Introduction to Investment Banking Modeling

Introduction

You're sizing or advising on a deal and need a crsip number-backed view; investment banking modeling is the set of financial forecasts and transaction analysis used to price deals and advise clients. It's built and used by bankers, corporate finance teams, private equity, and sell-side analysts to test scenarios and push decisions. The outputs drive concrete outcomes: valuation ranges, recommended deal structures, debt capacity, and projected returns scenarios, so you can defintely compare trade-offs numerically. Modeling turns financials into actionable deal decisions. Next: you - open the model, map three key assumptions (revenue growth, margin recovery, capex), and chek the base/upsides by Friday.

Key Takeaways

• Modeling converts financials into actionable deal decisions-producing valuation ranges, deal structure, debt capacity, and returns scenarios.
• Core model types: a clean three‑statement model is the foundation; use DCF for intrinsic value, LBO for sponsor returns/debt sizing, M&A accretion/dilution, and comps/precedents for market checks.
• Build robust three‑statement models by normalizing historicals, driving forecasts with revenue growth, margins, capex, working capital and tax, and fully linking statements with audit checks.
• Valuation requires projecting unlevered free cash flow, choosing a terminal method, discounting at WACC, and running sensitivity matrices-present a range, not a single number.
• Model deal mechanics and financing precisely (sources & uses, tranches, covenants, stress tests) and follow best practices: clear inputs/outputs, version control, and automated checks.

Core model types

You're building models to advise on deals or value a business; here's the direct takeaway: master a clean three-statement base, then layer DCF, LBO, and M&A mechanics, and always cross-check with market comps and precedents.

Three-statement model and discounted cash flow

Start with the three-statement model (income statement, balance sheet, cash flow). It's the foundation because every valuation and transaction flow begins with accounting that ties: profit → cash → capital structure. Build from audited FY2022-FY2024 historicals, normalize one-offs, then forecast FY2025-FY2029 drivers.

Practical steps:

• Map historical line items to consistent labels
• Forecast drivers: revenue growth, gross margin, SG&A, depreciation, capex, working capital days, and tax rate
• Link net income → cash flow adjustments → closing balance sheet; reconcile cash and equity
• Insert audit checks: balance sheet balances, cash-flow add-up, circularity flags

Example (Company Name FY2025 inputs for a DCF): revenue $1,200m, EBITDA margin 18% (EBITDA $216m), depreciation $30m, capex $40m, change in NWC -$5m, tax rate 25%. Unlevered free cash flow (FCF) for FY2025 ≈ EBITDA - dep - capex - ΔNWC - tax on EBIT. Here's the quick math: FCF ≈ $216m - $30m - $40m - ( -$5m) - tax; assume EBIT ≈ EBITDA - dep = $186m; tax ≈ $46.5m; FCF ≈ $84.5m.

DCF mechanics and best practices:

• Project 5 years of unlevered FCF, pick terminal method (Gordon growth or exit multiple)
• Choose WACC (cost of capital) carefully; example WACC 8.5% for mid-cap industrials in FY2025
• Run sensitivity table across WACC and terminal growth or terminal multiple
• Document assumptions and sources for growth and margins

What this estimate hides: small capex shifts or one-off tax items move value materially; always show ranges not a single point. One-liner: If the statements don't tie, the model can't be trusted.

Leveraged buyout model and M&A accretion/dilution

LBO and accretion/dilution are deal mechanics models - they test return targets, debt sizing, and the impact of financing on EPS. Use a transaction-focused copy of the three-statement model with new capital structure, purchase accounting, and cash waterfalls.

Practical LBO steps and controls:

• Set purchase price and purchase price allocation (goodwill, step-up to fair value)
• Structure debt tranches: senior, revolver, mezzanine; set interest rates and mandatory amortization
• Define equity check and fees; example purchase price $1,500m, equity 30% (equity $450m), debt $1,050m divided senior $800m at 7% and mezz $250m at 12%)
• Project sponsor returns to exit (year 5) using exit EV/EBITDA multiple; example exit multiple 8.5x

Here's the quick math for the example LBO: entry EV $1,500m, EBITDA FY2025 $216m. Assume stable EBITDA growth to exit year 5 of 5% CAGR → EBITDA exit ≈ $276m. Exit EV ≈ EBITDA exit × 8.5x = $2,346m. Net debt paydown and interest determine equity exit; if net debt falls to $900m, equity value ≈ $1,446m; equity multiple ≈ 3.21x, IRR ≈ 26% pa (illustrative).

M&A accretion/dilution practical checklist:

• Model pro forma shares, synergies (revenue uplift or cost saves), and integration costs
• Apply purchase accounting: goodwill and deferred tax impacts
• Compare standalone EPS vs pro forma EPS for accretion/dilution
• Stress-test funding mixes: all-cash, stock, mix - show EPS and leverage outcomes

Example accretion quick math (Company Name buyer): buyer shares 100m, buyer EPS pre-deal $1.50 (net income $150m), target net income $36m (EPS $0.36 given 100m shares). If acquisition funded 60% cash and 40% stock, and issued new shares = 40m, pro forma shares = 140m, pro forma net income ≈ $186m (plus synergies $10m) → pro forma EPS ≈ $1.39 (dilution vs accretion depends on synergies and purchase price). One-liner: Model the deal mechanics before you price the deal.

Trading comps and precedent transactions

Market-based checks (trading comparables and precedent transactions) provide a reality check and help set negotiation ranges. Use them to triangulate DCF and transaction outputs, not replace cash-flow-driven analysis.

Selection and adjustment steps:

• Choose peers by sector, size, geography, and margin profile
• Collect FY2025 metrics: revenue, EBITDA, net income, net debt, shares outstanding
• Compute multiples: EV/Revenue, EV/EBITDA, P/E; remove outliers and use median/25-75th percentiles
• Adjust for control vs minority, size discounts, and different growth/returns profiles

Illustrative FY2025 multiples and application (Company Name): peer median EV/EBITDA 9.5x, precedent deal median EV/EBITDA 11.2x. Apply to Company Name EBITDA $216m: implied EVs are $2,052m (trading) and $2,419m (precedent). Convert EV to equity value by subtracting net debt; if net debt is $300m, implied equity values are $1,752m and $2,119m respectively.

Best practices and gotchas:

• Document peer rationale; avoid sheet-level cherry-picking
• Normalize transaction multiples for timing - FY2025 comps vs deals closed in 2024-2025
• Watch double-counting: adding full run-rate synergies to both buyer and target multiples inflates value
• Show a sensitivity table across multiples and EBITDA scenarios

One-liner: Show a range, not a single number - market checks will keep your DCF from being a defintely outlier.

Building a clean three-statement model

You're about to convert FY2025 historicals into a forecast that investors and bankers can trust, and you need a repeatable playbook. Below I give the exact steps I use on live deals: collect, normalize, forecast drivers, link, and audit - with a short example using FY2025 numbers so you can follow the math.

Start with historicals, normalize one-offs, and map accounting line items consistently

Collect audited or 10‑K/10‑Q statements for FY2023-FY2025 and work off the fiscal year-end numbers. If you only have FY2025 available, make it the anchor year for trend analyses.

• Pull revenue, COGS, SG&A, D&A, interest, taxes, capex, and working capital line items.
• Normalize one-offs: remove asset sale gains, restructuring charges, or legal settlements and show them on a separate normalization schedule.
• Map accounts consistently: create a one-page mapping table that ties each source row to your model row (example: reported Freight In → COGS; Stock‑based comp → SG&A non‑cash).
• Document adjustments: state amount, reason, and where it sits in pro forma statements so reviewers see your thinking.

Example anchor (FY2025 actuals): $500,000,000 revenue; 60% COGS; $25,000,000 depreciation; $30,000,000 capex; $5,000,000 increase in working capital. Use those as your starting balances and keep the raw source files linked for auditability.

Forecast drivers: revenue growth, margins, capex, working capital days, and tax rate; link statements

Build forecasts from a few driver tables rather than from line‑item guesses. Drivers scale logically and make sensitivity analysis meaningful.

• Revenue: choose top‑down (market share × market growth) or bottom‑up (customer cohorts). Anchor Year = FY2025 $500,000,000.
• Margins: forecast gross margin then SG&A as a percent of revenue; justify movements with cost initiatives or inflation assumptions.
• Capex: tie to a capex schedule and useful lives; express as absolute dollars and as a percent of revenue for checks.
• Working capital days: model AR, INV, AP as days; convert to dollars each year to calculate delta working capital.
• Tax rate: use statutory rate adjusted for deferred items and permanent differences; for example assume a blended rate of 22%.

Link the statements every step: net income (income statement) flows into retained earnings (balance sheet) and starts the cash flow statement. On cash flow, adjust net income for D&A and non‑cash items, subtract capex, and add/subtract delta working capital to get cash from operations and ending cash.

Quick math (from FY2025 anchor): EBIT = $100,000,000; tax @ 22% → NOPAT $78,000,000; add D&A $25,000,000; less capex $30,000,000; less ΔWC $5,000,000 → unlevered FCF $68,000,000. What this estimate hides: timing of receipts, deferred tax effects, and any seasonal inventory swings.

Include audit checks: balance sheet balances, cash flow reconciliation, circularity controls

Put automated checks everywhere. If a check fails, the model should flag red and prevent further outputs until you fix the root cause. Small slips make big deal errors.

• Balance check: Assets = Liabilities + Equity each period. Create a check row equal to the absolute difference; target = $0.
• Cash reconciliation: Opening cash + cash flow from operations + investing + financing = Closing cash. Reconcile to balance sheet cash line.
• Equity reconcile: Beginning equity + net income - dividends + other equity moves = Ending equity.
• Debt and interest: link interest to the average or closing debt balance; if you create circularity (interest affects cash which affects debt), resolve with iterative calc and a clear circularity note.
• Version controls and flags: insert timestamp, model version, and a changes log row visible on the front tab so reviewers trace edits.

Controls to implement: use locked input cells, color‑code inputs vs formulas, include a assumptions panel, and build a checks dashboard with green/red flags. Watch common errors: double‑counting D&A and capex, treating stock comp as both cash and non‑cash, and wrong tax basis for deferred taxes.

If the statements don't tie, the model can't be trusted

You: build the FY2025 three‑statement model for Company Name using the anchor numbers above by Friday, December 5, 2025; Reviewer: provide written feedback by Tuesday, December 9, 2025.

Valuation mechanics and sensitivities

You're deciding a price range for a deal or investment; here's the direct takeaway: build a DCF, cross-check with market comps and precedents, and present a sensitivity surface so the buyer and CFO see risk and upside quickly.

Discounted cash flow - steps, math, and sensitivity grids

Start from FY2025 operating performance and project unlevered free cash flow (UFCF) for a 5-10 year explicit period, then value the terminal period with two methods and discount at WACC.

Steps to build the DCF:

• Pull FY2025 stat line items: revenue, EBIT, D&A, capex, change in working capital, and tax rate.
• Compute NOPAT (net operating profit after tax) = EBIT × (1 - tax rate).
• UFCF = NOPAT + D&A - capex - change in working capital.
• Project UFCF for each forecast year using driver assumptions (revenue growth, margin, capex intensity, working capital days).
• Value terminal either with Gordon growth (perpetuity) or an exit multiple on the terminal year EBITDA; report both.
• Discount all cash flows at WACC to get enterprise value (EV); subtract net debt to get equity value.

Here's the quick math with a compact FY2025 example you can follow:

• Assume FY2025 revenue $600m, EBIT margin 15% → EBIT = $90m.
• Tax rate 21% → NOPAT = $71.1m (90 × 0.79).
• D&A $12m, capex $20m, ΔNWC $5m → UFCF = 71.1 + 12 - 20 - 5 = $58.1m.
• Project UFCF forward for 5 years with explicit growth; discount at WACC (example 9%).
• Terminal value via Gordon: TV = UFCF_n × (1 + g) / (WACC - g). Use g = 2.5% as a baseline.

Best practices and checks:

• Show both terminal methods (perpetuity and exit multiple) and explain differences.
• Build a 2D sensitivity table: WACC ±200 bps vs terminal growth ±100 bps (or exit multiple band).
• Audit: ensure cash flow linkages reconcile to the closing balance sheet, and that net debt used in EV matches balance sheet cash and debt.
• Flag assumptions: if terminal growth > 3% for a mature company, call it out as aggressive.

What this estimate hides: small changes in WACC or terminal growth shift value materially; always present low/central/high cases.

Market approaches - trading comps and choosing multiples

You should use comparables to sanity-check the DCF and to show what market prices imply for the target's FY2025 performance.

Practical steps:

• Select 6-12 peers by business mix, geography, and size; prefer publicly reported FY2025 or LTM (last twelve months) figures.
• Normalize metrics: remove one-offs, use consistent EBITDA definitions, and convert currencies to the same reporting unit.
• Calculate multiples: EV/EBITDA, EV/Sales, P/E on FY2025 and FY2026 consensus where available.
• Trim outliers (e.g., top and bottom 10%) and report median and 25th/75th percentiles.
• Apply the multiple range to the target's FY2025 metric and show implied EV and equity values.

Concrete example:

• Peer median EV/EBITDA = 8.5x; target FY2025 EBITDA = $120m → implied EV = $1,020m (8.5 × 120).
• If peer median P/E = 14x and target adjusted EPS = $2.50, implied equity = $35.0/share (14 × 2.5) - reconcile to EV by adding net debt.

Adjustments and judgment calls:

• Size/illiquidity discount: subtract 10-25% on multiples for small-cap targets, unless growth justifies premium.
• Growth premium: add multiple points if consensus shows sustainably higher revenue growth vs peers.
• Leverage and capital structure: prefer EV-based multiples to avoid capital structure mismatches.
• Document your peer selection and the rationale for any manual multiple adjustment.

Precedent transactions, scenario matrices, and presenting ranges

Precedent transactions capture control premiums and deal market practice; pair them with scenario and sensitivity matrices so stakeholders see the range of fair values.

Using precedents - steps and caveats:

• Gather completed deals in the last 24 months with similar size, industry, and geography; use deal values at announcement and close dates.
• Calculate transaction multiples (EV/EBITDA, EV/Revenue) and the premium over the unaffected share price: Premium = (Offer Price / Unaffected Price) - 1.
• Expect precedent multiples to be higher than trading comps because they include control value and often synergies; quantify implied premium (e.g., 20-40% typical, varies by sector).
• Adjust for timing: translate precedent multiples into current terms by normalizing for market moves (e.g., differences in 10-year yield or sector risk) when necessary.

Scenario and sensitivity analyses - how to present them:

• Build scenarios: base (consensus drivers), downside (lower growth, margin compression), upside (accelerating growth, realized synergies).
• Run sensitivity matrices on the DCF: WACC across columns (e.g., 7.0% to 11.0%) and terminal growth or exit multiple across rows (e.g., 1.5% to 3.5%, or multiple 7x-11x).
• Show a compact table of implied equity value and per-share price across the matrix and highlight the range (25th/75th percentiles).
• Overlay comps and precedents bands on the DCF outputs to show where market and deal evidence sit relative to intrinsic value.

Example sensitivity snapshot (conceptual): if base DCF equity = $420m at WACC 9% and g 2.5%, a +100 bps WACC drops value to roughly $375m, while -100 bps increases to ~$470m. What this tells you: financing cost and terminal assumptions drive most valuation variance.

Show a range, not a single number

Owner: You: prepare the DCF with sensitivity tables using FY2025 base metrics; Reviewer: challenge peer set and precedent adjustments within three business days.

Transaction and financing considerations

LBO structure and sources & uses

You're sizing a sponsor bid or advising one, so start with the capital stack and cash needed at close. Quick takeaway: structure defines returns and constraints - get the equity check, debt mix, and uses nailed before you price the deal.

Steps to build the LBO structure

• Set the equity check as a percentage of enterprise value (EV) - common ranges: 20-40% depending on leverage appetite and sector.
• Layer debt by risk: Senior bank debt (floating rate, amortizing), Second‑lien or term B (higher spread), Mezzanine / PIK (higher cost, limited amortization).
• Define covenants: leverage (Net Debt / EBITDA), interest coverage (EBITDA / Cash interest), and minimum liquidity.
• Schedule mandatory amortization and revolver mechanics by year and tranche.
• Pick exit assumptions: hold period (typically 3-7 years) and exit multiple (use recent comps by sector).

Sources & uses checklist - map every dollar at close

• Sources: new debt tranches, sponsor equity, rollover equity from sellers, seller notes.
• Uses: purchase price (equity value + debt assumed), transaction fees, financing fees, refinancing of existing debt, working capital adjustments, and cash leftover.
• Include precise fees: legal, advisory, financing; a realistic budget example is 2-4% of purchase price for total fees.

Example sources & uses table (illustrative)

Best practices

• Model each debt tranche separately with covenants and amortization.
• Reconcile uses to cash required at close; check sponsor equity drawdown timing.
• Stress test sources for refinancing risk and revolver availability.

If you don't map sources & uses precisely, closing surprises will erode returns and credibility - defintely model every fee and working capital line.

Accretion and dilution mechanics, purchase accounting

You're pricing an acquisition for a public acquirer. Lead point: pro forma EPS and share count determine whether the deal is accretive or dilutive - model them line by line.

Concrete steps to build the accretion/dilution schedule

• Start with standalone income and share counts for acquirer and target for the last twelve months (LTM) or fiscal year 2025 data where available.
• Calculate exchange ratio for share deals or split cash vs stock consideration for mixed deals.
• Compute pro forma shares using the treasury stock method for any new share issuance and include dilution from options/RSUs.
• Adjust EBITDA and net income for recurring synergies (revenue lift and cost saves) and implementation timing - assume phased realization (year 1 30-50%, year 3 full).
• Model interest expense changes from new financing and corresponding tax shield; apply marginal tax rate to reflect after‑tax impact.

Purchase accounting and goodwill

• Calculate purchase price allocation: fair value of assets, identifiable intangibles, and assumed liabilities.
• Goodwill = purchase price paid for the target minus fair value of net identifiable assets; goodwill is non‑amortizing under US GAAP but tested for impairment.
• Amortizable intangibles (customer lists, non-competes) create straight‑line amortization charges that reduce EPS; model these explicitly.

Worked example (simple)

Practical checks

• Show EPS with and without synergies and with staggered timing.
• Explicitly model one-time deal costs in year 0 and recurring purchase accounting charges thereafter.
• Flag sensitivity: small changes in exchange ratio or synergy realization often flip accretion to dilution.

One-liner: If pro forma math doesn't show the EPS path by year 1-3, you don't understand the deal.

Stress tests: covenant headroom, rate shocks, and liquidity scenarios

You need to know when and how the deal can break. Bottom line: stress the capital structure and liquidity first - fixes are costly and time-sensitive.

Essential stress-test scenarios

• Revenue decline scenarios: run -10%, -20%, -30% and see EBITDA, cash flow, and covenant ratios.
• Interest-rate shocks: apply +100bp and +200bp to floating-rate tranches and recalc cash interest and coverage ratios.
• Capex shock: +25% in year 1 to simulate deferred maintenance or regulatory spend.
• Combined downside: revenue -30% plus +200bp rates to test correlated stress.

How to model covenants and headroom

• Encode covenant tests monthly or quarterly: Net Debt / EBITDA and EBITDA / Cash Interest are minimal standards.
• Show covenant headroom as difference between covenant threshold and pro forma metric. Example: covenant max leverage 4.5x, pro forma leverage 4.0x, headroom = 0.5x.
• Simulate covenant breach triggers and remedial actions: covenant waiver, equity cure, asset sale, or accelerated amortization.

Liquidity runway and default thresholds

• Build a 13-week cash forecast inside the LBO model to track revolver usage.
• Model mandatory amortization schedules to see when cash must be paid versus optional repayments.
• Quantify liquidity under stress: calculate months of runway before violating minimum liquidity covenant or exhausting revolver.

Example stress impact (illustrative)

Actions if stress shows breach

• Model amendment options: covenant step‑downs, restricted payments suspension, or equity cure timing.
• Quantify dilution impact of an equity cure vs value loss from a distressed sale.
• Prepare lender communication and waterfall of remedial actions in the model for each scenario.

One-liner: Model the deal mechanics before you price the deal.

Next step: You - build the sources & uses, accretion schedule, and three downside stress scenarios in the model by Friday; Reviewer/Mentor - provide feedback within two weeks.

Best practices, tools, and common pitfalls

You're building or reviewing a deal model and need it to be auditable, repeatable, and defensible - fast. Here's the quick takeaway: set strict input/output rules, version everything, and automate checks so small slip-ups don't change a billion-dollar decision.

Model hygiene and assumptions

Keep inputs and outputs visibly separate so anyone can answer Where did that number come from in under a minute. Put all assumptions on a single tab labelled assumptions, with inputs in blue and hard-coded overrides in green (common convention). Use a readonly calculations area and separate summary/output sheets for stakeholders.

Practical steps:

• List every assumption: source, unit, date
• Use consistent units (USD thousands or millions) across the model
• Document driver logic: e.g., revenue drivers → volume × price
• Keep links to source files (date-stamped) rather than pasted snapshots

Example: For a fiscal 2025 forecast, state the effective tax assumption explicitly - e.g., US federal 21% plus state, total effective tax ~ 26% - and point to the statutory source or tax memo.

If someone asks Which cell moves EPS most, you should be able to answer in one sentence.

Version control and audit trail

If you can't roll back a bad change in under five minutes, you're running blind. Save incremental files at key milestones and maintain a change log tab inside the workbook with Date, Initials, Change summary, and Impact. Use a filename convention such as ModelName_v20251130_JD.xlsx and keep a master clean build in SharePoint or an S3 bucket.

Practical steps:

• Save a major checkpoint every day and before sensitive edits
• Keep the last 10 versions; archive older ones offline
• Log every change with a one-line rationale and expected P&L/CF impact
• Use check-in/out on shared drives to avoid accidental overwrites

If you automate builds (Power Query or Python), tag generated outputs with the commit or run ID so results are reproducible.

One clean rule: never overwrite a model mid-deal without a documented rollback point - defintely avoid it.

Common errors, tools, and automated checks

Most broken models fail for a handful of repeatable reasons: unresolved circularity, wrong tax treatment, double-counted synergies, keypad-copy mistakes, or missing reconciliation lines. Build targeted checks to catch each failure mode automatically.

Concrete checks and tools:

• Balance sheet balance: Assets = Liabilities + Equity every recalculation
• Cash reconciliation: Opening cash + Cash flow from ops/inv/fin = Closing cash
• Circularity control: identify and break unnecessary iterative links; if iteration required, document solver settings
• Tax check: taxable income basis vs GAAP net income and deferred tax linkages
• Sensitivities: run WACC ± 100 bps and terminal growth ± 50 bps

Tools to reduce manual error:

• Excel: XLOOKUP, INDEX/MATCH, SUMIFS, XNPV for irregular cash flows
• Power Query: ingest and refresh feeds (consensus, pricing, FX)
• Templates: locked calculation blocks and input-only sheets
• Code checks: simple VBA or Python scripts to assert balance, sign checks, and version tags

Operational advice: run the audit suite after every set of material changes and before any external circulation; an automated preflight that takes 30-90 seconds beats manual review.

Small mistakes break big decisions.

Conclusion

You need a clear finish line: models answer the valuation, financing capacity, and returns questions that decide whether a deal proceeds. Quick takeaway: use a tied 3-statement plus DCF and LBO to produce a valuation range, debt sizing, and sponsor/issuer return scenarios.

Recap of what models must deliver

You're closing a modeling exercise and must show three outputs to stakeholders: value range, capital structure capacity, and return profiles. Start your deck with these three metrics so readers see the decision points immediately.

• Produce a valuation range (DCF midpoint ± sensitivity table).
• Show debt capacity (interest cover, covenant headroom, mandatory amortization schedules).
• Present returns (IRR or MOIC for sponsors, EPS accretion/dilution for acquirers).

One-liner: Models answer whether a deal makes economic sense, and by how much.

Next steps - a practical, timed practice plan

You need hands-on repetition with live numbers. Pick a public company, use its FY2025 reported financials as your base year, and build these models in order: three-statement → DCF → LBO. Document every assumption-sources, rates, and working capital days-so reviewers can audit quickly.

• Set a projection horizon of 5 years (FY2026-FY2030) with FY2025 as the base.
• Build 3 scenarios: base, upside (higher growth/margin), downside (lower growth/margin).
• Use a terminal-growth range of 0% to 3% and WACC sensitivity ± 200 bps.

One-liner: Practice on real FY2025 numbers, document assumptions, repeat until clean.

Learning plan and ownership with firm deadlines

You want measurable progress in 90 days. Follow a structured plan: five timed modeling exercises, peer reviews, and one end-to-end deal case study. Keep tasks short, measurable, and reviewable so feedback fixes model logic, not style.

• Schedule: 5 timed exercises (each 3 hours) over 30 days.
• Peer review: each model gets 1 peer review session (30-60 minutes) within 3 days of submission.
• Deal case study: one full deal build (3-statement, DCF, LBO, accretion/dilution) within the final 30 days.
• Audit controls: include balance checks, cash reconcile, and a sensitivity dashboard in each file.

Ownership and dates: You build the first model by Dec 14, 2025; Mentor or reviewer provides written feedback by Dec 28, 2025. If you miss the deadlines, reschedule immediately-delays mean less time for iteration and higher risk the model has hidden errors (defintely avoid that).

One-liner: Time-box practice, get fast feedback, iterate until the models are reliable.