Next Session

Aug 24-26

Location

New York City

Enrollment

$2,995

3-Day Instructor-Led Boot Camp in New York City

Investment Banking
AI Boot Camp

Over three immersive days in New York City, you'll learn to use AI across the core workflows of investment banking — and bring back the skills and judgement to become your team's AI expert.

Aug 24-26, New York City

Next Session

Aug 24-26

Schedule

9a–5p Daily

Location

New York City

$2,995 per person

Enroll in Boot Camp Request Group Pricing

Led By Wall Street's Top AI Trainers
Turbo-Charge Real IB Workflows
Meet & Network with AI-First Peers
Earn WSP's AI for IB Certificate
Earn 27 CPE Credits
Includes Full Modeling Training & Prompt Library Access

Learn From the Global Leader of IB Training

A Three-Day3-Day AI Intensive from
Wall Street's Training Provider

AI is fundamentally changing investment banking, turbo-charging work product while raising the stakes on human judgment. This boot camp is a direct adaptation of the AI training we run at the world's top investment banks. It delivers a practical AI skillset you can put to work immediately.

Claude building a debt schedule cash sweep waterfall

Using AI for Financial Modeling and Data Analysis

Turbocharge your ability to produce investment banking-grade financial modeling work product and perform complex data analysis, while developing the discipline and frameworks for verifying outputs and ensuring accountability.
Polished Deliverables that Pass VP Review

Learn to leverage AI to build core IB work product — CIMs, research, deal materials. And learn to detect AI pitfalls: language that degrades deal narrative, outputs that increase rather than reduce cognitive load for the seniors and clients reading your work.
Communication and Judgement

AI has raised the stakes on judgement, accountability, and communication skills, particularly among junior bankers. This boot camp navigates participants through common AI pitfalls, and builds best practices calibrated to communication, modeling, document review, and written work.

Program Agenda

Learn the AI Tools & Workflows Already Deployed at Leading Investment Banks

This boot camp is built by the same instructor-practitioners who lead AI skills training at the world's leading investment banks. That means you'll learn AI skills structured around the up-to-date tools and workflows investment banking analysts are actually using on the desk.

Day 1

Modeling & Valuation

A candid, demo-driven look at the current state of AI in financial modeling, before getting hands-on.

The state of play: an honest assessment of what tools like Claude, ChatGPT, Rogo and Copilot in Excel can and can't do in modeling work today, and where the technology is genuinely useful versus overhyped
Keeping humans in the loop: which parts of the modeling process still require judgment, and where blindly trusting AI output goes wrong
Common failure modes: the recurring mistakes AI makes in modeling (broken links, silent errors, fabricated figures) and how to catch them
Populating historicals: live demo of using AI to pull and structure historical financials into a model
Error-checking a model: using AI to audit an existing model for integrity issues, formula inconsistencies, and sign errors

Hands-on demonstrations of layering different pieces of analysis with AI inside a working model.

Building specific schedules: using AI to construct discrete model components (debt schedules, working capital, capex) to spec
Layering scenario toggles: setting up switchable scenario logic and driver-based cases with AI assistance
Stress-testing assumptions: pressure-testing a model's inputs and surfacing sensitivity ranges faster than by hand
Valuation touchpoints: where AI can accelerate comps, DCF, and football field work, and where it can't be trusted to
Workflow recap: assembling the pieces into a repeatable, auditable AI-assisted modeling workflow

Day 2

Diligence & Data

Front-to-middle of the deal lifecycle: finding, profiling, and reading deal materials with an IB lens.

Buyer/investor universe build: screening and ranking a target universe against deal criteria
Company & sector one-pagers: fast-turnaround company briefs and CEO profiles for live deal conversations
CIM review and risk teardown: identifying key risks and red flags embedded in a confidential information memorandum
Credit agreement and covenant review: extracting and interpreting covenant terms from lengthy credit documentation
Data room triage: systematically working through large volumes of unstructured documents to surface and log issues

Turning a messy, real-world data set into deal-ready analysis, then into the client-ready materials that analysis feeds.

Data cleaning & structuring: taking an inconsistent company-provided data set and converting it into an analyzable format
Trend and cohort analysis: surfacing segment, region, and customer trends, and running cohort analysis to understand retention, concentration, and mix
Visualization & dashboards: building charts and a summary dashboard that communicate the findings
Assumptions in, model out: translating the data findings into defensible assumptions for scenario building
Pitch book and report drafting: turning the analysis just produced into polished pitch and committee-ready materials
Building decks with AI: accelerating slide creation, structure, and narrative flow from the underlying work

Capstone assigned: Participants receive the buy-side case study to begin working on.

Day 3

Communication & Capstone

The most-cited pain point in enterprise AI adoption: knowing when to trust AI output, how to check it, and where human judgment stays non-negotiable.

Verifying AI output before it goes upstream: a structured review process for catching errors, fabrications, and unsupported claims before work reaches a VP or client
Common failure modes: hallucinated figures, fabricated citations, and plausible-but-wrong logic, and how each typically shows up in practice
Tying claims back to source: building the habit of traceable, auditable output that can withstand scrutiny
Knowing when to trust versus rebuild: judging when AI output is close enough to refine versus when it needs to be redone by hand
Client and internal communications: drafting tone-appropriate, defensible messages for external and internal audiences
Where human judgment is non-negotiable: the calls that stay with the professional regardless of how capable the tools become

Moving from one-off AI assistance to reusable, team-ready tooling: the direction the market is heading and where firms are investing now.

From one-off to reusable: turning a workflow you ran this week into something repeatable and shareable
Custom GPTs and Projects-based workspaces: packaging context, instructions, and reference material so a workflow runs consistently every time
Prompt libraries: building and maintaining a shared, reusable prompt set that a whole team can draw on
Simple agentic chains: where lightweight automation genuinely helps, and where it adds fragility and risk
Governance and guardrails: keeping reusable tools accurate and current as inputs and models change

Participants present their work and receive live feedback.

Presentations: each participant or team walks through their 4-5 slide output, including the football field and key findings
Live feedback on both the analysis and the AI workflow used to produce it
Debrief on where AI helped, where judgment made the difference, and which pieces are worth turning into reusable tools

Participants take on a buy-side mandate with preliminary data room access, including a sell-side base case model, high-level financials, and raw customer-level data. Over the program they build trading comps and precedent transactions to frame valuation, clean and analyze the raw data to inform assumptions, build an operating model with upside and downside scenarios, and package it into a 4–5 slide output with a football field and key findings. The capstone chains every skill from the program into one continuous workflow.

Upon completion, you will earn our AI for Investment Banking Certificate. This credential can be showcased on LinkedIn and resumes to demonstrate proficiency in this highly sought-after skillset.

Who is This Training For?

Built for IB Professionals, Students & Career Switchers

Incoming IB analysts preparing for their first year on the desk
First and second-year analysts building systematic AI fluency
Associates moving into deal leadership and client-facing roles
Private equity and credit professionals applying the same deal workflows
MBA students recruiting into banking or transitioning from another field
L&D teams evaluating the program for analyst class training
Career switchers moving into investment banking from non-finance backgrounds

What's included

Everything You Need to Hit the Ground Running

Reusable AI toolkit

A personal prompt library, custom GPTs, and Projects-based workspaces built during Day 1 and refined throughout — calibrated to the IB tasks participants do most often.

Comprehensive training materials

Detailed manuals and reusable Excel model templates for every session, formatted to the standards used at top IB firms.

AI output verification checklist

A task-specific verification framework covering modeling, document intelligence, and written deliverables. Built during the program, applicable immediately.

12 months of email support

Unlimited content-related questions answered by instructors for 12 months after the program.

AI for Investment Banking Certificate

Wall Street Prep's AI for Investment Banking Certificate, issued upon completion of the full three-day program.

Access to online companion content

Post-program access to WSP's online financial modeling library for ongoing reference and skills reinforcement.

All trainees get 12-month access to Wall Street Prep's self-study Financial & Valuation Modeling Program — a $499 value.

Wall Street Prep Financial & Valuation Modeling self-study program

How We Train

The Wall Street Prep Advantage

Attending a Wall Street Prep boot camp means you'll learn directly from the same instructor
-practitioners who lead intensive AI skills training at the world's leading investment banks.

The Same Intensive Training Used at Top Institutions

Wall Street Prep is the training provider of choice for incoming analyst classes at bulge brackets, elite boutiques, and leading private equity firms.

Hands-On Building, Not Passive Lectures

Every session is build-as-you-go. You leave with a working AI toolkit you built yourself: prompts, custom GPTs, and verified workflows.

Honest About What AI Can Do, and What It Can't

This program is built on real-time client intelligence that understands where AI accelerates the IB workflow and where it typically fails IB analysts in practice.

Built By the AI Thought Leaders Reinventing How Wall Street Trains

Wall Street Prep's AI training practice maintains active, hands-on expertise across every major general-purpose LLM and finance-specific AI platform - staying current on the latest functionality, model updates, and capability changes. More importantly, we know each tool's real-world limitations: where it misleads, where it requires validation, and where it is off-limits in a professional finance context.

Wall Street Prep AI Leadership

Bogdan Tudose

Head of AI & Data Science

8+ years IB training

Alastair Matchett

Head of Corporate Training

12+ years IB training

Matan Feldman

Founder & CEO

12+ years IB training

Ricardo Flores

AI Curriculum Director

8+ years IB training

The Finance Industry's Trusted Training Provider

Have Questions?

Speak with our Enrollment Team

Still have questions about the program? Schedule a short consult with one of our enrollment advisors to find out if the AI for Investment Banking Boot Camp is right for you.

Speak With an Advisor

More rigorous than I expected, they spent a good amount of time on failure modes like hallucinated figures, probably the most useful part for me.

Garrett M.

Practical training, left with resources I'll actually use again.

Betsy V.

A lot of the time actually went to judgment, like knowing when you should just rebuild something by hand instead of trusting the output.

Ari B.

Best analyst training I've been sent to, and the only one where I built something I still use.

Danielle O.

The capstone had us build trading comps and precedent transactions off a real data room, felt like an actual live deal.

Owen T.

Learned how to actually check a model's output instead of just trusting it. That was the most useful part for me.

Andrew T.

Well structured and relevant, the instructor actually knew how to teach.

Mark R.

Setting up scenario toggles and driver-based cases with AI is the part I use most now back at my desk.

Priya K.

Great overview of Rogo and Hebbia alongside Claude and Copilot, helpful to see them side by side.

Sue B.

Didn't realize the self-study modeling library access was included until partway through, that was a nice surprise.

Fatima H.

The live demo pulling historicals into a model was the single most useful fifteen minutes of day one.

Whitney C.

Great instructor and a good mix of theory and hands on work.

Julie B.

The CIM review and data room session was probably my favorite part. I use AI for diligence work now, but with an actual process behind it.

Chris G.

Appreciated the honest take on Rogo and Copilot in Excel, where they're actually useful and where they're kind of not.

Trevor S.

Practical and well organized, taught by people who've actually done the job.

Riley D.

The data cleaning and cohort analysis session was directly applicable to my job, turned a messy dataset into a real dashboard.

Michael D.

I work credit, not banking, but the covenant review and data room triage sessions mapped almost exactly to what I do.

Aaron J.

This was well organized and taught by people who clearly know the material.

Sonia C.

Loved the hands-on modeling with Claude and ChatGPT, we built debt schedules and stress tested assumptions in real time.

Megan R.

Got a lot out of the three days, and being able to email instructors for a year after is a nice add.

Colin R.

They also got into governance, like how you keep a tool accurate over time instead of just building it once and moving on.

Victor L.

Ended up with a certificate, a prompt library, and a verification checklist out of the three days, more than I expected going in.

Ibrahim K.

I've taken a few WSP boot camps now, always worth the time.

Angelina D.

Ricardo spent a good chunk of time on where AI actually helps versus where it just looks impressive. Changed how I review models now.

Helen P.

Building company one-pagers with AI saved me a ton of time, something that used to eat up most of an afternoon.

Natalie F.

Most useful training I've done, didn't feel like three days just checking a box.

Melanie E.

The agentic workflows session on day 3 was ahead of where I expected, useful for thinking about scaling beyond just me.

Thomas J.

Switching into banking from consulting, the program didn't assume I already knew the AI tools or the modeling conventions.

Nicole D.

Tying every AI claim back to a source is a habit I've already started using on live deals.

Elena V.

Honestly expected more of an AI sales pitch, but they were upfront about where it breaks and how to catch it before it gets to a VP.

Brett D.

Great pacing and materials I'll keep coming back to.

Tim V.

Setting up a Projects-based workspace with our own context loaded in was new to me, already using it at work.

Samantha B.

Second WSP boot camp I've taken and both were practical and well paced.

Courtney R.

The buyer universe screening and CIM teardown were basically real deal work, more than I expected from a training course.

George D.

Building out my own prompt library over the three days beat any generic prompt guide I've read online.

Paige M.

Hands on and relevant, the instructors know the material inside and out.

Amit P.

The capstone tied it all together, built comps, an operating model, and a football field with AI in three days.

Mike M.

The buyer and investor universe screening exercise was the closest to real deal work I've done in a training room.

Derek W.

Everything was hands on and I can use it at work tomorrow.

Dan S.

The credit agreement and covenant review exercise was new to me, useful to see AI pull covenant terms out of a huge document fast.

Kevin S.

More useful than other programs I've been through. Would recommend to anyone in the industry.

Leila A.

I was skeptical about using AI for modeling going into this, but the verification checklist we built is something I'll actually keep using.

Zachary D.

Turning our data analysis into a pitch book draft with AI was faster than I expected, still needed real editing after.

Rachel M.

Better than the internal training I've taken, the instructors bring real experience.

Jessica N.

As an associate moving into more client work, the module on tone and defensible messaging was the most relevant part for me.

Grant P.

Best training I've had on prompt libraries, we left with an actual custom GPT built during the course.

Brian T.

Covered a lot of ground without feeling rushed.

Francis C.

Building a dashboard out of a messy customer dataset on day two is the session I'll actually reuse the most.

Marcus B.

Every session was well paced and the instructor made the material easy to follow.

Brittany D.

Three days but dense, modeling, diligence, and data analysis all in one program. The capstone made it click.

Todd A.

FAQs

A three-day, hands-on training program where you build the AI-powered workflows already deployed at bulge bracket banks, elite boutiques, and leading PE firms — modeling and valuation, diligence and data, and client-ready communication, built live, not watched on a slide.
It's a direct adaptation of the same AI training Wall Street Prep runs inside JPM, Morgan Stanley, Evercore, and Blackstone, built on real client intelligence about where AI actually helps — and where it still fails — IB analysts in practice.
Incoming IB analysts, first- and second-year analysts building AI fluency, students preparing for IB recruiting, and career switchers moving into investment banking from non-finance backgrounds.
A reusable AI toolkit calibrated to the IB tasks you'll actually do (prompts, custom GPTs, and Projects-based workspaces), a verification framework for catching AI errors before they reach a VP, hands-on reps producing deal work with AI, and an AI for Investment Banking Certificate you can put on LinkedIn.
No. The program starts from fundamentals and builds toward advanced, deal-ready workflows over three days — you don't need to have used AI tools professionally before.
We recommend coming with a paid subscription to at least one frontier model so you can build alongside the instructor. Sessions are taught primarily on Claude, with demos across ChatGPT, Copilot, and Rogo so you can see how the workflows translate across tools. The skills are tool-agnostic: what you learn on one platform carries to whichever your firm deploys.
Three days: Day 1 covers modeling and valuation, Day 2 covers diligence, data, and building client-ready deliverables, and Day 3 covers judgment and output verification, scaling your work with reusable AI agents and custom GPTs, and a capstone that ties the workflows together.
Instructor-practitioners who lead the same intensive AI skills training inside the world's leading investment banks and private equity firms.
Yes — participants train alongside peers from across the industry and get 12 months of post-program email access to instructors for follow-up questions.
Participants who are unable to attend their scheduled boot camp may request to transfer their registration to a future Wall Street Prep Public Boot Camp. Requests must be submitted at least 1 week prior to the original seminar start date. Only one transfer is permitted per registration, and it must be used within one year of the original seminar date. Transfers are final and non-refundable; if the new boot camp has a higher registration fee, the participant is responsible for the difference, and no refunds or credits are issued for transfers to a lower-priced boot camp. Participants who cancel within 1 week of the seminar start date, or who do not attend without prior notice, are not eligible for a transfer or credit. Wall Street Prep reserves the right to cancel a seminar due to low enrollment or unforeseen circumstances — if it does, participants may choose either a full refund or a transfer to a future boot camp.

Investment Banking
AI Boot Camp

A Three-Day3-Day AI Intensive from
Wall Street's Training Provider

Using AI for Financial Modeling and Data Analysis

Polished Deliverables that Pass VP Review

Communication and Judgement