Country and sovereign risk: when a government interrupts payment

Country risk adds a layer beyond the individual borrower’s credit quality. A foreign company may be willing and financially able to pay, yet its government may restrict foreign-currency transfers or block debt payments. The foreign lender then faces an interrupted cash flow even though the company itself was not the original source of the problem.

Sovereign risk concerns a government’s own obligations or actions. The lecture groups it with country risk because both can affect cross-border recovery. Do not collapse the two mechanisms: a sovereign’s default on its own bonds is different from a transfer restriction preventing a private company from paying an external lender.

The source contrasts this with ordinary domestic recourse. Cross-border enforcement and collection can be more complex, and the usual domestic route may not be available in the same way. This should not be read as a universal legal claim that no remedy ever exists. The slide identifies lenders’ influence over future funding as one bargaining channel: a country’s future access to finance may depend on its treatment of existing claims. That influence is not a guarantee of recovery.

The three historical examples are Argentina in 2001, with roughly $130 billion of government debt default; Greece in 2012, with a stated 53.5% loss on a $265 billion bondholder position; and Russia in 1998, with default on short-term government bonds. These are the lecture’s historical figures, not current country assessments.

If the Greece percentage is applied literally to the same $265 billion base, the implied reduction is 265×0.535=$141.775 billion, leaving 265×0.465=$123.225 billion. This arithmetic explains the stated figures; the source does not specify whether its loss measure is a face-value haircut or a present-value loss. Actual restructuring comparisons require that distinction.

Credit Default Swap: read the sovereign five-year map

The handwritten annotation expands CDS as Credit Default Swap. A protection buyer pays a premium; the protection seller undertakes a contractually specified payment if a defined credit event occurs. It transfers a particular credit-event exposure rather than making the underlying borrower incapable of default. The protection seller and the contract itself can also introduce counterparty and settlement risks.

The map is labeled Sovereign 5 Y CDS. Five years is the contract tenor; it does not by itself tell you the horizon or method of any separately displayed probability estimate. The screenshot is timestamped 6 October 2026,1:47 GMT+0. It is a fixed historical page in the course, not a live market monitor.

The legend divides quoted spreads into up to 100 bp, up to 300 bp and above 300 bp. Green marks the lower bucket, yellow the intermediate bucket and red the higher bucket. In the source, Russia and Egypt are red; Brazil, South Africa and Türkiye are in the intermediate color. Uncolored regions cannot be interpreted as zero risk: this screenshot does not establish whether they lack data or lie outside its displayed coverage.

A spread is a price of protection, not itself a default probability. Higher expected credit loss can raise it, but recovery assumptions, liquidity, risk premia and contract conditions also matter. The following table lets you distinguish the spread level from its recent change, a credit rating and the site’s displayed PD estimate.

The October 2026 CDS table: all visible rows

The table’s columns are country, S& P rating, five-year CDS spread in basis points, one-month percentage change, six-month percentage change, displayed PD(*), and row date. The row dates are 4–6 October within the October 2026 screenshot. The numbers are preserved below as source evidence, not as up-to-date market quotations.

The PD asterisk refers to a footnote that is not visible on the source page. Therefore its precise horizon, recovery assumption and estimation method cannot be verified from the supplied image. We retain the label displayed PD, not “known probability of default.” The spread and PD columns must not be equated.

The rating is a categorical assessment, while the CDS is a market price. They need not order every country identically. A percentage change also needs its starting level: a spread rising from 10 to 20 bp has doubled, yet remains below a 300 bp spread. For example, France’s+136.70% monthly change does not mean its spread level is 136.70 bp or that its default probability rose 136.70 percentage points.

Türkiye’s source row is BB−,255.69 bp,+16.92% over one month,−8.54% over six months, displayed PD 4.26%, dated 6 October. The different signs simply mean the current spread is higher than one month earlier but lower than six months earlier. Ireland’s six-month figure is +25.43%; preserve the plus sign when comparing trends.

The extreme Russia row shows 13,775.17 bp and displayed PD 100%. Do not extend a simple linear spread-to-probability shortcut to that distressed quote. The screenshot supplies no methodology, liquidity or settlement detail sufficient to turn that row into a reliable independent probability calculation.

From basis points to a protection premium

One basis point is 0.0001 as a decimal rate. To convert a spread in basis points to an annual percentage, divide by 100; to use it in a money calculation, divide by 10,000. Thus 255.69 bp corresponds to 2.5569% or 0.025569. Switzerland’s 8 bp is 0.08%, and Egypt’s 328.03 bp is 3.2803%.

For an illustrative 10-million notional, a simple annualized premium calculation at Türkiye’s source spread is 10,000,000×255.69/10,000=255,690 per year. The currency is the contract’s notional currency. This is an educational approximation before payment schedules, accrued premium, upfront charges and other contract conventions; the source does not provide a full traded CDS pricing model.

A higher premium means protection is more expensive. It does not directly state how much the sovereign will pay on its bonds, the bond’s coupon, or the probability of default. Converting the spread to a probability requires assumptions about expected recovery, timing, discounting and risk pricing. The five-year tenor alone does not supply those missing assumptions.

An exam answer should therefore separate three operations: identify the quote unit, calculate a simple premium if instructed, and state the limits of inference. The source table is useful for comparing historical protection prices, but not for making a current trading recommendation.

Technology and operational risk: scale is not scope

The source uses the BIS/Basel operational-risk concept: losses can result from inadequate or failed internal processes, people or systems, or from external events. This includes much more than computer failure. A mistaken payment, unauthorized transaction, weak procedure or external disruption can all create an economic loss.

Technology risk also includes an investment that fails to deliver the expected cost saving. A new platform may be technically operational yet economically disappointing because integration costs were underestimated, staff training took longer, or transaction volume was lower than expected. Failure to achieve the promised efficiency gain is a risk even without a dramatic outage.

Economies of scale arise when average unit cost falls as the output of a service expands. In an original illustration,100 transactions costing 100 imply cost per transaction 1;200 transactions costing 150 imply 0.75. Output doubles while total cost rises by only 50%, spreading fixed infrastructure over more activity.

Economies of scope arise when producing several products together costs less than producing them separately. If payment services cost 80 alone and lending services 70 alone, but a shared platform supplies both for 120, the scope saving is 80+70−120=30. This is different from merely making more of one product. Shared customer data, distribution and processing may generate the joint saving, but poor integration can prevent it.

The two numerical examples are original teaching illustrations, not printed figures from the source. The source’s point is to ask whether the institution actually captures the expected scale or scope benefit after the technology investment, rather than assuming that a larger system is necessarily more efficient.

How operational risk shows up

The systems side of the source lists technology malfunctions and back-office breakdowns. A financial institution depends on reliable records, settlement, customer access and payment processing. A rare failure can affect the entire institution if many services share the same infrastructure. The operational loss may include direct remediation costs, interrupted revenue and liabilities created by incorrect processing.

The historical data-breach examples are Heartland Payment Systems, about 130 million cards in 2009, and Target, about 110 million records in 2013. Preserve their units: cards and records are not monetary loss amounts, and neither automatically equals a count of distinct people. Their role in the lecture is to show the scale of potential information and system exposure.

The people-and-process side includes employee fraud and ordinary error. The source names JPMorgan’s “London Whale,” Bruno Iksil, and approximately $6.2 billion of losses on large CDS positions. A price-sensitive position creates market exposure; inadequate limits, oversight or reporting can amplify it. The categories can therefore coexist in one event.

The footer adds reputational risk. Damaging information, whether true or false, can reduce customer trust, shrink the customer base and weaken future revenue. Direct financial loss and future business loss are different channels. If lost confidence also triggers withdrawals, an operational event can spread into liquidity stress. Reputation is therefore more than publicity; it can affect cash flow and the balance sheet.

Liquidity risk: valuable assets are not necessarily cash today

Liquidity risk arises when depositors, policyholders or other liability holders demand cash and the institution cannot obtain it on time without unacceptable cost or loss. An institution may own valuable long-term loans yet lack cash today. That is different from having assets worth less than liabilities, although the two problems can interact.

Normal day-to-day withdrawals are expected and can be met with cash buffers or routine borrowing. Abnormally large withdrawals change both sides of the funding calculation: more cash is needed, while purchased funds may become more expensive or unavailable. The institution may have to sell assets that were intended to be held until maturity.

A fire-sale means selling under pressure at a price below the value the institution would otherwise expect to realize. The price discount generates a loss, which can reduce capital. Thus an initially solvent but illiquid institution may become insolvent through the costs of meeting immediate claims. If many institutions sell similar assets simultaneously, prices can fall further and stress can spread.

The source’s historical example is the IndyMac deposit run in summer 2008, with continuing stress around FDIC intervention. Its economic lesson is that withdrawal demand can arrive faster than illiquid assets become cash. It is not a general claim that deposit insurance guarantees instant access in every operational situation. The source’s numerical box requires one missing assumption, which we make explicit next.

The 15-million withdrawal: reconcile the fire-sale arithmetic

The source states a surprise withdrawal of 15 million, a fire-sale price of 0.50 per 1 of book value, a 5-million loss, and equity falling from 10 to 5. Those numbers do not describe the sale of 15 million of assets. To raise cash G at price p, the institution must sell book value B=G/p; the loss is B−G.

At a 50% sale price, a 5-million loss accompanies a sale of 10-million book value for 5-million cash. Therefore the reported 15-million withdrawal requires another 10 million of cash already available, or equivalent non-loss funding. This 10-million cash buffer is inferred to reconcile the source, not printed on the slide.

One consistent starting balance sheet is cash 10 plus loans 90, financed by deposits 90 and equity 10. First sell loans with book value 10 for cash 5. Cash becomes 15, remaining loans 80, total assets 95; deposits remain 90 and equity falls to 5. Then pay the 15 withdrawal. Cash becomes 0 and deposits fall to 75, leaving assets 80 = liabilities 75 + equity 5.

The withdrawal itself reduces cash and deposits by the same amount, so it does not directly destroy equity. The sale discount destroys equity. If the bank had no cash initially, raising the full 15 at half price would require selling 30 of book-value assets and losing 15. Starting equity 10 would then become−5, not+5. This alternative proves why the omitted funding assumption matters.

In general, with withdrawal W, usable cash C and sale price p, the cash gap is G=max(W−C,0), book value sold is G/p and loss is G(1/p−1). Remaining equity is E₀ minus that loss, assuming book value equals pre-stress economic value and no other costs or changes. Keep cash needed, assets sold and loss as three separate quantities.

Insolvency risk: the final loss buffer

Insolvency risk is the danger that the institution has too little capital to absorb a fall in asset value relative to its liabilities. It can be the consequence of one or more earlier risks. It does not require all eight originating risks to occur at once. A single sufficiently large credit, market or operational loss can exhaust the cushion.

For a fixed asset size, more equity and less borrowing provide a larger buffer. A simple leverage measure is assets divided by equity, A/E. A bank with assets 100 and equity 5 has leverage 20; one with assets 100 and equity 15 has leverage about 6.67. If both suffer an 8-unit asset loss with liabilities unchanged, the first has equity−3 and the second retains 7. Capital changes resilience, not the amount of the shock itself.

The crisis box gives historical cases. Washington Mutual in 2008 is described as having capital fall to about $3.5 billion before FDIC seizure and sale to JPMorgan Chase. Citigroup in 2009 is shown with shares below $1 and support involving about $306 billion of guarantees and a $20 billion cash injection. The footer states that more than 700 banks received $205 billion in federal capital during 2008–2009.

These figures describe different objects. A guarantee’s covered amount is a contingent commitment, while a cash injection is actual financing. Adding 306+20 and calling 326 billion a realized cash loss would be wrong. Likewise a share price below $1 is not the institution’s total equity capital without knowing shares outstanding and the relevant accounting or market-value definition.

The source’s regulatory conclusion is that capital adequacy is central because capital is the final buffer against losses. Cash adequacy remains a separate question: well-capitalized institutions can still need liquidity, while liquid funding alone cannot repair a sufficiently large economic loss.

The risks are interdependent

The source now joins the categories. A rise in rates may increase the debt-service burden of floating-rate borrowers, raising credit risk. If a guaranteed borrower fails, an off-balance-sheet promise can be called as well. Thus interest-rate, credit and contingent exposures can worsen together under a common shock.

Missed loan receipts also remove cash the bank expected to use for its own obligations. Credit loss can therefore create liquidity pressure. Exchange rates and interest rates may respond jointly to central-bank actions or macroeconomic news, affecting borrowers and the bank’s own currency positions at the same time. These are scenario-dependent connections, not a universal fixed correlation or direction for every currency.

The source adds event risk: sudden discrete shocks such as regulatory change, war, market crashes, fraud or disasters. It also names macro/systematic risk, including inflation and unemployment. The example of US unemployment exceeding 10% in 2009 is historical context, not a current indicator. Such economy-wide stress can weaken many borrowers and increase demands on financial institutions simultaneously.

A complete stress narrative names each link rather than simply saying “all risks are related.” For example: a rate and currency shock weakens a foreign-currency borrower → missed payments reduce loan value and cash receipts → a guarantee is called while depositors withdraw → asset sales crystallize losses → capital is depleted. Weak operational controls may conceal or amplify the exposure along the way.

Every risk ends at capital

The synthesis diagram places eight originating categories above insolvency: interest rate, credit, off-balance-sheet, foreign exchange, market, country/sovereign, technology/operational and liquidity. Their common pathway is not that they are identical; it is that their losses reduce profits or asset value and can exhaust equity.

Equity absorbs the net economic effect. A fall in asset value with no offset reduces E=A−L. A newly recognized liability also reduces E. A cash withdrawal at par need not reduce equity immediately, but a fire-sale required to fund it can. The diagram therefore asks you to trace the balance-sheet mechanism instead of treating every cash movement as a loss.

This also connects the wider course terms financial globalization and financial crisis. Globalization integrates countries through financial claims, institutions, funding and markets. It can diversify opportunities, but the same networks transmit funding and asset-price stress. A financial crisis is a broad disruption of intermediation, funding or payments—not merely any daily price fall or one firm’s ordinary loss.

The diagram is a synthesis, not a forecast that every exposure must lead to failure. Risk management, diversification, hedging, liquidity planning and sufficient capital can limit the loss and keep the institution functioning. The management question is how much risk is being taken, what compensation it earns and whether the institution can bear the adverse outcome.

Key terms and the chapter’s source close

The source ends with 20 key-term boxes. Use them as a retrieval route back to the explanations, not as substitutes for those explanations. The order below follows the source rows. A strong answer defines the term and then gives the cash-flow or balance-sheet channel.

The final page adds source attribution rather than another model: Saunders and Cornett, Financial Institutions Management: A Risk Management Approach, Chapter 7, and the Bank for International Settlements/Basel Committee for the operational-risk definition. Page 52 is therefore recorded in the coverage ledger as the chapter close, not an omitted exercise.