Artificial FP&A

By Karl Kern, Founder/President, Kern Analytics LLC

As a child, I identified the word “artificial” to playing surfaces in professional baseball and football stadiums. While growing up the word “artificial” expanded to items like sweeteners.  Now as a professional the word “artificial” applies to work.

In regard to work, the word “artificial” applies to artificial intelligence.  Simply written, artificial intelligence is machines thinking on their own.  Machines thinking on their own present a number of anxieties in the workplace.  Perhaps the most significant anxiety is the loss of work.  Loss of work within factories is more than an anxiety, it is a reality.  Loss of work within offices may become as prevalent as within factories.  These statements apply to work within facilities but can be restated into more precise terms like functions such as FP&A.

Artificial intelligence has established its presence within the financial analysis.  Many accounting software packages provide quantitative measures such as ratios and visual aids such as graphs.  Many accounting software packages also provide the ability to compare actual results to budgets, forecasts, and prior year results.  How artificial intelligence may establish its presence further is in warnings.  Artificial intelligence may warn people about trends in ratios indicating potential good or bad news.  Artificial intelligence also may warn people about drivers affecting favorable or unfavorable outcomes in measures like income and cash flows.  Through the storage of data and advancements in technology, artificial intelligence may be able to become an in-house financial analyst within many companies.

Artificial intelligence is not prominent in financial planning but has the potential to increase its role.  Artificial intelligence could develop revenue forecasts by identifying trends in sales activity.  Artificial intelligence also could develop expense forecasts by identifying fixed and/or variable cost characteristics.  In addition, artificial intelligence could develop balance sheet forecasts by assessing the amount of time a company collects cash from its accounts receivable, sells inventory, and pays bills.  These examples apply to data inside the company but perhaps artificial intelligence could go further.  Perhaps artificial intelligence could obtain data outside the company, e.g. macro and microeconomic data, to determine whether adjustments to future revenues, expenses, and/or cash flows are needed.  Like financial analysis through the storage of data and advancements in technology, artificial intelligence may be able to become an in-house financial planner within many companies.

What has been described may be mildly or extremely unrealistic but the presence of artificial intelligence cannot be ignored.  Artificial intelligence is here and is not expected to disappear.  FP&A practitioners should not ignore the role of artificial intelligence when it comes to its potential for planning and analysis.