Machine learning and artificial intelligence are no longer just science fiction novels and movie concepts. They have become modern solutions to modern problems and they’re now changing the way companies collect and analyze data.
Because of its massive market potential, machine learning is also becoming integral in numerous industries, including the travel and expense management space, where personal and financial information is constantly changing.
From helping travelers save time by simplifying searches to helping businesses save money with more effective policy parameters, machine learning is revolutionizing what it means to manage employee bookings and expenses from anywhere in the world.
Machine learning is a subcategory of artificial intelligence. Its processes guide software applications in becoming more accurate at predicting potential outcomes—without being explicitly programmed that way. These algorithms can then use historical data to predict new output values.
For example, machine learning programs for airlines can assess all the historical data of a particular flight path—from New York to Chicago, say—and calculate a percentage of how often that flight will be on time. Travelers may see that the 2 p.m. flight is on-time 83% of the time, whereas the 5:30 p.m. flight typically has only a 57% on-time success rate.
When used correctly, this form of artificial intelligence can be a business leader’s greatest tool for making informed decisions and developing insights around the clock. According to Accenture, businesses that successfully apply artificial intelligence could increase profitability by an average of 38% by 2035.
Many legacy corporate travel and expense management tools run on older models of computing input data. For example, they will display vacant hotels in select cities, but there is no intelligent learning in that specific search; filters are manually applied. Even then, there are no behind-the-scenes processes and no optimization—just blind direction.
So, what can machine learning optimize when it comes to managing companies’ travel and expenses? Consider the following four key areas.
Machine learning can predict a booking by extrapolating data from each traveler’s previous search history, recent coworker bookings, or real-time price analyses. By connecting to a wide selection of inventory across flights, hotels, ground, and rail via APIs, employees are more likely to adopt these intuitive tools as they consistently keep them informed and up to date. The more use these tools incur, the greater visibility admins receive into trends regarding spend.
Machine learning can also calculate the median price alongside a dynamic policy for each search to ensure that travelers see the best results for themselves and their organization.
Machine learning is also used to proactively recognize when potential or on-trip travelers may benefit from additional support. Whether a support agent is automated or a live human, an intelligent solution can analyze how frequently an individual travels and then send help if someone needs extra assistance with a booking.
Companies may also leverage machine learning to notify travelers of flight delays or other travel disruptions, proactively surfacing alternative options and bringing in live human support where necessary, so travelers are never left feeling stranded while on a trip.
Optical Character Recognition (OCR) technology is a subset of pattern recognition and image processing for machine learning.
Simply put, it is the digitization of text. To help make receipts easier to capture when filing expenses, companies can employ OCR technology that captures a picture of a paper receipt and converts it into an electronic format. By doing so, employees don’t have to worry about keeping up with paper receipts and can file for reimbursements instantly with the click of a button.
Machine learning and AI can automatically analyze transactions that essentially eliminate the legacy way of filing expense reports. Transactions within a specific set of guidelines are automatically approved, and the technology can flag anything that wades out of policy.
Through machine learning, expense management software can suggest updated or additional policies that can help organizations make more informed decisions. Machine learning can also help to identify potential errors and anomalies that may indicate employee fraud.
Plus, without built-in smart policy controls, employees may book outside of policy again and again simply because of untrained software.
Time, of course, is money. For Navan, employing machine learning means saving finance leaders and teams time they would typically spend trying to book travel, file expenses, wait for reimbursements, and close books at the end of the month.
Luckily, Navan does all of the above and more through machine learning and AI-based solutions for companies globally. Machine learning isn’t about replacing humans with machines—it’s about knowing how to leverage a human interaction in the right way at the right time to get the traveler from Point A to Point B, C, and/or D as seamlessly as possible.
For Navan, smart use of this technology also means it has to be intuitive enough to offer human intervention. That’s why, if the solution flags something out-of-policy or a road warrior needs a little extra help, admins and travel support can step in at any point of the journey.
Schedule a demo today to learn more about how your company can leverage the Navan solution and reap the benefits of its machine-learning capabilities.