Accounting Meets AI: Why I’m Learning Python and Machine Learning

One may think that coding does not relate to accounting, but that could not be further from the truth. We live in an increasingly tech-driven business world, and coding is becoming a critical skill across jobs, disciplines and industries.

With new and innovative applications of AI making news seemingly every day, coding is more important than ever before. As accountants, we must strategically use technology tools to take our careers and our companies to the next level.

What better way to understand technology’s uses and benefits than by understanding a programming language software like Python to assist with our jobs?

I made the tactical decision to waive a core course in the UC Davis Master of Professional Accounting (MPAc) program and instead take a coding class, Machine Learning (ML) with Python.

I was drawn to UC Davis’s MPAc program because of its STEM-designed program. I wanted a program that would teach me the technical side of accounting, and would also train and prepare me for the operational nuances of the profession.

I earned a bachelor’s degree in accounting and have had multiple accounting internships, but I wanted to push myself outside my comfort zone and learn something new.

I had little, if any, coding background entering the MPAc program. I had only taken a business statistics course as an undergrad, which taught me some minor coding within R Studio.

However, my hope was that the ML with Python course could potentially take my coding skills to a new level and open my eyes to the world of coding and all the possibilities within technology. It would also teach me the important intricacies and topics of ML, which are important for data analysis skills.

This was a new world for me, but I was ready for the challenge. (BTW – some fun trivia to share with friends: The Dutch creator named Python not after the big snake but the British comedy series Monty Python's Flying Circus.)

Image

How Coding Relates to Accounting

Big Data is everywhere now, more than ever before, and we will continue to generate and collect data on countless metrics. Data is crucial for supporting business strategies, providing insights and making decisions. However, we cannot do anything with that data if it is not organized in a readable and presentable fashion.

Data needs to be manipulated in many forms for many needs. This is where a programming language like Python comes in, as it can be utilized to easily collect, manipulate and transform data for data analysis.

The common thought is that accountants spend hours hunched over Excel spreadsheets. However, accountants are not just crunching numbers, creating financial statements and reports. They also need to be able to look at data, analyze it and draw conclusions to support their decisions.

There are many complex problems and puzzles that arise within the accounting profession, and we must be able to use the tools available to us to draw those conclusions and perform analyses.

An auditor should use prior year’s financials, ratios and trends to determine the areas of risk for a client. A coding language processor like Python can be used for clients’ data collection and transformation, which will give accountants more meaningful and higher-quality data analyses within the business world.

Accountants Who Code Stand Out

Python can also assist accountants in automating tedious tasks, such as reconciliations, report generation and data entry, which tend to be repetitive in nature following a standard accounting month, quarter and year-end close cycles.

Rather than spending time on repetitive tasks month after month, accountants can utilize Python to create code to perform those time-consuming to-dos and can instead spend their time and skills on more meaningful decision-making and conclusion-drawing analyses.

With the skills that I have gained through the ML with Python course at UC Davis, I hope to become more efficient in my career, and allow me to elevate the type of contribution I make to my future employer.

One takeaway that I had from this class is that even if an accountant does not fully know how to code, it is important for them to be able to understand code and the ways that it can be used within the business world.

As an aspiring future accounting firm manager, it is crucial that I know how coding languages work and all their functions. I must be prepared to deploy the coding tasks to employees who may admittedly be more proficient than myself with the programming software. Understanding capabilities, use-cases and the best tools for specific tasks amongst all these complex tools is often even more valuable than performing the coding itself.

This class has proven that coding skills are not just useful for engineers. There are many ways that accountants can accelerate and elevate their career growth by expanding their skills.

The UC Davis faculty first taught us the foundations of each ML topic and how to perform the task with Python, then gave us real-world data sets to practice our newly acquired coding skills. These ML topics and coding skills can be applied to any company, career, or line of business. The coding skills that I have gained from this class are very niche but highly valuable for accountants and will contribute to my success as a future auditor.

I hope to stand out amongst my peers with my newly acquired skills.