So you’re an accountant and you want to become a financial analyst? First thing’s first: know you have a huge advantage with a background in debits & credits. Many financial analysts don’t bother to understand double-entry accounting at all.
On the other hand, you may find it difficult to conceptualize forward-looking, predictive analytics that financial analysts perform based on their understanding of business drivers.
Personally, I became a financial analyst in a multinational firm with no background in finance. I spent a lot of time honing my analytical skills and refining my knowledge of accounting, at which point I moved into a senior level role. I’ve also worked with two accountants on their transition into financial analysis. It is totally possible, and it’s very rewarding. But it requires work.
The good news is you don’t need to spend $100s or $1,000s on generic courses, not knowing if the curriculum is applicable in the real world. Instead, there is a small set of analytical exercises, basic math, and basic stats that you need to learn. The rest is practice, practice, practice. Most of these skills come with time — you just need to take the right steps.
This article outlines 11 steps to transition from accounting to financial analysis, and it focuses on building skills to bring value to your organization. To outline these steps, we will also cover the major differences between the professions.
11 Steps
This article is long (~4,000 words). It’s very thorough, but you may not be interested in each step. Here they are in list form to help you navigate:
- Step 1: Don’t Get a “Professional Certificate”
- Step 2: Get Better in Excel by Incorporating INDEX & MATCH, Goal Seek, and Pivot Table Calculated Fields
- Step 3: Don’t Use Your Mouse – Use Keyboard Shortcuts Instead
- Step 4: Practice Forecasting by Understanding Business Drivers
- Step 5: Get Comfortable with Net Present Value & Activity Valuations
- Step 6: Practice Building Cash Flow Statements with the Indirect Method
- Step 7: Learn how to Make 3-Statement Financial Models
- Step 8: Practice Building Simple Financial Models for Various Industries
- Step 9: Practice Building Detailed Models for Your Industry
- Step 10: Learn Variance Analysis
- Step 11: Learn Data Tools such as Tableau and Power BI
How to Transition from Accounting to Financial Analyst
In short, transitioning from accountant to financial analyst requires learning 3-statement financial modeling, valuation techniques such as Net Present Value (NPV), forecasting methodologies, and an overall analytical spirit centered on business drivers.
Step 1: For the Love of God, Don’t Get a “Professional Certificate”
Albert Einstein’s famous quote, “Try not to become a person of success, but a person of value,” is extremely appropriate here. Many financial analysts spend uncanny amounts of time and money on professional certificates such as the CFA, the CFP, and the FRM. While I can’t speak for all of them, it has been my experience that these certifications do not directly create value. They’re simply ways to get your foot-in-the-door.
The reason is that successfully completing them has very little impact on the value you can bring to an organization. This is worth repeating: completing certifications has very little impact on the value you bring to a company.
For the most part, certifications position themselves as the theoretical counterpart to in-the-field experience. But careers are not built on theory from certifications — they’re built on value from practical skills. And it takes a lot of time and practice to nail the practical skills. Why waste any on the theory? You’ll pick it up as you go.
Moreover, coming from accounting you probably already have the theory you need to be successful. Don’t get me wrong, having a certificate doesn’t prevent you from bringing value, but it doesn’t guarantee it. There are too many examples to count, and only 62% of CFOs, for example, have advanced degrees.
Do not feel like you need a certificate to be a successful financial analyst. Instead, feel like you need to bring value. The remaining steps are all focused on hard skills that result in good decision-making within an organization — the fundamental value of a financial analyst.
Differences to Note Between Accounting & Financial Analysis
The key difference in professional certificates is that accounting certifications, such as the CPA, are often considered more practical in nature than certifications for finance.
Step 2: Get Better in Excel by Incorporating INDEX & MATCH, Goal Seek, and Pivot Table Calculated Fields
If you didn’t already know, spreadsheets are the essential software program for finance. In most organizations, the spreadsheet software is Microsoft Excel, though there are free alternatives such as Google Sheets and LibraOffice.
Being a good financial analyst, and something that sets one apart from a good accountant, means building extremely user-friendly financial models in spreadsheets. And good models means good formulas. While you may already be familiar with basic formulas, you might not know INDEX & MATCH combos, Goal Seek, and Pivot Table Calculated Fields. Let’s look at each.
INDEX & MATCH as Alternative to VLOOKUP
When we want to identify a value in a table based on one or more criteria, our first instinct is to use VLOOKUP. I want to convince you that this is not ideal, and that you should use INDEX & MATCH instead. Why? Because the INDEX & MATCH method is faster, allows more flexibility on matches, and makes error checking easier.
For example, consider the following dataset:
Imagine you want to find the Price for the ISBN 989-28-79-43574-5. You could use =VLOOKUP(A5,$A$1:$H$10,8,FALSE) (colors added for visual aide). This would return the correct value of 23.99. However, Excel takes more time to make this calculation because it is highly dynamic; Excel needs to look at an entire array and computate two directions of cells to return one formula.
Using INDEX/MATCH allows Excel to break down the same calculations in two formulas. In this example, the formula would be =INDEX($A$1:$H$10,MATCH(A5,$A$1:$A$10,0),MATCH(H1,$A$1:$H$1,0)). This may look complicated, but we’ll see with some examination that it’s much more flexible than VLOOKUP.
In short, the INDEX formula asks for an array, a column number, and a row number. We provide the array directly, then use MATCH for the row and column numbers.
This is more flexible than VLOOKUP because we can modify both the row and column numbers by linking to a cell outside the table. By modifying these cells directly, we can change the output of the formula. While this is technically possible in VLOOKUP as well, it’s harder for the user to interpret. There’s a simplicity to the INDEX/MATCH setup, and this simplicity makes it easier to check for errors.
Moreover, if we want to detect values that are greater or less than the MATCH input value, we have the choice with the MATCH function. This is not possible with VLOOKUP. In the MATCH formulas above, you’ll note the last argument is “0.” Zero indicates an exact match, -1 indicates greater than match, and 1 indicates a less than match. We’ll see these in use in the section on Goal Seek.
Also, quite simply, INDEX/MATCH typically calculates 3% faster than VLOOKUP.
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Goal Seek
In the course of computations in Excel, we often want to determine an input value based on a desired output value. When our input value is run through a series of calculations to arrive at the output value, it’s no small matter of arithmetic — it’s a serious computation problem.
This is where Goal Seek comes in handy. For example, imagine you want to calculate the gross salary necessary to arrive at a net salary. The challenge is that taxes on gross salary are not a single percent but the result of progressive calculations on tranches of income.
In this case, the Goal Seek output is gross salary and our desired value is net salary. We build the calculations through which gross salary is run, then reverse engineer the values. Here’s what they setup looks like:
Here it is with the underlying formulas (download the Excel here to explore in depth):
As you can see, the calculation for net taxes is entirely based on formulas referencing the gross salary amount and the tax brackets table on the left. Taxes are progressive, which means each portion, or tranche (“Bottom – Top” in the image), is calculated at the given rate. The active tranche is the one in which the salary maxes out, and only the portion earned in that tranche gets calculated.
Imagine now, that we want to know how much brut salary we need to earn exactly $50,000 in net salary. Goal seek will do this for us — see a the short clip below:
Pivot Table Calculated Fields
As an accountant, you’re probably familiar with pivot tables. But in finance, we’re often dealing with data from non-accounting sources, and these may have entire fields on which we need to make simple calculations per row. Calculated fields in pivot tables are an excellent way to do so.
For example, imagine again our database of of books and authors:
Let’s say we want to find out the price per page of each book. We could create a new field in the data source that divides Price by Pages, but that would be modifying the dataset. We want to avoid touching the source data as much as possible to protect its integrity.
Instead, let’s put it in a pivot table, with ISBN as rows and Pages and Price as values. Once we’ve done that, we’ll navigate to PivotTable Analyze > Fields, Items, & Sets > Calculated Fields and input the following calculation:
The result will be a clean PivotTable Field that looks like this:
Pretty cool, right?
Differences to Note Between Accounting & Financial Analysis
It’s hard to say which spreadsheet skills accountants need vs financial analysts, but for the most part, advanced data analytics are in the finance domain. As an accountant, you’ll need to learn these in to transition.
Step 3: Don’t Use Your Mouse – Use Keyboard Shortcuts
Step 3 is easier said than done. As a general principle, you should learn to use the keyboard instead of the mouse in order to move more quickly through a spreadsheet. To do so, you’ll need keyboard shortcuts. Here are ten very common ones:
- Cntrl + Arrows: Skip to the end of a range of data or through blanks to the next non-empty cell
- Cntrl + Page Up/Down: Move from one spreadsheet to the next
- Alt > H > O > I: Autofit column width
- Alt > H > B > O: Set a bottom border
- F2: Enter cell, toggle to edit and choose cell with arrows
- ESC: Exit cell without modifying it/cancel changes to a cell
- Cntrl + Shift + Arrow: highlight cells in a range
- Cntrl + H: Replace
- Cntrl + F: Find
- Alt > E > S > Down Arrow > Down Arrow > Enter: Paste copied cells as values
Differences to Note Between Accounting & Financial Analysis
As an accountant you may already be familiar with many of these keyboard shortcuts. The key difference is that financial analysts incorporate keyboard shortcut speed as a measure of performance, whereas accountants may not consider them with such esteem. This dynamic, of course, depends on the team and organization.
Step 4: Practice Forecasting by Understanding Business Drivers
With the exception of adjusting entries for asset impairment and bad debt, accounting focuses on current and past results. Finance, on the other hand, concerns itself with current and future results.
Specifically, a key to transitioning from accounting to finance is understanding how to project the business’ financial statements. In its simplest form, projections can be simple assumed growth rates. In a more complicated form, they can be dynamic relationships between CoS and revenue, with capital expenditures informing the direction of growth.
The key to projections is ensuring they make sense given the specific business model of the company. It is not sufficient to say, “assume growth or decline by 10%.” You need to develop the direction based on business drivers.
A very simple example of business drivers can be found in online retailers. We can break down their growth into (1) number of visitors, (2) conversion rates, and (3) average spending. If the number of visitors is a direct result of ads on other websites or organic traffic through pages ranking high on search engines (SEO), then the ultimate business drivers are (1) advertising and (2) SEO. Given an amount of investment in these metrics, we can project the performance of the whole company.
While showing a full example is outside the scope of this article, you can check out what a complete financial model looks like here.
Differences to Note Between Accounting & Financial Analysis
Again, with the exception of adjusting entries for asset impairment and bad debt, accounting focuses on current and past results. Finance, on the other hand, looks forward.
Step 5: Get Comfortable with Net Present Value & Activity Valuations
The time value of money is a key concept for financial analysts. If you’re not already familiar, it simply means that money today is worth more than the same money in the future. Why? Because we can invest it now and get paid interest.
This concept is especially important for valuations. Finance has to calculate the the value of projects based on their earning potential, and the only way to compare projects or estimate the value of an acquisition is to consider what those projects are worth in the present day using Net Present Value (NPV).
In short, Net Present Value (NPV) look at the value of future cash flows, discount them with a given rate, and add this value to the initial outlay. If the outcome is positive, the project is profitable. If negative, the project is not profitable. Take a look at this example (included in the downloadable Excel):
The XNPV formula shown looks at the values of future and current cash flows in their net present value. The rate we’re using is 0.84% because that is the interest we could earn with 100% certainty with US treasury bonds. If we can make that interest on the money now, why would we invest in anything that doesn’t give us the same return or greater?
As you can see, the fictitious $41,013 values for each year in the future is the minimum amount needed to break even (I used Goal Seek to determine it). If there’s even $1 less in any of the years, the project will not be worth more than investing in treasury bonds.
The full mathematical formula for net present value is NPV = ∑(CF/(1+r)ˆn), where CF is cash flows in a period, r is the discount rate, and n is the period number. Luckily Excel takes care of this for us with XNPV.
Differences to Note Between Accounting & Financial Analysis
Accountants sometimes use NPV to determine the value in use of an asset as part of asset impairment and other adjustments, but it is otherwise absent in accounting. However, net present value is an almost-daily tool for financial analysts.
Step 6: Practice Building Cash Flow Statements with the Indirect Method
Everyone knows it — cash is king. In addition to constructing the P&L and balance sheet, accountants may often rely on software to construct the cash flow statement. In general, companies have the choice between (1) the direct method of cash flows and (2) the indirect method.
The direct method consists of all cash inflows and outflows on a company’s bank account(s), but it is rarely used in practice. The indirect method, however, is very popular.
In short, the indirect method consists of a calculation that starts with net profit (P&L) and adds back non-cash expenses such as depreciation and amortization (P&L). It then uses changes in working capital (receivables and payables) to show money that has not been transferred but has been recognized (B/S). Third, it looks reduces the cash amount by any major investing activities in large financial assets (B/S). Finally, it increases cash by any loans taken out (B/S).
This is a manual exercise performed in Excel, the reason being that any small nuances in balance sheet and P&L accounts must be considered and manually adjusted by the financial analyst. The cash flow statement that accountants often build with software usually either lacks manual adjustments or is not constructed in a presentable form.
While a full example and explanation for how to construct the cash flow statement is outside the scope of this article, I show you how to create one for Amazon in Excel Guide: How to Prepare Cash Flows with the Indirect Method.
Differences to Note Between Accounting & Financial Analysis
Accountants sometimes use a software program or ERP to construct the cash flow statement within a company. Financial analysts, however, often recreate it as simple, presentable form for presentation to management and for decision-making using NPV (discussed above).
Step 7: Learn how to Make 3-Statement Financial Models
The holy grail of financial analysis is financial modeling of a company’s financial statements. Financial models include both historical and projection data. They’re constructed based on a logic around operational business drivers, capital expenditures, and debt & equity financing.
While the core of financial models are the three financial statements, we need to use both assumptions for many line items and supporting schedules for long term assets and liabilities. The structure of a financial model looks something like this once complete:
The first run at building one of these models is always tough. Don’t get discouraged — it’s one of those topics that takes to time before it “clicks.”
You have 5 sections (headers in blue in the above image):
- Assumptions
- Income Statement
- Balance Sheet
- Cash Flow Statement
- Supporting Schedules
This is a sophisticated topic that requires some time and investigation to learn. I won’t show an example here, but you can learn how to build a 3-statement model while projecting cash flows in 3 & 12 Month Cash Flow Projection: Excel Guide & Template.
Differences to Note Between Accounting & Financial Analysis
To my knowledge, accountants never build financial models. Instead, they feed historical data to financial analysts who produce the models in Excel or other spreadsheet software.
Step 8: Practice Building Simple Financial Models for Various Industries
Once you’re familiar with the structure of a basic financial model, you can start to test building them across various industries. Don’t get too detailed with the these. The point here is that you want to build your intuition around how different industries function, develop personal tricks for your model, and start to see where eventual weaknesses can appear.
You can do this easily by downloading public company filings from the SEC’s EDGAR database. You simply need to identify a company of interest, navigate to its latest 10-K and click on the blue “Interactive Data” button. It’s not always in the same spot, but here’s what it looks like:
From there you can download an Excel of all the financial statements and build models quickly without burdensome data collection and cleaning. At AnalystAnswers.com, I’m working to create courses and task-based learning packets so you can ensure your results are correct — stay tuned.
Step 9: Practice Building Detailed Models for Your Industry
Once you’ve built some simple models for various industries, you’ll want to investigate building complex models in the industry you want to work in. Simple models are great for learning, but you’ll need to push your understanding further if you to bring real value to a company. Since most companies require highly-detailed models for decision-making, this is a must.
What makes a “complex” model different from a simple one? In most cases, complexity arises from the supporting schedules portion of the model. Detailed depreciation & amortization schedules with dynamic capital expenditures year-over-year, as well as complex rolling credit facilities and long term debt, can make a financial model very complex.
By learning how the industry works with these items, you will be able to bring huge value to the company.
Step 10: Learn Variance Analysis
Along with projections, valuations, and modeling, variance analysis is a key finance activity. What is variance analysis? In short, it’s explaining why one period’s number is different from either the budgeted number or the previous period’s number.
Imagine, for example, you had projected revenue for December 2021 at $100,000. In December 2020, the value had been 91,000, so you had projected roughly 10% growth. However, the actual number was $110,000. Great news! The company outperformed its budgets.
But why? Management will want to know what they did right to attain the higher value. Financial analysts need to go back to basics and examine the company’s business drivers to understand exactly what changed to allow the company to generate higher revenue.
For example, it could be that the cost of sales increased by the same 10% growth and direct costs stayed the same. In this case, the conclusion of variance analysis would be that increased cost of sales drove revenue variance to budget.
Obviously, it’s not always this easy. That’s why financial analysts need to really understand how a company works from a financial perspective — it’s business drivers.
Differences to Note Between Accounting & Financial Analysis
The difference here is simple. Accountants are not concerned with future performance and therefore do not perform variance analysis like financial analysts.
Step 11: Learn Data Visualization Tools such as Tableau and Power BI
In this article we’ve only talked about finance skills insofar as they relate to financial data — the information coming from accountants. However, more and more financial analysts are working with transactional data; that is — data coming directly from a non-finance database. In simple terms, we can refer to this as “commercial” data.
Commercial data and financial data are different in a few ways. Most importantly, commercial data is built in a database structure rather than a ledger structure.
Databases consist of multiple data tables that can all be joined on one or more unique IDs. This makes them extremely flexible and extremely useful for analysis (read more about data structure here).
Financial data and its ledgers, however, are not built on the same logic. Ledgers are not as complete and join-able as database tables.
Financial analysts often use commercial data to deep dive into their investigation of business drivers and opportunities for growth. To do so, analysts need more than the small computing powers of Excel. They need to learn data tools such as Tableau and Power BI.
Tableau and Power BI are data visualization tools that allow analysts to slice and dice large amounts of data without needed to learn a coding language. They work on logic similar to that of Excel Pivot Tables, but allow much more flexibility and the ability to create new database fields with sophisticated formulas.
Personally, I prefer Tableau to Power BI. You can download a free version of the software called Tableau Public here. I’ve written some troubleshooting articles about Tableau so you can get a feel for the tool. I’ll have task based packets and courses soon — stay tuned for that.
If you’re someone who likes to learn by playing with tools, start by downloading the Tableau Bookstore Excel here. Once you’ve got Tableau Public on your desktop, connect the Excel by navigating to Connect > Microsoft Excel to link the Bookstore data. Then drag one of the tables into the filed titled “Drag tables here.” From there move to the indicated “Sheet 1” tab and start playing!
Differences to Note Between Accounting & Financial Analysis
Because Tableau is not made for ledger databases, accountants typically don’t use it as often. However, for financial analysts of the future, skills in data visualization software will be a prerequisite.
Conclusion
It is entirely possible to switch from an accountant to financial analyst. You already understand the fundamentals of accounting data, which gives you a huge advantage. By addressing the 10 steps in this article, you will learn the necessary skills to bring value to an organization as a financial analyst. It will require some work, but I think you’ll find the transition is well worth it.
If you found this article useful, feel free to check out more content on data, finance, and business analysis at the AnalystAnswers.com homepage!
