There seems to be a big divide between accountants and programmers, and very few (if any) colleges offer Python development as part of an accounting degree. I’ve found that most accountants simply use standard software and get frustrated by their limitations. Considering that, are there any real-world uses for Python in accounting firms that would justify learning this skill?
Accounting firms can use Python to automate the repetitive tasks they perform every day. It has powerful data analysis capabilities and can be integrated with spreadsheets, databases, and software to simplify tasks, speed up processes, and use machine learning for accurate financial predictions.
Many people are shocked when I point out that there are online Python courses explicitly designed for accountants, but there’s a good reason for this. The finance industry, like all others, are exploring new technologies, and accountants with some coding expertise have an advantage over those without. Let me tell you about several good reasons for accounting firms to start using Python.
Automating Repetitive Tasks
As all accountants know, many accounting tasks are repetitive and time-consuming, but that doesn’t make them any less essential for accuracy and compliance. Python has powerful automation capabilities that drastically reduce the time and effort we normally put into completing such tasks, allowing accountants to focus on more strategic activities.
Processes such as data capturing, invoice processing, and generating financial reports can all be streamlined since Python can import data from various sources, populate fields in accounting software, and develop customized documents.
For example, let’s say you received 10 separate spreadsheets from a client. Each sheet contains the travel log data for one of their sales representatives. In this case, you could use a Python script to automatically scan each spreadsheet and import the data into the appropriate fields in a database or accounting software instead of manually typing it.
This enhances efficiency and accuracy while allowing you to scale your operations without increasing manual effort.
Data Analysis and Visualization
One of Python’s most significant advantages is the vast number of libraries it offers. These libraries are basically pre-built pieces of code that make it easier to program specific tasks, and some of them were made specifically to help with data analysis and presentation. Two popular ones I’ve used myself are Pandas and Matplotlib.
Pandas is a library that can simplify data processing and analysis. It can import data from just about any source you have available, including Excel spreadsheets, CSV files, and SQL databases, after which you can run algorithms to manipulate the data in various ways.
Matplotlib is a Python-based data visualization library. You can use the library to receive the analyzed data and create visual reports in your preferred style. Other tools, like Excel and PowerPoint, can do this, but you’re always limited by pre-configured styles and themes. In Python, you can code the tool to create the exact report you want and in any style you desire.
So, how would this work in real life? Using the same example as before, after extracting the travel log data from the spreadsheet, you can use Python scripts to calculate the travel expenses and rebates. Another Python script can then use Matplotlib to create a visual report to present to the client.
Financial Forecasting
Financial forecasting is a business-critical function of accounting firms since it helps businesses plan, manage risks, and make informed decisions with calculated risks. Python’s data processing and machine learning capabilities are two-notch, which makes it a dynamic tool any accountant can use to create accurate and sophisticated financial forecasts.
You can use libraries like Pandas (which we mentioned earlier) and NumPy to organize and summarize historical data and identify several key trends. Other libraries, like statsmodels and Prophet, will let you create algorithms for time series forecasting so you can develop models that will accurately predict aspects like future revenue, expenses, or cash flow.
For example, if the client in the travel log example planned to employ five more traveling sales representatives to expand their business, a Python script can combine the travel log feedback with other pieces of data, like each rep’s sales over 12 months, to create an accurate projection and forecast of the effect this move could have on the company.
Auditing and Compliance
Python can automate some parts of the auditing process by analyzing large datasets and comparing them with specific criteria to identify discrepancies using the same libraries used for data analysis. This is useful for checking for regulatory compliance. But it’s even possible to build pattern recognition algorithms into your code, which can help detect possible signs of fraud.
Essentially, if you can convert any of your auditing processes into a step-by-step formula or algorithm, you can probably create a Python script to perform that process for you.
For example, you could use the travel data provided before and run it through a separate Python script to compare each rep’s travel expenses with previous months. The script can highlight any significant discrepancies that could indicate someone using their travel allowance for personal purposes.
Custom Financial Applications
Isn’t it frustrating to have to work within the framework of pre-existing software? There are many excellent accounting software packages on the market, but they are all designed to cater to a wide range of accounting firms that all have varying needs. Most accounting firms simply choose to work around these limitations since developing their own software can be expensive.
With a bit of Python knowledge, accountants can create their own custom financial applications that provide the functions they need in a user-friendly way. Some accounting firms developed their own tax calculators, expense management apps, and financial reporting tools with the feature sets they need.
Integration
Another of Python’s most remarkable features is its ability to communicate and integrate with various other software packages. This includes most spreadsheet software, such as Excel, database applications, and many of the largest accounting software options on the market.
There are several reasons why this is useful for accounting firms:
- Application Programming Interface (API) integration: Many accounting platforms, including QuickBooks, Xero, and SAP, offer APIs (Application Programming Interfaces), enabling other applications to interact with their data. You can use Python to create your own scripts that connect to these APIs to extract, update, or synchronize data between systems.
For example, an accountant could automatically pull transaction data from a bank’s API and import it directly into the accounting software. - Data synchronization: Many companies store data in several locations, such as CRM systems, accounting databases, and payroll software. Python makes it possible to synchronize data between these different platforms quickly and efficiently.
- Custom middleware development: Middleware is software that communicates with multiple other programs and platforms to convert and share data. A Python-savvy accountant could write a custom middleware package that can export data from one system, convert it into a different format, and share it with another program in real-time.
- Workflow automation: Python can automate workflows that typically involve switching between multiple software tools. For example, a Python script could automatically download financial reports from accounting software, analyze and process the data, and upload the results to business intelligence software.
The possibilities unlocked by Python’s integration options are limitless, and new integrations are constantly emerging, unlocking even more opportunities for accounting firms to use this simple, powerful programming language.
Conclusion
Python is unbelievably easy to learn and use. When we also consider Python’s power, flexibility, and the sheer number of potential integration options, accountants have limitless opportunities for make their work easier and boost their productivity. As the world embraces new technology, I believe there is no reason why accountants shouldn’t learn to program with Python.