Impact of Artificial Intelligence on Accounting

Impact of Artificial Intelligence on Accounting

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Artificial intelligence is impacting all kind of industries and accounting is no exception. The growth of automated solutions particularly in various finance functions – primarily led to anxiety among financial professionals that their positions might be replaced by machines. With automation becoming more ordinary, however, it’s clear that accountants are still needed in the endeavor.

Some accounting practices are starting to employ such advanced technology to simplify their operations. The general result that they are perceiving is saving time, reducing costs, increasing productivity and providing better accuracy. This means this is hardly a trend that will fade anytime soon, so it’s better to catch up with it now rather than later.

In reality, small businesses say they are actually demanding more from their accountants and bookkeepers than ever before. In addition to the standard numbers-crunching and tax filing, accountants are expected to serve as strategic advisors to small business clients.

Rather than eliminate the human workforce in accounting firms, the humans will have new colleagues—machines—who will pair with them to provide more efficient and effective services to clients. Currently, there is no machine replacement for the emotional intelligence requirements of accounting work, but machines can learn to perform redundant, repeatable and oftentimes extremely time-consuming tasks. Here are some of the possibilities:

Auditing of expense submissions: Machines could learn a company’s expense policy, read receipts and audit expense claims to ensure compliance and only identify and forward questionable claims to humans for approval. Otherwise, machines could handle the bulk of this task.

Clear invoice payments: Today, when customers offer payment that might merge multiple invoices or that don’t match any invoices in the accounting system, it’s time-consuming for accounts receivable staff to apply for payment correctly without making a call to the client or trying to determine the right combination of invoices. However, smart machines could analyze the possible invoices and can match the paid amount to the right combination of invoices, clear out short payments or automatically generate an invoice to reflect the short payment without any human intervention.

Risk assessment: Machine learning could facilitate risk assessment mapping by pulling data from every project a company had ever completed to compare it to a proposed project. This complete assessment would be not possible for humans to do on this level and under a similar timeline.

Automated invoice categorization & Bank reconciliation: Most ERP softwares have advanced expense claims capabilities. These ERP softwares can not only scan and understand the bill through smart scanning, but also decode the type of expense claim and book it into the exact account code. It also flags policy violations and overspending.

Other ERP software can undertake bank reconciliations pretty easily. It simply matches transaction lines along with bank statement lines using specific keywords and algorithms. The only intervention of the accountant would be to sense check the recons before confirming the same.

Accounting software is getting more intelligent, performing automation as well as analysis which were formerly done by humans.
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