Intro to Machine Learning: a CPA New Brunswick Monograph

Accounting and other financial information can be viewed as a large set of structured data: hence highly amenable to machine learning, correspondingly responsive to current accounting and auditing processes, and decidedly impactful on the work that CPAs perform.

“Software is eating the world.”

Marc Andreessen, Entrepreneur, Investor, Author and Software Engineer 

The above quote, incidentally borrowed from co-founder of Netscape, reflects today’s new normal: the new reality in which software drives our economy and propels our lives. The world’s largest retailer, Amazon, has no physical stores, the largest video service by number of subscribers, Netflix, has no physical outlets or even cable networks, the world’s largest recruiting interface, LinkedIn, does not employ recruiters. These are all software companies, just like other similar disrupters such as Google, EBay, PayPal, Uber, and Airbnb to name but a few.

Accountancy is not immune to the disruptive emerging technologies embraced by the world; those reshaping the very characterization of prosperity and striking at the very foundation of the profession and its value proposition. One such technology generally categorized as Machine Learning has particular relevance to CPAs and their clients – generating extensive insights from large data sets.

Accounting and other financial information can be viewed as a large set of structured data – hence highly amenable to machine learning, correspondingly responsive to current accounting and auditing processes, and decidedly impactful on the work that CPAs perform.

It is entirely conceivable that future accounting firms will be predominantly staffed by data scientists with accounting and finance as their domain expertise.

CPA New Brunswick and its authors are not computer scientists, nor computing experts, but rather CPAs who simply wish to table this monograph (not a research paper) with its members: presenting a concise, coherent and curated account of machine learning and its limitless application. It does not present any new or original ideas on the subject and is based on countless information sources in public domain. The monograph does not assume any knowledge of programming languages or statistics and the intended audience is constituted as professional accountants... aiming to furnish them a high level, non-technical introduction to the subject; perhaps even a call to action which will in future enable CPAs to better respond to future opportunity.

The subject of machine learning is as colossal and obscure as an iceberg and we have no illusion that this monograph covers even the tip of the proverbial iceberg.

It will however hope to serve as a compass – helping to steer the drift of the accounting profession arousing further interest and deeper conversation about redefining the profession.

Please click the button below to download the full report by Kamalesh Gosalia, Ph.D., CFA, CPA, CGA and Rock Lefebvre, MBA, FCIS, FCPA, FCGA.

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About the Author

CPA New Brunswick

We are the Chartered Professional Accountants of New Brunswick (CPA New Brunswick). Our vision is for the Canadian CPA to be the preeminent, globally-respected business and accounting designation.