AI can help streamline, touching every aspect of expense management, including:
Capturing expense data. Inputting expense data can be riddled with errors; you might misread expense receipts, transfer across incorrect dates, etc. But at Payhawk, our OCR technology, including an AI camera, extracts all these details automatically, making the initial phase of the process speedy and error-free.
Verifying invoice details. Trying to spot discrepancies in data with the human eye alone? Then, it’s really easy to miss important things such as supplier details or matches between the goods received and your original purchase order. But with the help of three-way matching, we automatically compare your invoice to your receipt note and purchase order to ensure you don’t pay out the incorrect amount.
Real-time visibility into spending patterns. And AI support doesn’t stop there; it extends to automatic expense categorisation on the reporting side of expense management. Automatically categorising your expenses makes real-time spend visibility much more efficient and effective, letting you quickly spot spend patterns and address them before they cause budget damage.
And many, many more.
The risks of using AI in expense management
Although AI is helpful, sometimes, the recommendations you get need just a little clarification. You might think, “How did it generate that particular number or suggestion?”
Taking this suggestion at face value without context can be difficult and can mean digging deeper to see if the suggestion can be trusted, defeating the purpose of using AI in the first place.
Instead, you need a reliable AI expense management solution to help generate short explanations of where the recommendation has come from.
How Payhawk is demystifying AI: Our feature in a nutshell
You rely on accurate expense data to make impactful business decisions, but how can you ensure the reliability of the AI suggestions and autofill fields?
Our new expense automation tooltips feature gives users more context by popping up next to AI suggestions. They make it clear where the suggestion comes from and improve visibility into how we used AI to create it.
Without this handy context box, users don’t know where the data comes from or how to improve its configuration.
Let’s take this quick Q&A, for example: Where does the automated data come from?
It can come from:
- Card transaction
- An attached document
- Customer’s historical data using Payhawk AI
- Selected supplier
- The employee/team of the expense
- A linked purchase order
And the list is continually growing, so expect more in the near future…
Here’s an example of what the automation tooltips look like for expenses (below). The box will become visible when you click on the field, helping give context and reassurance to you or another user.
