Does every financial professional need programming skills? Some would say yes.

With the release in 2015 of the second series of the American Institute of Certified Public Accountants’ (AICPA) Audit Data Standards, the AICPA asked the question, “Should Accounting Students Learn to Code?” (1) The question, related to new or existing CPAs/CAs, keeps coming up – from the CPA Canada (2), ICAEW (3), and others. 

Now with guidance on the need to up the game in Audit Data Analytics (4), the days of being able to simply create macros in Excel or leverage tools like Tableau (5) may be coming to an end. And it is free software with names like R (6) or Pandas for Python (7) that seem to be leading that pack.

I am not a programmer (although “I play one on tv”.) I cut my modelling teeth with Lotus 1-2-3 nearly 40 years ago. When I was creating forecasts in Lotus, the day flew by. I’ve done some mini-programming here and there: macros, of course; a year developing proprietary point-of-sale integration tools with Basic for Unix; a few years developing VBA solutions in Microsoft Access. Still, I deny being a developer (and developers would say I am an accountant, albeit a “technical” one, and not a developer); however, recapturing that original thrill is something I have felt again recently. 

The University of Illinois at Urbana-Champaign-Urbana offers a course through Coursera called Accounting Data Analytics with Python. Geared toward accountants and not programmers, it introduces an integrated environment for writing, testing and executing programming code, intermixed with documentation, called Jupyter Notebook.

Jupyter Notebook is a coding and documentation tool. Not a hard core programming environment, it lets you document text using a markup method called Markdown and intersperse the text with others “cells” in which you create and run your code. With Python add-ons, you can automate tasks such as pulling information from PDF trade documents, CSV export files from accounting systems, or reading, analyzing, and updating Excel spreadsheets.

Certainly, learning Python or R may not be relevant to everyone. You may have other resources to help you “automate the boring stuff” or do more complex analyses of your clients’ data to be competitive. Artificial intelligence may advance quickly enough that our computers can interpret our interests and code for us. But you, or people in your organization, may take to these free tools and help your organization be more competitive and agile.

(1) https://www.aicpa.org/interestareas/accountingeducation/newsandpublications/should-accounting-students-code.html

(2) https://www.cpacanada.ca/en/business-and-accounting-resources/other-general-business-topics/information-management-and-technology/publications/coding-important-for-cpas

(3) https://ion.icaew.com/technews/b/weblog/posts/should-accountants-be-able-to-code-in-r-and-python

(4) https://www.cpacanada.ca/en/business-and-accounting-resources/audit-and-assurance/canadian-auditing-standards-cas/publications/audit-data-analytics-resources

(5) https://www.journalofaccountancy.com/issues/2020/mar/microsoft-excel-vs-tableau.html

(6) https://www.r-project.org/

(7) https://pandas.pydata.org/