How Euro Car Parts found £250,000 in duplicate payments

Customer Story

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Invoice errors are inevitable when you process a high volume of invoices, even with a world-class AP team and tools. Operating 300 branches and stocking 160,000 parts, the finance team at Euro Car Parts – the UK’s leading distributor of car parts – were painfully aware they needed more control against the risk of invoice errors.

Baz Durrani is ECP’s Continuous Improvement Manager. When he joined in 2018, his first remit was to review and improve the Procure-to-Pay system. The company had a basic process that created many inaccurate results (false positives). It was time-consuming, and the real risks were hidden in the noise of false positives.

“90% of our invoice processing used OCR scanning technology. It would scan each PDF for key data and send the XML file to our ERP system. Far from perfect technology, it was heavily dependent on the quality of data coming in. For example, scanning errors could occur when an ‘s’ was read as a 5, or an 8 was interpreted as a zero.

"We only had three variables to work with when checking for duplicates: invoice number, invoice date, and invoice value. Whenever we looked for duplicates, we ended up with loads of false positives. In fact, it was one person’s full-time job to process the potential problems,” says Baz.

Reducing false positives

Like 90% of ERP solutions, the system in place at ECP could only check for exact match duplicates, leaving the business at risk of errors and threats. To better capture indirect invoices, ECP had already added Coupa to its technology stack. Whilst this had given ECP better control, it also was only capable of highlighting exact match duplicates.

Keen to address this problem, Baz first looked at an in-house solution using queries in Microsoft Access. This carried too much reliance on manual checks, and ECP was still limited to exact matches. Baz explains: “We downloaded some of our incoming documents to Microsoft Access, still only able to work with the same three variables: invoice number, date, and value. But Access could only identify a duplicate where, for example, it discovered 1234 twice. It wouldn’t pick up an entry of 1235 and question it. There was no intelligence to achieve that level of checking.

"At one point, we tried looking at invoice value only. But that dramatically increased suspected duplicates. For some suppliers, every invoice can be the same value. So, someone had to physically check every single one, which could create further human errors.”

Discovering the value of AI

When Baz came across Xelix, the difference was immediately clear. “Straightaway Xelix was visually appealing. But the thing that got us most was how it learned. For example, it learnt invoice patterns, meaning our duplicates would reduce rapidly. It didn’t waste our time. Xelix checks for over 300 different variables - not three. ”

Setting up Xelix was relatively easy, says Baz. It was flexible in the required files and could be up and running in a week. The Xelix team were on even hand to help as they worked to extract data from Babbage, "an ERP that's not very user-friendly."

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Retrospective duplicate checking exercise

Having worked with Xelix for some time, Baz is clear on the transformation it’s delivered for ECP from day one. He explains, “We first did a retrospective duplicate checking exercise with documents from the last two years. This resulted in us recovering £250,000 on day one. It’s a huge return and covered the cost of Xelix for years to come.”

A second transformation concerned staff efficiency and impact: “Because Xelix all but eliminated false positives, they were only looking at the realistic duplicates. This reduced the workload from two hours to ten minutes a day.”

They now have time to tackle the root causes of any duplicates to stop them from happening again. "It’s been a huge saving for us. Everyone quickly bought in to something that would put an end to firefighting and make the job much easier.”

It’s not just duplicate checking. ECP is successfully using Xelix to identify ledger errors, such as incorrect VAT and invoices posted to the wrong supplier. For example, using self-learning, Xelix flags when a supplier or an account code looks out of place.

Another benefit is how Xelix continually reviews master and transactional data, helping to keep it clean.“Xelix gives you that master data cleanse tool, which is a big challenge for any business. It’ll flag supplier duplicates and little-used vendors. And it’ll spot potential errors with account coding,” says Baz.

Reduce your risks

While some organisations fear the onset of AI, Baz is clear it’s “the way forward” because it eliminates the risk of human error and is self- learning. But what about jobs?

“You shouldn’t always see AI as a threat to people losing their jobs. We’ve demonstrated that clearly, utilising the saved resources elsewhere in the business. So, we’ve had more resource to tackle the root causes of duplicates and radically improve our processes.”