For those of you who work in finance, have you ever had a perfect invoice come across your desk? Error-free, no handwritten notes, perfect in every way?
Sure, it can happen. But a perfect invoice is rare enough we’re positive you do a happy dance whenever you don’t have to spend a lot time correcting the invoice.
Invoices are tricky to navigate because you must go over it with a fine-tooth comb to ensure it matches the contract terms, contains no typos and the numbers are correct. Tedious, boring, time-consuming work.
Then you have the added headache of missing something on the invoice and overpaying. No one likes the game of pay and chase. No one.
Let’s talk about invoice fraud. Anything from double charges to false invoices charging for services never performed, fraud can be difficult to detect if it is only manually processed. Intentional or accidental, invoice fraud is a serious concern that can affect a company’s bottom line.
Don't fret! We have a solution. ElectrifAi machine learning provides deep insights to find the darkest corners of your invoice web. From navigating contract terms to highlighting concerning invoices, ElectrifAi takes out the hard work from invoice processing while simultaneously reducing risks.
Sounds great, right? Read on to find out about invoice concerns and how machine learning can detect fraud and errors.
Large corporations are most susceptible. Sometimes millions of dollars are affected but usually an auditor would pick up on that right away. We’re talking about small incidents that would be hard to detect by someone processing tons of invoices a day.
Sometimes invoices can be mistakenly sent for services never performed and we hope those sending the invoices would point out the error. Some contractors, however, set out with fraudulent intent.
Imagine a contractor invoicing every three weeks instead of monthly. Once a year, the contractor would be paid an extra month due to that 3-week billing cycle.
Unless the accountant processing the invoices has a photographic memory or the contractor has a very unusual name, it’s unlikely the trick would be detected. An auditor may not pick it up either if they only process random batches of invoices. A company would have to resort to an entire team of auditors to review every invoice and match it to the contract terms and ensure the numbers aligned to the services performed.
Along with invoicing on a 3-week cycle, another trick to watch for are duplicate or inflated invoices. Duplicate invoices may be sent at the same time for the same services in the hopes an accountant is just routinely processing invoices and not checking. Inflated invoices increase the amount of time worked or charging more for services than indicated in the contract.
Quite often, invoices with rounded amounts are made in error instead of sent with fraudulent intent. Equally concerning, though, if you process hundreds or thousands of these invoices. If the amount is rounded up $0.47 times 1,000, that equals $470 lost from a clerical error. Pocket change for large corporations, sure, but if you add that up for many contractors or suppliers it can be damaging.
While many companies are transforming their processes from handwritten invoices to digital, it’s still a common practice to handwrite notes on the invoice. If you use an automated invoice processing, this will cause an error and take even more time to go back to the invoice to manually process.
Traditional handwritten invoices can also be altered, leading to complications on both sides. Further, if you must keep a paper copy to have the original invoice for record-keeping, that takes up a lot of storage room and the copy can degrade over time. And losing the invoice? Cringe-worthy.
The risks of incorrect or fraudulent payment of invoices goes beyond just financial. Depending on the goods or the services and the size of the discrepancy, there may also be legal risks. These risks would most often be associated with tax liabilities; however, there are also risks of legal payment requirements for contracted labor. Keeping a close eye on invoices and ensuring payments are correct keeps the lawyers away.
ElectrifAi recently spoke with a large company who said they were only able to get 25% of the info off invoices correctly when using automation. That means 75% of their invoices had to be reprocessed manually! Oftentimes, there are companies with 50 or more people going through invoices manually. That’s a lot of manpower and money spent on payroll.
Machine learning can help detect invoice fraud and general errors much, much faster than manual processing. It starts with being able to accurately take an invoice apart and figure out, despite sometimes crazy formatting, exactly what the invoice states.
Invoices are made up of unstructured data. ElectrifAi structures that data to get key information with over 90-95% accuracy. We can use invoices in PDF format, they are sent electronically, ones that have been printed or faxed, anything like that. We can take the image and clean it up with OCR (optical character recognition). The data generated is then fed into the fraud detection model and what’s happening on the invoice versus what should occur based on the contract will be discovered.
You can expect some fluctuation from one week to another on a certain contract as a service outside the contract may have been performed. But if the invoice is 50% more or doubled you can flag that as a potential problem. That’s just one of the many things the machine learning model looks at to indicate if the invoice is incorrect.
Machine learning can also make an auditor’s job more efficient. By using machine learning, you can triage the invoices and tell the auditors here are 10 things that look bad, start your day there.
The best part is machine learning can work on invoices in any industry! ElectrifAi works across all verticals. In our case, we are not limited to direct versus indirect spend or some of the other gotchas you can run into with other systems. We can take any type of invoice for any service, product or spend.
When we talk to people about their invoice concerns, they almost always say yes, we could really use machine learning to help us because we find so many errors on our invoices. Or our current automation processes are ineffective. For those people who say they haven’t come across any errors, then they really need to speak with ElectrifAi because that means they haven’t been catching the errors!
Invoice fraud and errors are a common occurrence. Thankfully, most errors are not intentional and are generally caused by typos. Some people, however, have low morals and will seek money they didn’t earn.
Keep your company and assets safe by using machine learning capabilities to process, sort, and find errors. Getting ElectrifAi to help you with your invoices is a great insurance policy against something going very wrong – it happens more often than people think. Machines love crunching numbers and sorting through tedious invoices, so let them do the hard work for you!
