Over the past several years, artificial intelligence (AI), alongside several other technologies, has completely changed the way financial departments are operating. In fact, some of these industry changes are happening so fast that many companies are having a tough time trying to keep pace.
This is expected, given that these technologies have an impact on almost everything, including the way these companies bank, invest their money, receive loans, or prevent financial crimes. At the very core of AI sits machine learning. It is a self-improving software that takes in data and repurposes it for its benefit and that of the company.
Here are five ways artificial intelligence will completely change the financial department.
Powered by such technologies as natural language processing (NLG) and machine learning algorithms, chatbots have become a powerful tool to provide a highly personalized and conversational experience with customers or other users from different domains.
Recently, the Bank of America introduced its chatbot, called Erica. By using the bank's mobile app, users can get in touch with Erica over voice or message to do all sorts of financial operations. It includes things like sending money, paying bills, help you with your savings, or manage your finances.
Approval workflows are based traditionally on two-dimensional matrices. They list the various conditions on which approval levels are usually triggered. However, they do not take into account broader consequences-- whether the previous requests were rejected or approved, whether the requestor role might require more supervision, or whether that is an exception usually granted in that particular scenario. But with creative approval workflows, finance teams can distinguish the real exceptions in real-time and filter them out from the low-risk ones.
With machine learning capabilities, computers can now understand and predict the numerous complexities and subtleties that take place in stock trading. In fact, artificial intelligence has become better at picking stocks than the humans involved in the market.
EquBot is one such software that is continually analyzing information from roughly 6,000 US-listed stocks. It scans through all regulatory filings, social media posts, newspaper articles, and various other financial metrics to find the most undervalued investments possible. As compared to additional actively managed funds, EquBot's daily turnover is much higher.
Finance employees have to make sure that the receipts they receive are genuine, that they match the claimed amounts, and whether they are in line with the company policy. Even with some high-tech travel-and-expense solutions, this process is still being done by hand, one claim at a time. But with AI technology, this entire process can be fully automated, and only questionable claims could be sent to a manager for approval.
With the rise in popularity of e-commerce over the past several years, so has online fraud. But fighting online fraud is not as easy as it may seem. Artificial intelligence can be of great help here. Machine learning algorithms can analyze various data points and detect fraudulent transactions much faster and more accurately than human analysts could. It will significantly improve the rate of real-time transaction approvals as well as reducing the number of incorrect declines.
Artificial intelligence and machine learning are still somewhat in their infancy, which means that there are still many hurdles to overcome. Nevertheless, the number of changes they were able to bring in such a short amount of time is only indicative of what it is to come.