[mikeyouse]

In many businesses, the employee is responsible for inputting most of that. If a LLM can get to 95% accuracy and flag exceptions, the employees (and AP team) would actually have less work and bureaucracy.

Though we’ve had a few incidents where employees have submitted AI-generated receipts for reimbursement which is another issue..

[notahacker]

It's already pretty common for some sort of tool involving some sort of AI to collect receipt data and attempt to categorise them and hook up to your accounts. They also make mistakes, though the advantage of more tractable, less configurable and more limited models is they're unlikely to interpret a prompt as "invent receipts that have never been submitted" or "delete records", as well as trained much more on receipt OCR and less on poetry....

As a business, you've also got to remember that employees are much more likely to complain if the 'agent' or any other form of automation errs by denying their claim or underpaying than the reverse. Depending on the scale of expenses and how likely you are to be audited, the cost of the odd mistake might be more or less than the cost of doing it manually.

[Zopieux]

Please tell me those are former employees. How can anyone feel confident committing such blatant fraud.

[mikeyouse]

Yeah the ones that were just fraud we termed almost immediately.. there were a few in the middle ground of where they’d lost their receipts (or decided that fabricating a receipt was easier) but we could verify that the expense actually took place from a cc statement. We added an extra approval step for those employees going forward which is annoying for everyone involved so hopefully they’ve learned their lesson there.