Commercial Awareness Update: 13th October 2026

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Let’s go over three stories from the last week that are particularly useful for interviews.

Here's what we're covering:

There's a common theme running through all three: the relationship between risk, returns and the cost of capital.

And because we're in application season, I've included talking points to help you turn each story into something useful for interviews.

Let's get into it.

Prepare for interviews, under pressure.

IB Cheat Codes | IB Prompts (Save Hours)

JPMorgan Chase reported its third-quarter earnings today.

And for the first time since late 2023, America's largest bank failed to meet Wall Street's profit expectations.

The bank earned $5.57 per share, compared with analysts' expectations of $5.85.

That's a relatively small miss in percentage terms.

But when you're a bank the size of JPMorgan, investors pay close attention to even small deviations from expectations.

What's particularly interesting is what happened underneath the headline.

Investment banking fees fell 8% compared with the previous quarter.

Fixed-income trading revenue declined 4%.

But equities trading revenue increased an extraordinary 49% year-on-year.

So how can one of the world's largest investment banks experience a slowdown in some divisions while another is growing almost 50%?

Here's the mechanism, because it tells us something important about how investment banks actually make money.

Investment banking and trading are fundamentally different businesses.

Investment bankers generate fees by advising companies on acquisitions, helping them raise capital and executing transactions.

Those fees depend heavily on companies being willing and able to do deals.

Imagine a private equity firm considering a £5 billion acquisition.

Six months ago, it might have expected to borrow money at 5%.

Today, suppose that financing costs 8%.

If it borrows £3 billion, that three-percentage-point increase represents an additional £90 million of annual interest expense.

Suddenly, the acquisition looks much less attractive.

The private equity firm might delay the transaction, renegotiate the purchase price or abandon the deal entirely.

And if the transaction doesn't happen, the investment bank may lose the advisory fees it was expecting.

That's one reason higher interest rates can hurt investment banking activity.

But trading works differently.

Trading desks generate revenue by facilitating client transactions, making markets and managing risk.

When markets become volatile, institutional investors often need to adjust their portfolios.

A pension fund might reduce its equity exposure.

A hedge fund might hedge against further market declines.

An asset manager might rotate out of technology stocks and into defensive sectors.

Those activities create demand for trading services.

And that's exactly what JPMorgan's results demonstrate.

While dealmaking slowed, investors continued actively repositioning their portfolios.

The result?

Equities trading revenue increased 49%.

There's another interesting part of the results.

JPMorgan's net interest income, excluding its markets business, increased 6% to $24.7 billion.

Net interest income is essentially the difference between the interest a bank earns on assets such as loans and the interest it pays on funding such as deposits.

Higher interest rates can benefit that business, although the outcome depends on deposit costs, loan demand and credit quality.

So within the same bank, higher rates can simultaneously:

That's why saying "higher rates are good for banks" or "higher rates are bad for banks" is far too simplistic.

The answer depends on which business you're talking about.

And the broader earnings picture reinforces this.

Goldman Sachs and Citigroup exceeded analysts' profit expectations, demonstrating that the same market environment can produce very different outcomes depending on a bank's business mix and execution.

1. Know what happened

JPMorgan reported a rare earnings miss, with earnings per share of $5.57 versus expectations of $5.85. Investment banking fees declined 8% quarter-on-quarter, while equities trading revenue increased 49% year-on-year.

2. How does it impact the firm?

The results show why revenue diversification matters. A universal bank can benefit from lending and trading even when advisory activity slows. However, sustained higher rates could eventually weaken credit quality and client demand.

3. How does it impact the division?

For Investment Banking, discuss the impact of higher financing costs on M&A and IPO activity.

For Sales & Trading, explain how portfolio repositioning and volatility can increase client activity, without assuming volatility always increases profits.

For Asset Management, discuss how changing rates and valuations influence portfolio allocation.

For Risk, consider the possibility that borrowers face greater repayment pressure as debt matures and needs refinancing.

4. How does it impact clients?

Corporate clients may postpone acquisitions or capital raising.

Private equity firms may find leveraged buyouts less attractive.

Institutional investors may need to hedge interest-rate exposure or rebalance portfolios.

5. What's your opinion?

"I think JPMorgan's results demonstrate the resilience of a diversified banking model. The 49% increase in equities trading revenue is impressive, but I'd be cautious about extrapolating that growth because trading activity can be unpredictable. I'm more interested in whether the investment banking pipeline converts into completed transactions over the next few quarters."

6. What would you watch next?

Watch whether delayed M&A and IPO transactions return, whether equity trading remains strong and whether higher rates start affecting credit quality.

The key question is whether we're experiencing a temporary slowdown in dealmaking or the beginning of a more prolonged period of expensive capital.

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On Tuesday, Chinese technology giant Tencent raised approximately $5.7 billion through the bond market.

But the remarkable part isn't how much Tencent borrowed.

It's how much investors wanted to lend.

The company received more than $23 billion in investor orders.

That's more than four times the amount of debt it actually issued.

And this is happening at a time when investors are becoming increasingly nervous about the enormous amount of money being borrowed to fund artificial intelligence.

So why did Tencent attract so much demand?

First, it's worth understanding how a bond offering actually works.

When a company wants to borrow money through the bond market, it typically hires investment banks to arrange the transaction.

Those banks help determine how much debt the company should issue, what maturity it should have and what interest rate investors will require.

They then approach institutional investors such as pension funds, insurance companies and asset managers.

Investors submit orders indicating how much debt they're willing to buy.

Those orders form what's called the order book.

Imagine Tencent wants to borrow $5 billion.

If investors collectively offer to buy only $3 billion, demand is weak.

Tencent might need to offer a higher yield to attract more buyers.

But if investors submit $20 billion in orders, demand is extremely strong.

That gives the company and its bankers greater negotiating power over pricing.

And that's exactly what happened here.

Tencent issued bonds in both US dollars and offshore Chinese yuan.

The dollar bonds included 10-year and 20-year maturities, while the yuan bonds extended as far as 30 years.

The company's 10-year dollar bonds were marketed initially at around 115 basis points above comparable US Treasury yields.

They ultimately priced at 90 basis points above Treasuries.

That's a reduction of 25 basis points.

For context, one basis point is 0.01 percentage points.

On $1.3 billion of 10-year bonds, a 25-basis-point reduction in annual borrowing costs represents approximately $3.25 million in interest savings per year, assuming the comparison is made on the same principal and benchmark.

Across ten years, that would amount to approximately $32.5 million before considering discounting and other bond-pricing details.

That's real money.

And it demonstrates something important:

Strong investor demand can directly reduce a company's cost of borrowing.

But why was demand so strong?

Tencent has substantial established businesses generating revenue and cash flow.

Its bonds are also expected to carry investment-grade credit ratings.

That makes it a different proposition from a highly leveraged AI infrastructure company whose future revenues remain uncertain.

Tencent is increasing its AI investment significantly.

Its capital expenditure more than doubled to 96.3 billion yuan in the first half of 2026, compared with 45.9 billion yuan a year earlier.

But investors aren't simply lending against the hope that AI might eventually become profitable.

They're lending to an established company with existing operations and a substantial financial position.

There's also a useful detail for anyone applying to investment banks.

JPMorgan, Goldman Sachs, HSBC and Morgan Stanley were joint global coordinators for Tencent's dollar bond offering.

This is precisely the kind of transaction Debt Capital Markets teams work on.

And it's a perfect example of how investment banks generate fees without advising on an acquisition.

1. Know what happened

Tencent raised approximately $5.7 billion through dollar- and yuan-denominated bonds, attracting more than $23 billion in orders. Strong demand allowed the company to tighten pricing relative to initial guidance.

2. How does it impact the firm?

Banks involved in arranging the offering can earn underwriting and distribution fees while strengthening relationships with a major corporate client.

The transaction also demonstrates continued demand for financing services connected to AI investment.

3. How does it impact the division?

For Debt Capital Markets, discuss bond pricing, investor demand, maturities and credit spreads.

For Sales & Trading, explain how banks distribute securities and facilitate secondary-market trading.

For Asset Management, consider whether Tencent's yield offers sufficient compensation for credit, currency and geopolitical risks.

For Risk, focus on the company's capacity to service its debt and the potential consequences of rising AI capital expenditure.

4. How does it impact clients?

Corporate borrowers may see Tencent's deal as evidence that bond markets remain open for strong issuers.

Institutional investors gain access to long-dated corporate debt.

However, investors also need to assess credit risk, duration risk and, where relevant, currency exposure.

5. What's your opinion?

"I think Tencent's bond offering demonstrates that investors aren't necessarily turning against AI-related borrowing altogether. They're becoming more selective. Companies with established cash flows and strong balance sheets can still attract significant demand, while more speculative borrowers may struggle to obtain similarly attractive financing."

6. What would you watch next?

Watch whether Tencent's AI investment translates into revenue and cash flow growth.

Also monitor credit spreads.

If investors begin demanding significantly higher spreads from even established technology companies, that could indicate a broader change in risk appetite.

Your fastest route to an offer this application season.

For much of 2026, technology companies have been borrowing enormous amounts of money to finance AI infrastructure.

Data centres.

GPUs.

Electricity.

Cooling systems.

Networking equipment.

The scale of spending has become extraordinary.

But something interesting is happening in credit markets.

According to reporting from the Financial Times, AI-related debt issuance fell to approximately $23 billion in September, less than half the amount raised in August.

Earlier in the year, monthly financing activity had reportedly reached as much as $113 billion in June.

And according to Goldman Sachs data reported by Reuters, AI-related leveraged finance issuance had already reached approximately $88 billion in 2026 by the end of September.

This isn't evidence that AI investment has stopped.

Far from it.

But it does suggest that investors are becoming more cautious about how that investment is financed.

Here's why this matters.

Imagine a company wants to build a $10 billion data centre.

It expects to generate substantial revenue by renting computing capacity to AI companies.

But constructing the data centre requires billions of dollars upfront.

The company might finance the project using a combination of equity and debt.

Let's say:

That model can work extremely well if demand materialises as expected.

But what happens if construction takes longer than planned?

Or electricity costs rise?

Or a major customer delays its expansion?

Or the GPUs become technologically outdated faster than anticipated?

The debt still needs to be serviced.

And because lenders have contractual claims on the business, they care enormously about the reliability of future cash flows.

This is where AI financing becomes more complicated than simply believing AI will change the world.

You can be completely correct that AI adoption will grow dramatically over the next decade.

But that doesn't automatically mean every data centre built today will generate attractive returns.

It also doesn't mean every company borrowing to finance those data centres will be able to repay its debt.

Think about the internet boom.

The internet fundamentally transformed the global economy.

But that didn't prevent enormous losses for investors who financed businesses with unsustainable economics during the dot-com bubble.

The technology can succeed while individual investments fail.

That's the distinction investors are increasingly trying to make with AI.

And there's another issue.

Interest rates are rising.

The Federal Reserve raised rates in September, while US Treasury yields have climbed sharply.

Higher government bond yields increase the returns investors can earn from relatively low-risk assets.

So if an investor can earn more from US Treasuries, they may demand an even higher yield to finance a speculative data centre.

That increases the project's cost of capital.

And as financing becomes more expensive, some projects that previously looked profitable may no longer generate acceptable returns.

This is why the AI investment cycle is becoming a question of capital allocation.

Not simply:

"How much AI infrastructure can we build?"

But:

"Which projects will generate enough cash flow to justify the money being invested?"

And this connects directly to Tencent.

Tencent's offering attracted enormous demand because investors were comfortable with its overall credit profile.

But weaker or more leveraged AI borrowers may face much greater scrutiny.

Two companies can both be investing in AI and still face completely different financing conditions.

1. Know what happened

AI-related borrowing has slowed from earlier peaks as investors increasingly scrutinise leverage, financing costs and the reliability of future cash flows.

2. How does it impact the firm?

Banks can generate substantial revenue by arranging AI-related financing, but they also face underwriting, counterparty and credit risks.

If demand weakens, banks may find it harder to distribute debt or may need to offer more attractive terms to investors.

3. How does it impact the division?

For Investment Banking, discuss project finance, capital raising, restructuring and M&A opportunities.

For Asset Management, examine whether AI-related credit spreads adequately compensate investors for risk.

For Sales & Trading, discuss credit spreads, liquidity and the potential for greater volatility in corporate bonds.

For Risk, focus on leverage, concentration risk, collateral valuations and the reliability of contracted future revenues.

4. How does it impact clients?

AI companies and infrastructure developers may face higher borrowing costs or stricter lending conditions.

Institutional investors may find opportunities to earn higher yields, but they must distinguish financially resilient issuers from speculative projects.

Private equity and infrastructure funds may need to reassess project valuations and expected returns.

5. What's your opinion?

"I'm positive on the long-term demand for AI infrastructure, but I think investors are right to become more selective about financing. The key distinction is between technological adoption and investment returns. AI can transform the economy without every company funding the buildout becoming a successful investment."

6. What would you watch next?

Watch four things:

AI revenues → Capital expenditure → Free cash flow → Credit spreads

If revenues and free cash flow grow quickly enough to support the enormous investment, confidence should improve.

If borrowing continues rising while cash generation disappoints, financing conditions could tighten further.

Three stories this week.

JPMorgan missed earnings expectations as higher rates and uncertainty affected parts of its business.

Tencent raised $5.7 billion and attracted more than $23 billion of investor demand.

And the broader AI debt market is showing signs of slowing as investors become more selective.

At first glance, they look like separate stories.

But they're all about the same underlying question:

How much risk are investors willing to take, and what return do they require to take it?

JPMorgan's results show how changing financial conditions affect different banking businesses.

Tencent's bond offering demonstrates that companies with strong credit profiles can still access enormous amounts of capital on attractive terms.

And the slowdown in AI borrowing shows what happens when investors become less confident about future cash flows.

Here's the distinction I want you to understand.

Capital hasn't disappeared. It's becoming more selective.

Investors are still willing to lend.

Banks are still willing to arrange financing.

Companies are still investing.

But the terms increasingly depend on the quality of the borrower, the credibility of its cash flows and the risk investors are being asked to assume.

And that's how you should think about commercial awareness.

When you read a headline, don't stop at what happened.

Ask yourself:

How does this affect the firm I'm applying to?

How does it affect the specific division?

What does it mean for the firm's clients?

Do I think the development is positive or negative, and why?

What do I expect to happen next?

You don't need to predict the future perfectly.

You need to demonstrate that you understand the relationships between businesses, markets and the wider economy.

That's what separates someone who reads financial news from someone who understands finance.

That's all for now. Have a good week ahead!

Afzal

Ps. Whenever you’re ready: