You can’t open a professional journal, website, or news site these days without seeing articles about artificial intelligence (AI). AI, in all its many forms, offers exciting potential to many professions, including accounting. Machine learning is one branch of the overall AI “tree” that continues to expand in many directions, including Generative AI, machine learning, natural language processing, and more. In this article, we’ll help you better understand machine learning and share examples of how CFOs are tapping into the potential of this new technology.
What Is Machine Learning?
Machine learning is a branch of artificial intelligence (AI) that involves the development of algorithms and statistical models that enable computers to progressively improve their performance on a specific task through experience or data. Instead of being explicitly programmed to carry out a certain task, machine learning algorithms learn from patterns in data, allowing them to make predictions or decisions without being explicitly programmed for every scenario. Machine learning techniques are widely used in various fields such as image and speech recognition, natural language processing, medical diagnosis, financial forecasting, and many others.
Machine learning works best when there are predictable, stable patterns and large amounts of data the system can tap into for learning. Consider grammar-checking software. It is a form of machine learning software that ingests copious amounts of data (previous texts and the rules of English grammar) and checks your writing for errors. Does it make mistakes? Yes, since it may not recognize specific elements of style unique to your writing that skirt the rules of English grammar or that the context of a sentence calls for something a bit different than the norm. However, it is a useful bit of machine learning and one that we now take for granted in our word-processing programs.
Machine Learning in Accounting
Many accounting platforms have machine learning built into the system to help accountants and financial professionals do more with their data. A few machine learning examples from the world of finance and accounting include:
- Forecasting: Machine learning programs can leverage both historic data as well as current market predictions to improve forecasting. Better forecasting offers companies smarter money management, for example, or better inventory management if they can forecast supply and demand with greater accuracy.
- Fraud Detection: Manually reviewing accounts payable or receivable line by line is a thing of the past with new fraud detection tools. Because machine learning systems are good at pattern recognition, anything outside of an expected pattern can be brought to the user’s attention. These fraud detection features save many hours of tedious journal reviews and allow users to spot patterns with ease.
- Risk Management: If the system has access to large data sets, it can review past data, identify patterns around known prior risks, and help detect similar risks in the future.
- Compliance: Machine learning can augment accounting systems and provide notices, reminders, and more on key compliance issues and dates. The resulting reminders can help organizations remain compliant.
Can Machine Learning Take the Place of an Accountant?
Machine learning is, as we said, great at pattern detection. However, what to do once a pattern is detected requires the insights, skills, and experience of a professional accountant. No machine will ever replace a CFO or accountant. Instead, software that uses machine learning can help accountants complete tasks efficiently, improve predictive analytics, and prevent fraud.
Welter Consulting
Welter Consulting bridges people and technology together for effective solutions for nonprofit organizations. We offer software and services that can help you with your accounting needs. Please contact us for more information.
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