Financial Modelling: 7 Decisions Leaders Should Test First

A practical guide to using financial models to test cash flow, growth, hiring, pricing, debt, valuation, and risk before committing money, time, or people.

Financial modelling helps leaders test business decisions before they commit. A good model shows how assumptions about revenue, costs, cash flow, debt, working capital, pricing, and growth affect future outcomes. This guide explains how financial modelling works, which decisions to test first, and why AI makes judgement more important, not less.

A financial model is not a crystal ball!

It will not tell you exactly what will happen next year. If it could, we would all be sitting on a beach somewhere, pretending to “check emails”.

A good financial model does something more useful. It helps you test what could happen before you commit money, time, people, or reputation.

What this article covers

what financial modelling means
how financial models work
what financial modelling is used for
common types of financial models
how to build a simple financial model in Excel
the 7 decisions leaders should test first
what makes a financial model reliable
common financial modelling mistakes
whether AI will replace financial modelling
CFA vs financial modelling
whether business leaders need a financial modelling course how
financial modelling supports better decisions under uncertainty

What is financial modelling?
What is financial modelling used for?
What are the main types of financial models?
Financial modelling vs budgeting vs forecasting
How do you build a financial model in Excel?
7 decisions leaders should test first with financial modelling
What makes a financial model reliable?
What are common financial modelling mistakes?
Will AI replace financial modelling?
CFA vs financial modelling: which is better?
Do business leaders need a financial modelling course?
What this looks like in real business
Where this goes wrong
The KrisLai Decision Framework™ and financial modelling
Financial modelling under uncertainty
What you should actually do
People Also Ask
FAQ

Key Takeaways

Financial modelling is a decision simulator, not a crystal ball.
The model is only as useful as the assumptions behind it.
Leaders should use financial models to test decisions before committing money, time, or people.
Scenario analysis and sensitivity testing matter more when conditions are uncertain.
AI can speed up financial modelling, but it cannot replace leadership judgement.

What is financial modelling?

Financial modelling is the process of building a structured forecast that shows how a business may perform in the future. It usually links revenue, costs, cash flow, profit, working capital, debt, and assumptions so leaders can test decisions before committing resources.

In simple terms, financial modelling helps you answer questions such as:

What happens if sales grow?
What happens if sales fall?
Can we afford to hire?
Can we afford more debt?
Will this project make money?
How much cash runway do we have?
What happens if customers pay late?
What is the business worth?
What decision should we make next?

Investopedia describes financial modelling as creating a spreadsheet summary of a company’s expenses and earnings to calculate the impact of a future event or decision. (Source: investopedia.com)

That definition is useful, but for business leaders I would put it like this:

Financial modelling is a way to test “what could happen if…” before real money is spent.

It is not about building a spreadsheet that looks clever.

It is about improving the quality of the decision.

Definition: Financial Modelling

Financial modelling is a structured way to test what could happen if a business makes a decision. It helps leaders understand possible outcomes before committing money, time, people, debt, or other resources.

A financial model is like a business flight simulator

A financial model is like a flight simulator for business decisions.

Pilots do not use flight simulators because they know exactly what will happen in the sky.

They use them to practise what could happen under different conditions.

Bad weather.

Engine trouble.

Navigation errors.

Pressure.

A business leader uses a financial model for a similar reason.

The model lets you test decisions before real cash, people, and risk are involved.

You can ask:

What if sales are lower?
What if costs rise?
What if customers pay late?
What if we hire too early?
What if the project takes longer?
What if the loan repayments are harder than expected?

That is why financial modelling matters.

It helps you practise the decision before the business has to live with the consequence.

From spreadsheet to decision…

The value of financial modelling is not in the spreadsheet itself.

The value is in the questions the spreadsheet helps you ask.

A model should help leaders move from:

“We think this will work”

to:

“Here is what has to be true for this to work.”

That is a very different level of thinking.

The easiest way to understand financial modelling is to see it as a decision loop: define the decision, test the assumptions, review the risks, and then make a better choice.

Financial modelling decision loop showing decision, assumptions, model, scenarios, sensitivity test, risk review, and better decision. — The Financial Modelling Decision Loop shows how leaders can turn assumptions, scenarios, sensitivity tests, and risk reviews into better business decisions.

In my experience, financial models become far more useful when leaders treat them as living decision tools, not one-off spreadsheets created and forgotten.

What is financial modelling used for?

Financial modelling is used to forecast performance, test decisions, raise finance, value a business, plan cash flow, assess projects, compare scenarios, and understand risk. For business leaders, its main purpose is to improve judgement before money or resources are committed.

Financial modelling can support many decisions, including:

cash-flow planning
hiring
pricing
business growth
debt
fundraising
investment
project planning
budgeting
valuation
business sale preparation
acquisition decisions
cost reduction
stock and working capital planning
scenario planning

CFA Institute describes financial modelling as a practical skill used to analyse financial data and test strategic scenarios. Its financial modelling module includes revenue forecasting, cost modelling, working capital, debt schedules, and scenario analysis.

Source: CFA Institute, Financial Modeling

For SME leaders, the most useful financial models are usually not the most complex.

The most useful model is the one that helps you answer a real business question.

For example:

Can we afford this growth plan?
Can we survive if sales are 20% lower?
Can we take on this loan?
Is this new contract profitable?
How long will our cash last?
What happens if wages increase?
What happens if we increase prices?
What if our best customer delays payment?

A good model does not remove uncertainty.

It helps you see uncertainty more clearly.

What is Financial Modelling? Direct Answer:

Financial modelling helps leaders test decisions before they act. It is used for cash-flow forecasting, budgeting, business valuation, debt planning, hiring, pricing, project investment, fundraising, and scenario analysis. A good financial model shows how assumptions change future outcomes.

What are the main types of financial models?

The main types of financial models include cash-flow forecast models, three-statement models, budget models, scenario models, valuation models, DCF models, startup models, project models, M&A models, and debt models. SMEs usually need simpler models focused on cash, profit, risk, and decisions.

Not every business leader needs every financial model.

A small service business probably does not need a leveraged buyout model.

A private equity team might.

A growing SME may need something much more practical:

a cash-flow forecast model
a hiring model
a pricing model
a debt repayment model
a project investment model
a valuation model
a scenario model

Wall Street Prep lists several common financial model types, including three-statement models, DCF models, merger models, and LBO models.

Source: Wall Street Prep, Financial Modeling Guide

The CFO also explains common model types, including three-statement, DCF, M&A, LBO, sum-of-the-parts, and consolidation models.

Source: The CFO, Types of Financial Models

For your business, the question is not:

“How many model types do we know?”

The better question is:

“Which model helps us make the next important decision?”

Model type	What it does	Best used for	SME relevance
Cash-flow model	Shows money coming in and going out.	Liquidity and cash pressure.	Very high.
Three-statement model	Links profit and loss, balance sheet, and cash flow.	Full business forecasting.	High for larger SMEs.
Budget model	Sets the financial plan.	Annual planning and control.	High.
Scenario model	Tests different futures.	Uncertainty and risk.	Very high.
DCF model	Values future cash flows.	Business valuation.	Medium to high.
Startup model	Tests runway, growth, and funding needs.	Fundraising and early growth.	High for startups.
Debt model	Tests repayment ability.	Borrowing and finance applications.	High.
Project model	Tests one project or investment.	Equipment, expansion, or new service decisions.	High.

Financial modelling vs budgeting vs forecasting

Budgeting sets the planned financial target. Forecasting updates what is likely to happen. Financial modelling connects assumptions, drivers, and scenarios so leaders can test decisions before acting. All three are useful, but they do different jobs.

These terms are often used together.

That can make them confusing.

Before going deeper, here is a simple side-by-side comparison of budgeting, forecasting, and financial modelling so you can quickly see what each one is really for:

Comparison table showing budgeting vs forecasting vs financial modelling, including purpose, what it shows, best used for, main risk, and leadership question. — This comparison table shows the difference between budgeting, forecasting, and financial modelling, helping leaders choose the right tool for planning, monitoring, and decision-making.

In my experience, many leaders mix these three together, and that is where confusion starts. Each one has a different job, and better decisions come from using the right tool for the right question.

Here is the simple difference:

A budget says what you plan to happen.
A forecast says what now looks likely to happen.
A financial model shows what could happen if assumptions change.

That last part matters.

Because business decisions rarely happen in perfect conditions!

Tool	Purpose	Best used for	Leadership question
Budget	Sets the plan.	Targets and spending control.	What are we aiming for?
Forecast	Updates expected results.	Current business outlook.	What now looks likely?
Financial model	Tests decisions and assumptions.	Scenario planning, risk, and decision support.	What happens if we act?

A budget can tell you the target.

A forecast can tell you where you are heading.

A financial model can help you decide whether to change course.

That is why leaders should use all three, but not confuse them.

How do you build a financial model in Excel?

To build a financial model in Excel, start with the decision, gather historical data, list assumptions, forecast revenue, forecast costs, model cash flow, link key statements where needed, add scenarios, test sensitivities, and check the model for errors before using it.

You do not need to build an investment banking model to get value from financial modelling.

For many SME decisions, a simpler model is better.

The goal is not to impress another spreadsheet enthusiast.

The goal is to support a decision.

Step 1: Start with the decision

Do not start with Excel.

Start with the question.

For example:

Can we afford to hire?
Can we take on this loan?
Should we raise prices?
Should we open another location?
Can we invest in new equipment?
How much cash runway do we have?
What happens if sales slow down?

A model without a decision often becomes a spreadsheet looking for a purpose.

That rarely ends well…

Step 2: Gather historical data

Use recent, reliable information.

Gather:

sales
gross margin
direct costs
overheads
wages
debt repayments
tax
stock or working capital
customer payment timing
supplier payment timing
cash balance
budget vs actual results

You do not need perfect data.

But you do need honest data.

A clean-looking model built on weak numbers is still weak.

It just has better formatting.

Step 3: List your assumptions

Assumptions are the heart of the model.

Examples include:

expected sales growth
conversion rate
customer payment timing
price increase
wage increases
cost inflation
marketing spend
gross margin
debtor days
tax timing
loan interest
repayment terms

GOV.UK’s financial model guidance says figures, assumptions, and forecasts should be transparent, defensible, and grounded in real-world data.

Source: GOV.UK, Financial Model Essentials

That is exactly the standard leaders should aim for.

Step 4: Build revenue drivers

Revenue should not just be one guessed number.

Break it into drivers.

For example:

Revenue = Number of customers × Average order value × Purchase frequency

Or:

Revenue = Number of contracts × Monthly contract value × Retention rate

Or:

Revenue = Leads × Conversion rate × Average sale value

This helps you see what actually drives growth.

Step 5: Build cost drivers

Costs should also be linked to real drivers.

For example:

wages linked to headcount
delivery costs linked to orders
materials linked to sales volume
software linked to users
rent linked to locations
finance costs linked to debt
marketing linked to campaign spend
stock purchases linked to demand

This gives you a model that changes when the business changes.

Step 6: Add working capital

Working capital is where many models become too optimistic.

You need to include timing.

For example:

customers may pay after 30, 45, or 60 days
suppliers may need paying before customers pay
stock may need buying before sales happen
VAT and tax may be due later
growth may use cash before it creates cash

This is where many businesses get caught.

They forecast profit.

But they forget cash timing.

Useful related reading:

Cash Flow Forecasting as an Early-Warning Decision Tool

Step 7: Add debt and tax where relevant

If the decision involves borrowing, add:

loan amount
interest rate
repayment period
monthly repayments
security
fees
covenant or lender requirements

If the decision affects tax, add a tax estimate.

A model that ignores tax and debt may make a decision look better than it really is.

That is not modelling.

That is wishful thinking with columns.

Step 8: Build the cash-flow view

The cash-flow view should show:

opening cash balance
cash received
cash paid out
tax payments
debt repayments
investment spend
closing cash balance

The cash-flow line is often the most important line in the model.

Profit is useful.

Cash keeps the business alive.

Step 9: Add scenarios

At minimum, use:

cautious case
expected case
stretch case

Ask:

What if sales are 20% lower?
What if customers pay later?
What if costs rise?
What if the project is delayed?
What if a key customer leaves?
What if the hire takes longer to become productive?

Step 10: Add sensitivity testing

Sensitivity analysis tests which assumptions change the result most.

For example:

What happens if gross margin drops by 3%?
What happens if conversion rate falls from 20% to 15%?
What happens if wages rise by 8%?
What happens if debtor days move from 30 to 45?
What happens if interest rates rise?

This helps leaders see which assumptions matter most.

Step 11: Check the model

Before using the model, check:

formulas
links
totals
assumptions
dates
signs
debt repayments
tax timing
cash flow
version control
hidden hardcoded numbers

Wall Street Prep’s financial modelling guidance stresses best practices, auditability, clear model structure, and avoiding overly complex formulas.

Source: Wall Street Prep, Financial Modeling Guide

Step 12: Review and update

A model is not finished when it is built.

It should be reviewed when reality changes.

Update it when:

sales change
costs change
payment timing changes
debt changes
tax changes
customer behaviour changes
market conditions shift
new information arrives

A model that is not reviewed becomes a historical document.

Very tidy. Very calm. Not always useful.

Practical Application: Simple Financial Model Build Steps

Start with the decision.
Gather reliable historical data.
List assumptions clearly.
Build revenue drivers.
Build cost drivers.
Add working capital and cash timing.
Add tax and debt where relevant.
Build the cash-flow view.
Add cautious, expected, and stretch scenarios.
Run sensitivity tests.
Check the model for errors.
Review and update it regularly.

7 decisions leaders should test first with financial modelling

Leaders should use financial modelling to test decisions about cash flow, hiring, pricing, growth, debt, investment, and valuation. These decisions can change the financial health of the business quickly, so they should be tested before resources are committed.

Before going deeper, here is a simple overview of the seven decisions leaders should test with financial modelling before committing money, time, people, or resources:

Financial modelling infographic showing 7 decisions leaders should test first, including growth plan, hiring, pricing, debt, investment, cash runway, and business value. — This infographic shows seven business decisions leaders should test with financial modelling before committing money, time, people, or resources.

The key point is simple: a financial model becomes useful when it helps leaders test real decisions, not just produce tidy forecasts.

Yes, a financial model becomes useful when it supports a real decision.

Here are the seven decisions I would test first:

Decision 1: Can we afford this growth plan?

Growth can use cash before it creates cash. A financial model helps leaders test whether higher sales will need more staff, stock, marketing, equipment, working capital, or finance before cash comes back into the business.

Growth sounds positive.

And it can be.

But growth can also create pressure.

A business may need to spend before it earns:

hire more people
buy more stock
increase marketing
extend credit to customers
upgrade systems
buy equipment
increase management time
fund longer payment cycles

What this looks like in real business:

A business wins more work.

The leader hires quickly.

Costs rise.

Customers pay after 45 days.

Cash gets tight.

The profit forecast looks fine.

The bank balance disagrees.

The model should test:

sales growth
gross margin
staff costs
customer payment timing
supplier payments
stock or materials
tax
debt
working capital
cash balance

Decision insight:

Do not ask only, “Will growth increase revenue?”

Ask:

“Can we afford the cash timing of this growth?”

Useful related reading:

Financial Mistakes: 10 Warning Signs That Hurt Cash Flow

Decision 2: Can we afford to hire?

A hiring model should test salary, payroll costs, equipment, training, management time, productivity delay, expected revenue contribution, and cash-flow impact. The key question is not only whether the person is needed, but whether the timing is financially safe.

Hiring decisions are often emotional.

The team is busy.

Everyone is stretched.

Customers are waiting.

The leader thinks:

“We need someone now!”

That may be true.

But the model should test the cost before the commitment.

Include:

salary
National Insurance and payroll costs
pension
recruitment fee
training
equipment
software
supervision time
productivity delay
expected revenue contribution
cash-flow effect
downside scenario

Example:

A new hire costs £38,000 salary.

The full cost may be closer to £48,000–£55,000 after payroll costs, equipment, training, software, and management time.

If the hire takes six months to become fully productive, the early cash impact may be heavier than expected.

The model should answer:

What revenue must this hire support?
How long before the hire pays back?
What happens if sales are slower?
What happens if the hire does not work out?
What happens if cash gets tight in month three?

Decision insight:

A hiring decision is not just a people decision.

It is a cash-flow decision.

Decision 3: Should we change our pricing?

A pricing model helps leaders test how price changes affect revenue, margin, customer demand, profit, and cash flow. A price rise may improve margin even if some volume is lost, but leaders should model the trade-off before acting.

Pricing is one of the most powerful decisions in business.

It is also one of the most avoided.

Many leaders fear that customers will leave if prices rise.

Some might.

But the model helps you see how much volume you can afford to lose before the price rise becomes a problem.

Example:

Current situation:

1,000 units sold
price: £100
variable cost: £60
contribution per unit: £40
total contribution: £40,000

New price:

price rises to £110
variable cost stays £60
contribution per unit becomes £50

If volume falls to 850 units:

850 × £50 = £42,500

Even with fewer sales, total contribution improves.

That does not mean every price rise works.

It means you should test the maths before relying on fear.

Decision insight:

A pricing model helps leaders move from “customers might leave” to “how many could leave before this becomes a bad decision?”

Useful related reading:

Customer Intent Marketing

Decision 4: Can we take on more debt?

A debt model helps leaders test whether the business can afford repayments under normal and difficult conditions. It should include interest, fees, repayment timing, cash-flow pressure, downside scenarios, and how debt affects flexibility.

Debt can be useful.

It can fund equipment, growth, working capital, or acquisition.

But debt also creates fixed commitments.

The lender still expects payment when sales are slow, customers pay late, or costs rise.

Funny how lenders are not always moved by “the market felt strange this quarter”.

A debt model should include:

loan amount
interest rate
repayment period
monthly repayment
fees
security
tax impact
debt service cover
cash-flow impact
downside case

Ask:

Can we pay this loan if sales are 15% lower?
Can we pay it if customers pay later?
Can we pay it if costs rise?
What cash balance remains after repayments?
What other options do we lose by taking this debt?

Decision insight:

Debt should be tested against cash flow, not just confidence.

Useful related reading:

Business Credit Score: 7 Ways to Build Borrowing Power

Decision 5: Is this project or investment worth it?

A project model helps leaders test whether an investment is likely to return enough value for the cash, time, and risk involved. It should include upfront cost, expected income, running costs, payback period, cash timing, risks, and opportunity cost.

A new project can look exciting.

New equipment.

New system.

New location.

New product.

New service.

New market.

A new reason to hold another meeting…

But the model needs to ask:

What is the upfront cost?
What is the monthly cost?
What revenue could it create?
What margin could it create?
When does cash come back?
What could go wrong?
What else could this money do?
What is the payback period?
What is the downside case?

Example:

A business wants to spend £60,000 on equipment.

Expected benefit:

£8,000 extra monthly contribution
£2,000 extra monthly running cost
net monthly benefit: £6,000

Simple payback:

£60,000 ÷ £6,000 = 10 months

That looks good.

But now test:

What if extra sales take three months to build?
What if running costs are £3,500?
What if the equipment needs training?
What if cash is needed for tax?
What if demand is lower?

Decision insight:

A project model should not only show the upside.

It should show what has to be true for the upside to happen.

Decision 6: How much cash runway do we have?

A cash runway model shows how long the business can operate before cash becomes too tight. It should include cash in the bank, expected receipts, monthly spending, customer payment timing, debt, tax, planned investment, and different sales scenarios.

Cash runway is not only for startups.

Any business can benefit from knowing how long cash will last under different conditions.

The basic formula is:

Cash Runway = Cash Available ÷ Monthly Net Cash Burn

Example:

Cash available: £120,000

Monthly net cash burn: £20,000

Runway:

£120,000 ÷ £20,000 = 6 months

But be careful.

That simple formula only works if cash burn is steady.

In real business, cash changes because of:

customer payments
tax
supplier timing
debt repayments
stock purchases
seasonality
delayed projects
unexpected costs

So build three scenarios:

expected runway
downside runway
severe downside runway

Decision insight:

Cash runway is not a panic number.

It is an early warning signal.

Useful related reading:

Cash Flow Forecasting as an Early-Warning Decision Tool

Decision 7: What is the business worth?

A valuation model helps leaders estimate business value using future cash flows, EBITDA, profit, growth, risk, debt, and market assumptions. It is useful for selling a business, raising investment, buying another business, or understanding value drivers.

Business valuation can feel mysterious.

But at its heart, valuation is about future value, risk, and evidence.

A model may include:

revenue forecast
EBITDA
profit
cash flow
working capital
debt
growth rate
risk
valuation multiple
DCF assumptions
buyer expectations

A simple valuation model might use:

Estimated Enterprise Value = EBITDA × Valuation Multiple

But a more detailed valuation may use discounted cash flow, often called a DCF model.

The important point is this:

A valuation model is only as credible as its assumptions.

If the forecast is too optimistic, the valuation will be too optimistic.

If cash flow is weak, the valuation may suffer.

If customer concentration is high, risk increases.

Decision insight:

A valuation model should not only ask, “What is the business worth?”

It should ask:

“What would make the business worth more or less?”

Useful related reading:

EBITDA Explained: 7 Uses and 5 Risks for Business Leaders

Business Valuation Under Uncertainty

What makes a financial model reliable?

A reliable financial model is clear, transparent, consistent, easy to audit, and built around defensible assumptions. It should separate inputs, calculations, outputs, and scenarios so leaders can understand what changed, why it changed, and what it means for the decision.

A model does not need to be beautiful.

It needs to be useful.

Useful means:

easy to understand
easy to update
easy to check
linked to the decision
based on clear assumptions
built on reliable data
able to show scenarios
able to show cash impact
not hiding important risks

GOV.UK’s financial model guidance stresses that a robust model should be transparent, defensible, and grounded in real-world data.

Source: GOV.UK, Financial Model Essentials

I would use this simple structure:

Inputs

These are the assumptions you can change.

Examples:

sales growth
prices
wages
costs
payment timing
interest rates
tax
debt
stock
marketing spend

Calculations

These are the formulas.

They should be clear and consistent.

Avoid hiding important logic inside overly complex formulas.

If a formula needs a small map and a snack break to understand, it may need simplifying.

Outputs

These are the results.

Examples:

revenue
profit
cash flow
cash balance
debt
margin
break-even point
valuation
runway

Scenarios

These show different futures.

Examples:

cautious
expected
stretch
severe downside
delayed growth
higher cost case

Checks

These help catch errors.

Examples:

balance sheet balances
cash does not go negative without warning
formulas copy correctly
totals match
dates align
debt repayments are included
tax is not forgotten
no hidden hardcoded figures

Key Insight

A reliable financial model does not make the future certain. It makes the assumptions, risks, and trade-offs easier to see.

What are common financial modelling mistakes?

Common financial modelling mistakes include weak assumptions, over-optimistic forecasts, broken formulas, hidden hardcodes, no cash-flow view, no downside scenario, poor version control, circular references, and treating the model as certainty rather than a decision-support tool.

Financial models can be helpful.

They can also be dangerous.

A bad model can give leaders confidence in a poor decision.

That is worse than having no model at all!

At least with no model, you know you are guessing.

With a bad model, you may think you are being analytical.

Very dangerous. Very spreadsheet-shaped.

Common financial modelling mistakes to avoid

Building the model to justify a decision already made
Using over-optimistic sales assumptions
Ignoring customer payment timing
Forgetting working capital
Leaving out tax
Underestimating costs
Ignoring debt repayments
Using hidden hardcoded numbers
Making formulas too complex
Failing to include a downside scenario
Not testing key assumptions
Using poor version control
Not checking formulas
Trusting AI output without review
Treating the model as certainty

Warning: The Model Is Not the Decision

A financial model supports a decision. It does not make the decision for you. Leaders still need to challenge assumptions, review risks, and judge whether the result makes sense in the real business environment.

The mistake I see most often

In my experience, the biggest mistake is not a broken formula.

It is weak assumptions.

The model may be mathematically correct but commercially unrealistic.

For example:

sales growth is too high
customer payment timing is too fast
costs are too low
hiring works too smoothly
the project starts too quickly
customers behave perfectly
cash pressure is ignored

The model says the plan works.

Reality says, “Interesting theory.”

Will AI replace financial modelling?

AI will not remove the need for financial modelling. It will speed up parts of the work, such as formula building, summaries, data handling, and draft models. But leaders still need judgement, assumptions, review, scenario thinking, and accountability for the decision.

AI is already changing financial modelling.

Tools such as Microsoft Copilot, Claude in Excel, and AI-assisted finance tools can help with:

formulas
summaries
model structure
data clean-up
scenario drafting
chart creation
error checking
documentation
explaining outputs
comparing assumptions

ICAEW has discussed how AI can augment financial modelling in Excel as Copilot and Claude-style tools become more advanced.

Source: ICAEW, Augmenting Financial Modelling with AI

CFI also now teaches AI financial modelling with Claude in Excel, including model structure, valuation, sensitivity analysis, and audit best practices.

Source: CFI, AI Financial Modeling with Claude in Excel

But AI does not remove responsibility.

AI can help build the model.

It does not know whether your sales assumption is sensible.

It does not know whether your customers will pay late.

It does not know whether your team can deliver the project.

It does not know whether a supplier is becoming unreliable.

It does not know whether the decision fits your strategy.

That is still leadership work.

How leaders should use AI in financial modelling

Use AI to help with:

drafting model structure
checking formulas
explaining variances
summarising scenarios
creating charts
testing assumptions
spotting missing items
improving documentation

Do not use AI as a replacement for:

judgement
ownership
data quality
assumption review
scenario thinking
professional advice
common sense

The future of financial modelling is not “AI instead of leaders”.

It is better models, faster checks, and stronger human judgement.

That is the opportunity.

Caution: AI Can Make a Wrong Model Look Very Polished

AI can help build and explain financial models, but leaders must still check the assumptions, formulas, data, and outputs. A polished model can still be wrong if the business logic is weak.

CFA vs financial modelling: which is better?

CFA and financial modelling serve different purposes. CFA is a broad professional finance qualification covering investment knowledge, ethics, analysis, and portfolio management. Financial modelling is a practical skill for building forecasts, valuations, cash-flow models, and decision-support tools. The better choice depends on your goal.

This is a common comparison.

But it is not really a fair “which is better?” question.

It depends on what you need.

Option	What it is	Best for	Best question to ask
CFA	A broad finance and investment qualification.	Investment careers, analysis, portfolio management, and professional finance knowledge.	Do I need a recognised finance qualification?
Financial modelling	A practical skill for building decision-support models.	Forecasting, valuation, cash flow, fundraising, debt, pricing, and business planning.	Do I need to test real business decisions?

For most SME leaders, the practical skill matters more than the credential.

You do not need to become a professional analyst to use financial modelling well.

But you do need to understand enough to ask better questions.

That is the leadership skill.

Do business leaders need a financial modelling course?

A financial modelling course can help if leaders need to understand forecasts, cash flow, valuation, fundraising, or business planning. But the best course is not always the most advanced one. Leaders should choose based on the decisions they need to make.

Instead of asking:

“Which is the best financial modelling course?”

Ask:

“What decision do I need to understand better?”

A course may help if you need to learn:

Excel modelling basics
cash-flow forecasting
three-statement models
budgeting and forecasting
valuation
scenario analysis
sensitivity analysis
model auditing
startup modelling
debt modelling
investor-ready models

But leaders should not confuse course completion with decision skill.

A course gives you tools.

Real business gives you consequences.

Both matter.

What to learn first

If you are a business leader, I would learn in this order:

How financial statements connect
Cash-flow forecasting
Revenue and cost drivers
Working capital
Scenario analysis
Sensitivity analysis
Debt and tax impact
Valuation basics
Model checking
AI-assisted modelling and review

When to get expert help

Get help if the model supports:

fundraising
bank finance
business sale
acquisition
major investment
restructuring
board decision
legal or tax-sensitive decision
complex debt
investor due diligence

A leader does not need to build every model personally.

But the leader should understand the assumptions well enough to challenge the model.

That is where decision quality improves.

What this looks like in real business

A growing business may use financial modelling to test whether it can hire, invest, borrow, or expand without creating cash pressure. The model should show how the decision affects revenue, costs, cash flow, risk, and timing under different scenarios.

Imagine a growing service business.

Sales are rising.

The owner wants to:

hire two people
increase marketing
buy new equipment
take on a business loan
improve systems
expand into a new area

The plan sounds sensible.

But the model shows a few risks:

customers pay after 45 days
hiring costs arrive before revenue improves
marketing takes three months to convert
loan repayments start immediately
equipment creates upfront cash pressure
tax is due in the same quarter
one large customer accounts for 30% of revenue

Insight:

The plan may still be good, but the timing is risky.

Real example:

The leader originally planned to do everything in one quarter.

The financial model shows cash could go negative in month four if sales are 15% lower than expected or customers pay late.

Decision:

The leader stages the plan.

First, improve marketing conversion.

Then hire one person.

Then buy equipment after cash targets are met.

Debt is delayed until the cash-flow forecast is stronger.

Consequence:

Growth is slightly slower, but safer.

The business avoids a cash crunch, protects confidence, and makes decisions from signals rather than pressure.

Real Business Lesson

A financial model should not be used to prove that a preferred decision is right. It should be used to test whether the decision still works when reality becomes less convenient.

Where this goes wrong

Financial modelling goes wrong when leaders use the model to justify a decision they already want to make. Weak assumptions, missing cash-flow timing, no downside case, too much faith in AI, and poor review can turn a useful model into a confident mistake.

What I’ve seen is that models often fail for human reasons before they fail for technical reasons.

People want the decision to work.

So the assumptions become friendly.

Sales grow smoothly.

Costs behave politely.

Customers pay on time.

The new hire performs quickly.

Debt feels manageable.

The project starts on schedule.

The spreadsheet becomes a very charming optimist.

The problem is that business does not always behave like that.

Common ways financial models go wrong

the model is built after the decision has already been made
assumptions are not challenged
there is no downside case
cash flow is ignored
tax is forgotten
working capital is missing
AI output is trusted without review
formulas are too complex
nobody owns the model
the model is not updated
version control is poor
leaders focus on profit and ignore cash

Failure Point: The Spreadsheet Agrees Too Easily

If a model only confirms what leaders already wanted to do, it is not being used properly. A useful financial model should challenge the decision, not simply decorate it.

The KrisLai Decision Framework™ and financial modelling

The KrisLai Decision Framework™

A practical model for better business decisions in complex environments. It focuses on four essential elements:

Human Behaviour — how people actually think and decide
Signals — what people are trying to do right now
Environment — whether the system supports good decisions
Consequences — what happens next, and after that

Strong decisions consider all four — not just one.

Financial modelling fits the KrisLai Decision Framework very well.

Human Behaviour

Leaders can become overconfident.

They can avoid bad news.

They can look for numbers that support the decision they already like.

They can fear missing out.

They can trust a polished model too quickly.

Signals

A financial model should help leaders read signals such as:

cash flow
gross margin
conversion rate
debtor days
customer retention
cost increases
debt repayments
working capital
cash runway
forecast variance

Environment

The model should reflect real conditions, such as:

customer behaviour
supplier pressure
AI-driven market change
lender expectations
inflation
competition
hiring difficulty
payment timing
uncertainty

Consequences

A poor financial decision can lead to:

cash shortfall
hiring too early
weak debt cover
missed opportunity
delayed investment
pressure on staff
damaged trust
slower growth

This approach is part of the KrisLai Decision Framework, a practical method for improving business decisions.

Better decisions come from understanding behaviour, signals, environment, and consequences.

This connects closely to how I think about decisions more broadly in the KrisLai Decision Framework™.

Financial modelling under uncertainty

Financial modelling is most useful when the future is uncertain. Leaders should use scenarios, sensitivity analysis, pre-mortems, value-of-information thinking, and regular reviews to test decisions under different conditions before committing cash, people, debt, or time.

Business decisions rarely happen in calm conditions.

AI is changing search behaviour.

Customers compare more.

Costs move.

Markets shift.

Talent is harder to find.

Lenders ask sharper questions.

Cash timing matters.

That is why a single forecast is not enough.

Use the model to test different futures.

Scenario planning

Build at least three cases:

cautious case
expected case
stretch case

Ask:

What if sales are 20% lower?
What if costs rise by 10%?
What if customers pay later?
What if funding takes longer?
What if a key customer leaves?
What if the model is wrong?

Sensitivity analysis

Test which assumptions matter most.

Examples:

price
margin
conversion rate
wages
debtor days
interest rate
customer retention
sales volume

Pre-mortem thinking

Before committing, ask:

“If this decision fails, what probably caused it?”

That question helps reveal hidden risks.

Value of information

Ask:

“What information would reduce uncertainty enough to improve the decision?”

Sometimes the best decision is not “yes” or “no”.

It is:

“Find out more before committing.”

Monitor-and-adapt reviews

Set trigger points.

For example:

hire only if revenue stays above a set level for three months
increase marketing only if conversion rates hold
take on debt only if cash stays above a minimum level
delay expansion if debtor days rise
pause investment if margin falls below target

As the Swedish saying goes: “Lagom är bäst.”

It means, “The right amount is best.”

That is a useful idea for financial modelling.

Do not overcomplicate the model.

Do not ignore the model.

Use enough detail to improve the decision.

What you should actually do

Start with one decision, not a blank spreadsheet. Decide what you need to test, list the assumptions, build simple revenue and cost drivers, model cash flow, add scenarios, test the key risks, and review the model before committing resources.

This is the practical process I would follow.

Step 1: Write down the decision

Use one clear sentence.

Examples:

Should we hire a new operations manager?
Should we take on a £100,000 loan?
Should we raise prices by 8%?
Should we buy new equipment?
Should we open another location?

Step 2: List the assumptions

Write down what must be true.

Include:

sales growth
pricing
customer demand
conversion rate
payment timing
costs
wages
debt
tax
working capital
project timing

Step 3: Build a simple model

Start with:

revenue
direct costs
gross profit
overheads
net profit
cash in
cash out
closing cash balance

Add detail only where it improves the decision.

Step 4: Add scenarios

Use:

cautious
expected
stretch

Do not only model the future you want.

Model the future you may get.

Step 5: Test the most sensitive assumptions

Find out what changes the result most.

Ask:

What if sales are lower?
What if costs are higher?
What if customers pay late?
What if the hire takes longer to pay back?
What if the project starts slowly?

Step 6: Review the result

Ask:

Does the decision still work?
What is the cash-flow risk?
What could make it fail?
What information do we need?
What should we monitor?
What trigger tells us to pause?

Step 7: Decide the next action

Possible actions:

proceed
delay
reduce the scale
run a pilot
gather more information
change the timing
get expert advice
reject the decision

Practical Application: Financial Modelling Decision Checklist

Before using a financial model to make a decision, check:

What decision is the model testing?
Who owns the model?
What historical data is being used?
What assumptions drive the result?
How are revenue and costs calculated?
Is working capital included?
Are tax and debt included where relevant?
Does the model show cash flow?
Are there cautious, expected, and stretch scenarios?
Has sensitivity testing been done?
Have formulas and links been checked?
What trigger tells us to pause or review?
What action follows from the model?

Financial modelling and AI search

AI tools can now answer “what is financial modelling?” very quickly.

They can explain model types, list formulas, and suggest templates…

That means a basic definition alone is no longer enough.

Useful content must help people act.

That matters here.

Financial modelling can influence debt, hiring, valuation, investment, cash flow, and business survival.

That is why I have not just explained modelling.

The aim was to help leaders use modelling responsibly.

AI can draft a model.

But leaders still need to decide:

which assumptions matter
what risks to test
what information to trust
what trade-offs to accept
what action to take

Over time, I’ve found that good decisions rarely come from data alone. They come from understanding people, reading signals, creating the right environment, and thinking beyond the immediate outcome.

That is why I write about how better decisions are made in business — combining strategy, behaviour, and practical thinking.

Research and experience note

This article is based on practical experience, independent research, and analysis and synthesis of financial modelling, business forecasting, cash-flow planning, AI-assisted modelling, and decision-making under uncertainty.

Useful reference sources include:

Investopedia: Financial Modeling Explained

GOV.UK: Financial Model Essentials

CFA Institute: Financial Modeling

Wall Street Prep: Financial Modeling Guide

Corporate Finance Institute: AI Financial Modeling with Claude in Excel

ICAEW: Augmenting Financial Modelling with AI

FAQ

What is financial modelling?

Financial modelling is the process of building a structured forecast that shows how a business may perform in the future. It links assumptions about revenue, costs, cash flow, debt, working capital, and profit so leaders can test decisions before committing resources.

What is financial modelling used for?

Financial modelling is used for cash-flow forecasting, budgeting, business valuation, fundraising, debt planning, pricing, hiring, project investment, scenario analysis, and risk review. Its main purpose is to help leaders make better decisions before spending money or committing resources.

What are the main types of financial models?

The main types of financial models include cash-flow forecast models, three-statement models, budget models, scenario models, DCF models, valuation models, startup models, debt models, project models, M&A models, and LBO models. SMEs usually need models focused on cash, profit, risk, and decisions.

How do you build a financial model in Excel?

To build a financial model in Excel, start with the decision, gather historical data, list assumptions, build revenue and cost drivers, include working capital, add cash flow, create scenarios, test sensitivities, check formulas, and review the outputs before acting.

What is a three-statement financial model?

A three-statement financial model links the income statement, balance sheet, and cash-flow statement. It helps leaders see how revenue, costs, profit, assets, liabilities, debt, working capital, and cash flow interact over time.

What is sensitivity analysis in financial modelling?

Sensitivity analysis tests how changes in key assumptions affect the model’s results. For example, it can show how profit or cash flow changes if sales fall, costs rise, margins shrink, customers pay later, or interest rates increase.

What are common financial modelling mistakes?

Common financial modelling mistakes include weak assumptions, over-optimistic forecasts, broken formulas, hidden hardcodes, missing cash-flow timing, no downside scenario, poor version control, no model review, and treating the model as certainty rather than decision support.

Will AI replace financial modelling?

AI will not fully replace financial modelling. It will speed up formula building, summaries, data handling, model drafting, and error checks. But leaders still need judgement, assumption review, scenario thinking, business context, and accountability for the final decision.

Is CFA better than financial modelling?

CFA and financial modelling are different. CFA is a broad finance and investment qualification. Financial modelling is a practical skill for building forecasts, valuations, cash-flow models, and decision-support tools. The better choice depends on your goal.

Do business leaders need a financial modelling course?

A financial modelling course can help business leaders understand forecasts, cash flow, valuation, fundraising, and decision support. But leaders should choose a course based on the decisions they need to make, not just the course brand or technical complexity.

Build Deeper Insight

Financial modelling connects closely to cash flow, forecasting, budgeting, valuation, business credit, EBITDA, and decision-making under uncertainty.

These related articles may help you go deeper:

Related Decision-Making Articles

Financial modelling is not only a finance skill. It is also a decision-making skill. These articles support the wider thinking behind better business decisions:

Conclusion and final thoughts: use the model to test the decision

A financial model is not there to predict the future perfectly.

It is there to help leaders test decisions before they become expensive.

Used well, financial modelling helps you see:

what must be true
what could go wrong
what changes the outcome most
how cash flow is affected
where uncertainty sits
what action makes sense next

The best leaders do not use financial models to avoid judgement.

They use them to improve judgement.

I help people make better business decisions through psychology, strategy, and practical thinking. Financial modelling fits that perfectly because it sits at the point where numbers, assumptions, behaviour, risk, and action meet.

Your Next Step

Choose one important decision and model it before you commit.

Pick one decision about hiring, pricing, debt, growth, investment, cash runway, or valuation. Write down the assumptions, build a simple cash-flow view, and test cautious, expected, and stretch scenarios.

This one step will help you move from hope to evidence before money, time, or people are committed.

Download the KrisLai Decision Framework™ Guide

If you want a practical way to think through business decisions, download my free KrisLai Decision Framework™ guide.

It will help you look at decisions through four simple lenses: behaviour, signals, environment, and consequences.

Use it before major choices about cash flow, growth, hiring, pricing, debt, valuation, investment, marketing, operations, and AI.

Financial pressure rarely begins with one dramatic event. It usually starts with small signals that are easy to miss.

Enter your email below and I’ll send you the free KrisLai Decision Framework™ guide, a practical model for understanding behaviour, signals, environment, and consequences before problems become more expensive.

It is designed to help leaders think more clearly and act earlier when timing, pressure, and uncertainty begin to build.

Business Thinking Hub

If you enjoy exploring the ideas behind better business decisions, you may find the Business Thinking Hub useful.

If you enjoy exploring the ideas behind different marketing strategies, you may find the Business Thinking Hub useful.

About the author

Kris Lai is a business operator and managing director with experience in land and building surveying, facilities management, logistics, and service delivery.

Earlier in his career, he worked as a Search Engine Evaluator (via Lionbridge, supporting Google), where he assessed search result relevance, user intent, and content quality using structured evaluation frameworks. This experience gives him a rare, practical understanding of how search systems interpret signals and make ranking decisions.

In parallel, whilst working with a charity organisation, he has delivered 1000’s of structured presentations in English, Finnish, and Chinese to audiences ranging from small groups to more than 600 people, and has spent decades mentoring and developing others. This experience informs his approach to clarity, communication, and decision-making under pressure.

He writes about AI, search behaviour, business strategy, and decision-making from a practical, real-world perspective.

A practical guide to using financial models to test cash flow, growth, hiring, pricing, debt, valuation, and risk before committing money, time, or people.

A financial model is not a crystal ball!

It will not tell you exactly what will happen next year. If it could, we would all be sitting on a beach somewhere, pretending to “check emails”.

What this article covers

Table of Contents

What is financial modelling?

A financial model is like a business flight simulator

From spreadsheet to decision…

What is financial modelling used for?

What are the main types of financial models?

Financial modelling vs budgeting vs forecasting

How do you build a financial model in Excel?

Step 1: Start with the decision

Step 2: Gather historical data

Step 3: List your assumptions

Step 4: Build revenue drivers

Step 5: Build cost drivers

Step 6: Add working capital

Step 7: Add debt and tax where relevant

Step 8: Build the cash-flow view

Step 9: Add scenarios

Step 10: Add sensitivity testing

Step 11: Check the model

Step 12: Review and update

7 decisions leaders should test first with financial modelling

Decision 1: Can we afford this growth plan?

Decision 2: Can we afford to hire?

Decision 3: Should we change our pricing?

Decision 4: Can we take on more debt?

Decision 5: Is this project or investment worth it?

Decision 6: How much cash runway do we have?

Decision 7: What is the business worth?

What makes a financial model reliable?

Inputs

Calculations

Outputs

Scenarios

Checks

What are common financial modelling mistakes?

Common financial modelling mistakes to avoid

The mistake I see most often

Will AI replace financial modelling?

How leaders should use AI in financial modelling

CFA vs financial modelling: which is better?

Do business leaders need a financial modelling course?

What to learn first

When to get expert help

What this looks like in real business

Where this goes wrong

Common ways financial models go wrong

The KrisLai Decision Framework™ and financial modelling

Human Behaviour

Signals

Environment

Consequences

Financial modelling under uncertainty

Scenario planning

Sensitivity analysis

Pre-mortem thinking

Value of information

Monitor-and-adapt reviews

What you should actually do

Step 1: Write down the decision

Step 2: List the assumptions

Step 3: Build a simple model

Step 4: Add scenarios

Step 5: Test the most sensitive assumptions

Step 6: Review the result

Step 7: Decide the next action

Financial modelling and AI search

Research and experience note

People Also Ask

FAQ

What is financial modelling?

What is financial modelling used for?

What are the main types of financial models?

How do you build a financial model in Excel?

What is a three-statement financial model?

What is sensitivity analysis in financial modelling?

What are common financial modelling mistakes?