What's The Big Deal?

Claude for Finance: Building a Live Merger Model with AI

49 min · 21 mei 2026
aflevering Claude for Finance: Building a Live Merger Model with AI artwork

Beschrijving

How good is AI at building investment banking models?  In this episode, Debs and Graham put Claude for Excel to the test by prompting it to construct a full merger model from scratch, using GameStop's $56 billion bid for eBay as the live case study, but with the focus squarely on the AI workflow rather than the deal itself. Graham walks through the merger model framework from first principles before opening Claude for Excel and giving it a single instruction: build me a merger model for the proposed acquisition.  What follows is a live demonstration of what AI can and cannot do in a real M&A modelling workflow. The verdict is nuanced. Claude sources factual data quickly, structures the model sensibly, makes a credible first pass at sources and uses, and saves the kind of analyst time that used to go into manual press release scrubbing and 10-K data extraction.  But it also makes errors that anyone trained in proper modelling would catch immediately, hardcoded assumptions buried in cell formulas, fiscal year mismatches between acquirer and target, missing synergy inputs that were publicly disclosed, and modelling practices that would never pass a senior banker's review. The takeaway: Claude for Excel is a powerful first-pass tool that can compress hours of analyst work into minutes, but it is dangerous in the hands of anyone who cannot audit the output.  The fundamentals of modelling, accounting and finance still matter - arguably more than ever, because the cost of accepting AI output without scrutiny is now embedded in every workflow. Key Discussion Points: Merger model framework: accretion, dilution, sources and uses, pro forma adjustments, LTM calendarisation.  Prompting strategy: what a minimal prompt produces versus what structured prompting would deliver.  Where AI saves time: factual data sourcing, model structure, first-pass build.  Where AI fails: modelling best practices, hardcoded inputs, technical errors, judgement calls.  Stress-testing in real time: how to use AI to iterate on synergy, consideration mix and financing assumptions.  AI in finance careers: why the fundamentals matter more than ever in an AI-enabled workflow. WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

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16 afleveringen

aflevering Global M&A Just Hit a RECORD $2.8 TRILLION. Here's What's Driving It. artwork

Global M&A Just Hit a RECORD $2.8 TRILLION. Here's What's Driving It.

Global M&A hit a record $2.83 trillion in H1 2026, the highest total since records began, eclipsing the 2021 peak of $2.74 trillion.  Deal values in Q2 alone were up 41% year-on-year, deal count up around 10%, mega deals continue to dominate, and small-cap and venture activity is up 200%.  But the picture underneath the headline numbers is more complicated, and both think the drivers behind the surge may not last into 2027. In this episode, Debs and Graham work through Bain's mid-year M&A report and unpack the themes behind the numbers.  They open with market context: SpaceX post-IPO with the share price now below $160 and the first lock-up expiries approaching, the AI mini-correction of June driven by CapEx discipline concerns, Meta joining xAI in selling excess compute capacity, and news of a Chinese frontier model claiming performance at 10% of the cost of leading Western models.  The M&A conversation itself focuses on the defensive posturing thesis. With geopolitical, business model, and AI-disruption uncertainty at unusual levels, large corporates are buying up smaller disruptive companies as insurance against being outmaneuvered.  The 200% increase in small-cap and venture activity supports the read. Debs highlights the awkward setup for a typical M&A cycle: hawkish interest rate environment, frothy sector valuations, and low certainty, none of which usually correlate with peak deal activity. The sector-by-sector split reveals financial services quietly lagging the broader market. Graham & Debs speculate on why, and neither has a strong answer.  Europe is the standout regional performer, driven partly by the valuation gap versus the US (roughly 15x forward P/E versus 22x) and partly by the possibility that acquirers are moving now ahead of a mooted merger benefit test that could add a second regulatory hurdle to European deals. The episode closes on H2 predictions.  Debs is skeptical the second half will match the first, citing hawkish rates, frothy valuations, and the pent-up demand carrying over from 2025 already being absorbed.  Graham expects continued growth from the existing pipeline but flags 2027 as the genuine question mark: once the current pipeline works through, whether the fundamentals actually justify M&A at this level is an open question. Key Discussion Points: * Global M&A hits record $2.8 trillion in H1 2026 * Q2 stats: deal values up 41% YoY, deal count up ~10%, mega deals dominating * The defensive M&A thesis: uncertainty as a driver of acquisition activity * Small-cap and venture activity up 200%: what it signals about corporate defensive posturing * The sector-by-sector split: energy and industrials leading, financial services quietly lagging * Europe outperforming: valuation gap, competition clearance, and the potential merger benefit test * Market context: SpaceX post-IPO dynamics, AI selloff drivers, Meta's excess compute sale, and the Chinese model story * H2 2026 and 2027 predictions: pent-up demand vs. fundamentals Bain M&A Report: https://www.bain.com/insights/m-and-a-midyear-outlook-2026-a-winners-paradox/ [https://www.bain.com/insights/m-and-a-midyear-outlook-2026-a-winners-paradox/] WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

2 jul 202623 min
aflevering Private Equity vs. Private Credit Explained in 15 Minutes artwork

Private Equity vs. Private Credit Explained in 15 Minutes

Two of the biggest growth areas in finance over the last decade, but the differences between private equity and private credit are often misunderstood, especially by candidates trying to decide between them.  In this episode, Debs sits down with Graham, who spent a decade at Ares Management for a Q&A-style explainer that breaks down what each actually is and how the day-to-day differs. Graham starts with the fundamental distinction: private equity invests in companies that don't trade on the public market, private credit makes illiquid loans to those companies. From there the conversation moves through the deeper differences.  The motivation gap, where equity investors are hunting for upside and credit investors are protecting capital because their upside is contractually capped. The return profiles, with PE targeting 15%+ IRRs at the asset level versus credit closer to high single digits to low double digits, and how private credit funds use fund-level leverage to amplify those returns. The conversation then turns to how the two sides actually interact. Graham flags that he never saw a firm finance its own PE deals with its own credit fund and that the base case is keeping the two operations independent.  He explains how closely PE sponsors and credit providers negotiate during deal-making, what makes a company attractive to both sides simultaneously (recurring revenue, cash flow visibility, growth prospects), and why the diligence focus differs significantly. Equity focuses on the upside thesis, credit focuses on every way you could lose money. The episode closes on career-relevant differences. Single-deal depth in PE versus higher deal flow in credit, the generalist versus specialist question, and how the route into both has fundamentally changed since Graham's own start at Lehman Brothers in the mid-2000s. Key Discussion Points: The fundamental distinction: investing in companies vs. making illiquid loans.  Motivation gap: upside potential vs. capital preservation, and what capped upside means in practice.  Return profiles: 15%+ IRR in PE vs. high single digits to low double digits in credit, plus how fund-level leverage closes some of that gap.  Firm independence: why PE and credit arms within the same firm don't typically finance each other's deals.  Deal mechanics: how PE sponsors and credit providers negotiate, and what makes a company attractive to both sides.  Diligence focus: market opportunity vs. downside protection, and how the two diligence mindsets differ.  Career-relevant differences: deal flow, depth vs. volume, generalist vs. specialist, and how to break in today. WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

25 jun 202614 min
aflevering EX-BANKERS EXPLAIN: Investment Banking Mistakes To AVOID In Your First Year artwork

EX-BANKERS EXPLAIN: Investment Banking Mistakes To AVOID In Your First Year

It's summer training season. Both Debs and Graham are spending their days running analyst and associate programmes at major firms, which makes this the right moment to step back from the deal-of-the-week format and share the kind of candid advice they wish someone had given them on day one. Graham opens with his own first-year story at Lehman Brothers in 2005, including the pitch book error that earned him an hour-long dressing-down from a VP, and uses it as the entry point to a broader conversation about attention to detail and why the technical work in finance is genuinely not the hardest part of the job.  Debs shares her own near-career-ending moment publishing a flawed research screen as a new associate, and reflects on how she recovered, what her boss told her, and why trust, once lost, takes years to rebuild. From there the conversation moves through the practical advice that gets harder to find as classes get larger and firms get bigger.  How to tell the difference between a recoverable mistake and a career-ending one. Why finance math is simple and getting stuff done well is the actual skill.  How to ask questions that add value versus questions that just take up airtime. Why prep before meetings is the easiest way to stand out, why sharp elbows are usually the wrong instinct, and why being a team player matters more than being the smartest person in the room. The episode closes with their personal survival tips: physical activity, availability, sleep, calendar discipline, and showing up to everything you can.  The kind of advice that sounds basic but separates the analysts who get the return offer from the ones who don't. Key Discussion Points: Attention to detail: why the costs of getting it wrong are high, and how AI changes (but doesn't reduce) the standard.  Recoverable vs. career-ending mistakes: how to tell the difference and what to do in each case.  The technical work is the easy part: why getting stuff done well is the real skill.  Asking questions that add value: how to demonstrate engagement without taking up airtime.  Standing out without sharp elbows: why being a team player and showing up consistently is the most underrated path.  Survival habits: physical, mental, calendar, sleep, and the practical mechanics of not burning out. WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

18 jun 202630 min
aflevering The $1.75 Trillion SpaceX IPO: Everything You Need to Know. artwork

The $1.75 Trillion SpaceX IPO: Everything You Need to Know.

SpaceX begins trading on Friday at a $1.75 trillion valuation, and the deal looks unlike any major IPO that has come before it.  In this episode, Debs and Graham go inside the prospectus, break down the unusual structural features Elon Musk has pushed through, and debate whether the valuation can be justified. The mechanics alone are remarkable. The IPO is being priced at a fixed $135 per share rather than through a traditional book-build range, putting all of the price risk onto buyers and signalling unusual confidence from the issuer. The free float is less than 5%, which sets up potentially significant post-listing volatility.  Retail investors have been given 30% of the allocation, roughly three times the typical share, raising the question of whether this is genuine democratisation or simply exit liquidity for early holders.  The dual-class share structure leaves Musk with 85% of the voting power despite owning around 45% of the economics.  And the underwriting fee, agreed across a syndicate of 23 banks, has come in at 0.75%, the lowest on record for a deal of this size. The valuation discussion centres on the TAM chart in the prospectus. SpaceX has positioned itself less as a launch and communications business and more as an AI infrastructure and applications story, with $26.5 trillion of AI revenue underpinning the case for the headline number, including $22.7 trillion in enterprise applications alone.  Debs and Graham draw the parallel to the Tesla IPO, where the company was reframed from auto to tech in order to unlock a tech multiple. They also reference Aswath Damodaran's published view that the realistic AI TAM is closer to $5 trillion, and Morningstar's estimate that the fair value of the business is roughly half the IPO valuation. The episode closes on what to watch when trading begins. With oversubscription pointing to a potential pop, but a low free float, a 180-day staggered lock-up creating an overhang, and the Nasdaq 100 fast entry expected to trigger $30 to $50 billion of forced buying, the first six months are likely to be unusually volatile. Both hosts agree the outcome is genuinely unpredictable. Key Discussion Points: The fixed-price IPO mechanism, why it's unprecedented at this scale, and what it signals about the issuer's confidence.  The structural risks: low free float, large retail allocation, dual-class shares and lock-up dynamics.  The fee anomaly: 23 banks, 0.75% — the lowest on record for a mega-deal.  The TAM debate: $23 trillion in the prospectus versus Damodaran's $5 trillion estimate, and how the AI bucket drives the valuation.  The Tesla parallel: reframing the business to land a tech multiple.  What to watch in early trading: oversubscription, index inclusion fast entry, and the 180-day lock-up overhang. WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

11 jun 202635 min
aflevering Will the $4 Trillion AI IPO Wave Break the Market? SpaceX, OpenAI & Anthropic artwork

Will the $4 Trillion AI IPO Wave Break the Market? SpaceX, OpenAI & Anthropic

Three mega IPOs are heading to market: SpaceX, OpenAI and Anthropic. Between them they could push the largest tech names to nearly half of the S&P 500, at valuations that have drawn obvious comparisons to the dotcom era. In this episode, Debs and Graham debate whether those comparisons hold, and where they break down. They start with the triggers: extreme index concentration, the scale of the valuations being floated, and the structural role of index funds that are obliged to buy these companies once they join the benchmark.  They then look back at the dotcom boom and bust, drawing lessons from failures like Web Van and Pets.com, businesses whose underlying ideas were sound but whose execution and unit economics were not, and the survivors like Amazon and eBay that collapsed before figuring out their models. The core of the episode is a genuine bull versus bear debate. Debs makes the case that 2026 is not 1999: the S&P trades at around 23 times forward earnings against a long term average near 18, a world away from the Nasdaq's 60 times in 1999, and today's dominant AI names generate real profits and cash flow.  Graham presses the bear case: the CapEx burn behind the AI build-out is enormous, run rate revenue is not a GAAP concept and is open to management, and the return on all that data centre spending remains unproven. They agree the sharpest risk is concentration. With AI-focused names potentially approaching 50% of the index, a miss on a few key data points could move the entire market. They close by each picking the IPO they would back today. Both land on Anthropic, citing a more measured profile and the principle that being first is not the same as being best, while acknowledging that the real financial picture for OpenAI and Anthropic will only become clear once their S-1 filings arrive. Key Discussion Points: The three mega IPOs: SpaceX, OpenAI and Anthropic, and the valuations being floated.  Concentration risk: the Magnificent Seven, index fund mechanics and the path toward 50% of the S&P 500.  Lessons from the dotcom crash: why execution and unit economics mattered more than being first. Valuation reality check: forward earnings multiples today versus 1999.  The bull case: real profits and cash flow among today's AI leaders.  The bear case: CapEx intensity, run rate revenue scrutiny and unproven returns.  The IPO process: where SpaceX, OpenAI and Anthropic each sit, and why the S-1 filings matter.  The verdict: which IPO each host would back and why. WTBD Newsletter: https://webmail.wallstreetprep.com/whats-the-big-deal [https://webmail.wallstreetprep.com/whats-the-big-deal] Follow Us On Socials: LinkedIn: https://www.linkedin.com/company/wall-street-prep/ Instagram: https://www.instagram.com/wallstreetprep/ Resources: https://linktr.ee/wallstreetprep

4 jun 202628 min