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cfo-advisor

Financial leadership advisor for CFOs on financial planning, fundraising, investor reporting, unit economics, cash management, and financial operations. Use when building a financial model, preparing for fundraising due diligence, designing investor reporting packages, calculating unit economics, managing cash runway, or planning month-end close processes.

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CFO Advisor

The agent acts as a fractional CFO, providing financial strategy and operational finance guidance grounded in SaaS benchmarks, GAAP standards, and investor expectations.

Workflow

  1. Establish financial baseline -- Collect current ARR, burn rate, cash balance, and headcount. Calculate runway in months. Validate that the data is recent (within 30 days).
  2. Build unit economics -- Calculate CAC, LTV, CAC Payback, LTV:CAC ratio, NRR, and Burn Multiple using the formulas below. Flag any metric outside benchmark ranges.
  3. Construct financial model -- Build a 3-year model following the Revenue Build and Expense Build structures. Document all key assumptions explicitly.
  4. Design investor reporting -- Configure the Monthly Metrics Package template. Set up the Board Financial Presentation slide structure for quarterly use.
  5. Set up cash management -- Build the 13-week cash flow forecast. Establish the monthly rolling forecast. Verify minimum 6-month runway is maintained.
  6. Establish close cadence -- Implement the Month-End Timeline (Day 1-12). Assign owners to each quality checklist item.
  7. Assess risk posture -- Review market, credit, and operational risk categories. Confirm insurance coverage is adequate for company stage.

SaaS Unit Economics

CAC = (Sales + Marketing Spend) / New Customers
CAC Payback = CAC / (ARPU x Gross Margin)

LTV = ARPU x Gross Margin x Customer Lifetime
LTV:CAC Ratio = LTV / CAC                        Target: > 3:1

Logo Retention = (Customers End - New) / Customers Start
Net Revenue Retention = (MRR End - Churn + Expansion) / MRR Start

Burn Multiple

Burn Multiple = Net Burn / Net New ARR

< 1.0x   Excellent efficiency
1.0-1.5x Good efficiency
1.5-2.0x Average
> 2.0x   Needs improvement

Rule of 40

Rule of 40 = Revenue Growth % + Profit Margin %

> 40%   Strong performance
20-40%  Acceptable
< 20%   Needs attention

Monthly Metrics Package

FINANCIAL HIGHLIGHTS
- Revenue: $X.XM (vs Plan: +/-Y%)
- Gross Margin: XX% (vs Plan: +/-Y%)
- Operating Loss: $X.XM (vs Plan: +/-Y%)
- Cash Balance: $X.XM
- Runway: XX months

REVENUE METRICS
- ARR: $X.XM (+Y% QoQ)
- Net New ARR: $XXK
- NRR: XXX%
- Logo Churn: X.X%

EFFICIENCY METRICS
- CAC: $X,XXX
- CAC Payback: XX months
- Burn Multiple: X.Xx

Board Financial Presentation

  1. Financial summary (1 slide)
  2. Revenue performance (1-2 slides)
  3. Expense breakdown (1 slide)
  4. Cash flow and runway (1 slide)
  5. Key metrics trends (1 slide)
  6. Forecast outlook (1 slide)

Revenue Build (Financial Model)

  1. Starting ARR / customers
  2. New logo assumptions (by segment)
  3. Expansion rate
  4. Churn rate
  5. Pricing changes
  6. Segment mix

Expense Build (Financial Model)

  1. Headcount plan (by department)
  2. Comp and benefits
  3. Contractors
  4. Software / tools
  5. Facilities
  6. Marketing programs
  7. Travel and events

Budget Categories

| Category | Line Items | |----------|-----------| | Revenue | New business (by segment), expansion, renewals, professional services | | Cost of Revenue | Hosting/infrastructure, support, PS delivery, payment processing | | OpEx | Sales & Marketing, R&D, G&A |

Month-End Close Timeline

| Days | Activity | |------|----------| | 1-3 | Transaction cutoff | | 3-5 | Reconciliations | | 5-7 | Accruals and adjustments | | 7-10 | Management review | | 10-12 | Final close |

Quality Checklist: Bank reconciliation, revenue recognition, expense accruals, prepaid amortization, deferred revenue, intercompany elimination, flux analysis.

Revenue Recognition (ASC 606)

  1. Identify the contract
  2. Identify performance obligations
  3. Determine transaction price
  4. Allocate price to obligations
  5. Recognize revenue when satisfied

SaaS considerations: Subscription vs usage revenue, implementation services, professional services, multi-year contracts, discounts and credits.

Cash Management

13-Week Cash Flow: Week-by-week projections of all known inflows/outflows. Review weekly. Maintain minimum cash buffer.

Monthly Rolling Forecast: 12-month forward view covering revenue collection timing, payroll, vendor payments, debt service, and CapEx.

Treasury Principles: Maintain 6+ months runway, preserve capital, optimize yield on idle cash, follow investment policy.

Cash Preservation Levers (when extending runway):

  1. Hiring freeze
  2. Vendor renegotiation
  3. Discretionary spend cuts
  4. Payment term extension
  5. Revenue acceleration
  6. Bridge financing

Due Diligence Data Room Checklist

Financial data:

  • [ ] 3 years historical financials
  • [ ] Monthly P&L by segment
  • [ ] Balance sheet and cash flow
  • [ ] ARR/MRR cohort analysis
  • [ ] Customer unit economics
  • [ ] Revenue recognition policy
  • [ ] AR aging
  • [ ] AP summary

Projections:

  • [ ] 3-5 year financial model
  • [ ] Key assumptions documented
  • [ ] Sensitivity analysis
  • [ ] Use of funds breakdown
  • [ ] Path to profitability

Financial Risk Categories

| Risk Type | Key Concerns | |-----------|-------------| | Market | Interest rate exposure, FX exposure, customer concentration | | Credit | Customer creditworthiness, AR aging, bad debt reserves | | Operational | Internal controls, fraud prevention, systems reliability |

Example: Series-A SaaS Financial Snapshot

A Series-A company ($3M ARR, 35 employees, $12M raised) preparing for Series B:

Unit Economics:
  CAC: $22K  |  LTV: $88K  |  LTV:CAC: 4.0x  |  CAC Payback: 16 months
  NRR: 115%  |  Logo Retention: 90%  |  Gross Margin: 78%

Burn:
  Monthly burn: $350K  |  Net new ARR/month: $180K
  Burn Multiple: 1.9x (average -- needs improvement for Series B)
  Cash: $5.2M  |  Runway: 15 months

Rule of 40:
  Revenue growth: 95% YoY  |  Profit margin: -40%
  Score: 55% (strong)

Board recommendation: Raise in 6 months at current trajectory.
  Target metrics for raise: Burn Multiple < 1.5x, NRR > 120%.

Essential Insurance Policies

D&O, E&O, Cyber liability, General liability, Workers compensation, Key person insurance.

Scripts

# Unit economics calculator
python scripts/unit_economics.py --metrics data.csv

# Cash flow projector
python scripts/cash_forecast.py --actuals Q1.csv --assumptions model.yaml

# Financial model builder
python scripts/fin_model.py --template saas --output model.xlsx

# Investor metrics dashboard
python scripts/investor_metrics.py --period monthly

References

  • references/financial_modeling.md -- Model building guide
  • references/saas_metrics.md -- SaaS metrics deep dive
  • references/accounting_policies.md -- Policy documentation
  • references/audit_prep.md -- Audit readiness guide

Tool Reference

financial_health_scorer.py

Comprehensive SaaS financial health assessment: Rule of 40, burn multiple, LTV:CAC, CAC payback, NRR, magic number, and composite score with investor-readiness verdict.

# Run with demo data (Series A SaaS)
python scripts/financial_health_scorer.py

# Quick assessment with key metrics
python scripts/financial_health_scorer.py --arr 3000000 --revenue-growth 95 --profit-margin -40 --burn 350000 --cash 5200000 --nrr 115 --gross-margin 78 --headcount 35

# From JSON file
python scripts/financial_health_scorer.py --input financials.json

# JSON output
python scripts/financial_health_scorer.py --input financials.json --json

burn_rate_calculator.py

Models burn rate, runway under 5 scenarios (current, hiring freeze, 10% cut, 20% cut, revenue acceleration), generates 13-week cash flow forecast, and identifies action triggers.

# Run with demo data
python scripts/burn_rate_calculator.py

# Quick calculation
python scripts/burn_rate_calculator.py --cash 5200000 --revenue 250000 --expenses 600000 --headcount 35

# JSON output
python scripts/burn_rate_calculator.py --json

scenario_modeler.py

Three-scenario financial projection engine with probability weighting, sensitivity analysis, and decision triggers. Projects b

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