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Happy Monday, future bankers!

Hope everyone is doing well and is having a great start to the week! Today we’re going over calculating free cash flows, discussing how you learn, and how generative-AI may be contributing to a soft landing.

🚀 Let’s get into it.

🔢 Technical Question

“How do you get from revenue to free cash flow when you’re forecasting cash flows?”

Here’s a possible response:

"Free Cash Flow (FCF) is a measure of a company’s financial performance and health. It represents the cash that a company is able to generate after spending the money required to maintain or expand its asset base. To get from revenue to FCF, we need to follow several steps:

1. Subtract Cost of Goods Sold (COGS) from Revenue: This gives us Gross Profit.

2. Subtract Operating Expenses from Gross Profit: This gives us Operating Profit or Earnings Before Interest and Taxes (EBIT).

3. Subtract Taxes from EBIT: This gives us what is commonly referred to as NOPAT (Net Operating Profit After Tax). The tax is calculated as a percentage of the EBIT.

4. Add back Depreciation and Amortization to Net Income: These are non-cash expenses that were subtracted out to calculate net income.

5. Subtract Capital Expenditures (CapEx): These are the costs for long-term assets that will help generate future income.

6. Subtract the Change in Net Working Capital: This represents the changes in current assets and current liabilities.

The result is the Free Cash Flow, which is a key indicator of a company’s profitability after all costs and reinvestments."

Remember, the exact calculation can vary depending on the specifics of the company and the industry it operates in. It’s also important to note that this is a simplified explanation and actual financial modeling can be much more complex and nuanced.

🗣 Behavioral Question

"How do you approach a new or unfamiliar topic or problem?"

This is a good question to prepare for, as it shows your ability to learn and adapt quickly in a dynamic and complex industry. Here are some best practices when responding to this question:

• Use the STAR method (Situation, Task, Action, Result) to structure your answer. This will help you provide a clear and concise example of how you approached a new or unfamiliar topic or problem in a previous situation.

• Choose a relevant and specific example that demonstrates your skills and knowledge in the investment banking field. For instance, you can talk about a project or assignment that involved researching a new market, company, product, or concept that you were not familiar with before.

• Explain the steps that you took to learn about the topic or problem, such as identifying and accessing reliable and relevant sources of information, analyzing and synthesizing the information, evaluating its quality and credibility, and applying it to the topic or problem.

• Highlight the skills and qualities that you displayed in the process, such as curiosity, initiative, resourcefulness, critical thinking, analytical thinking, and problem-solving.

• Emphasize the positive outcome or result that you achieved or contributed to, such as delivering a high-quality report, presentation, or recommendation, gaining new insights or perspectives, or solving a challenge or issue.

Here is a brief example response that follows these best practices:

“I approached a new topic when I analyzed a fintech acquisition in a case competition. I researched the industry, the target, and the acquirer using various sources and tools. I started out by learning about the industry, and then slowly narrowing into the specific company that I was researching. I valued the target, assessed the fit and synergies, and recommended the deal. I delivered a quality report and presentation, and learned a lot about fintech and M&A.”

🗞 Industry News

Generative-AI Creating A Soft Landing? 🛬

Americans may be on the cusp of witnessing a historic economic event: inflation returning to normal without plunging into a recession, a scenario fondly referred to as a "soft landing" by analysts. The recent burst of productivity growth has been credited with much of this progress. Last year saw a remarkable rebound in productivity after a sharp decline in 2022. This surge allowed workers to enjoy significant wage gains without burdening consumers excessively, as they were able to produce enough across various industries to offset higher labor costs.

Productivity, in economic terms, essentially means doing more with less, and last year's strong productivity meant the economy could maintain robust growth without stoking inflation. The productivity rate saw a notable jump, particularly in the fourth quarter, surpassing the average increase of the past two decades. While there isn't a single reason for this productivity surge, theories range from the impact of generative artificial intelligence making tasks more efficient to companies becoming leaner and more efficient in anticipation of a recession that never occurred.

Despite the challenges in precisely measuring productivity in real-time, it remains a crucial factor considered by Federal Reserve officials in shaping policy decisions. However, accurately measuring productivity, especially in the service sector, poses significant challenges. While last year's productivity boom may have contributed to a soft landing, it's still uncertain whether it signifies a transformative shift in the economy. Nevertheless, expectations lean towards continued improvements in productivity, particularly driven by generative tools, which could contribute to disinflation over the long term.

Read more about this story below.

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Thanks for tuning in today! Best of luck to everyone working through recruiting right now. If you sign an offer, reply to this email and let us know about it! Like seriously, do it—we’d love to hear about it!