFD (USD IN MILLIONS)
NIMTAAVG = NET INCOME TO MARKET TOTAL AVERAGE ASSETS*
Latest 2nd Latest 3rd Latest 4th Latest
Dec-22 Sep-22 Jun-22 Mar-22
Net income 305.00 418.00 353.00 533.00
Equity 16,295.00 15,810.00 16,276.00 16,360.00
Total liabilities 195,498.00 197,057.00 198,113.00 203,995.00
NIMTA 0.00144 0.00196 0.00165 0.00242
Weights 0.5333 0.2666 0.1333 0.0666
0.0007680 0.0005235 0.0002195 0.0001611
NIMTAAVG 0.001672089
TOTAL LIABILITIES TO MARKET TOTAL ASSETS (TLMTA)
e
pl
CASH TO MARKET TOTAL ASSETS (CASHMTA)
m
Sa
EXRETAVG = EXCESS RETURN COMPARED TO THE BENCHMARK INDEX (NIFTY 50)
n
tio
lu
So
SIGMA = STANDARD DEVIATION OF DAILY RETURNS OVER THE PAST THREE MONTHS
The Case Solution Starts From page 5
